{ "data": { "a": { "slug": "lfm3-1-7b", "name": "LFM3-1.7B", "vendor": "Liquid AI", "vendorUrl": "https://www.liquid.ai", "kind": "weights", "category": "open-weights", "summary": "LFM3-1.7B is Liquid AI's open-weight 1.73B text model for on-device agents, with tool calling, deferred tools, switchable thinking and a 256K-token context, released on 27 October 2026 with Liquid's own GGUF, FP8, NVFP4, MLX and ONNX builds.", "url": "https://www.anchorterminal.com/tools/lfm3-1-7b", "markdownUrl": "https://www.anchorterminal.com/tools/lfm3-1-7b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/lfm3-1-7b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/lfm3-1-7b.json", "dns": "lfm3-1-7b.grade.anchorterminal.com", "repo": "https://huggingface.co/LiquidAI/LFM3-1.7B", "license": "LFM Open License v1.0 (free commercial use below $10M annual revenue)", "transports": [], "packages": [ { "registry": "huggingface", "name": "LiquidAI/LFM3-1.7B" }, { "registry": "huggingface", "name": "LiquidAI/LFM3-1.7B-GGUF" }, { "registry": "huggingface", "name": "LiquidAI/LFM3-1.7B-MLX-4bit" }, { "registry": "ollama", "name": "lfm3" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository and Liquid's GGUF, MLX and ONNX repositories are not gated (checked 2026-11-10).", "pricing": "free", "pricingNotes": "Free to download and use under the LFM Open License v1.0, commercial use included for organisations with under $10M in annual revenue; above that, commercial use isn't licensed. Running it yourself costs little hardware, 1.10 GB for Liquid's Q4_K_M GGUF and 3.46 GB in BF16. Liquid's API also serves it, at prices shown in its console (checked 2026-11-10).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-10" }, "docsUrl": "https://docs.liquid.ai/lfm/models/lfm3-1.7b", "llmsTxt": "https://docs.liquid.ai/llms.txt", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "dense", "small", "edge", "reasoning", "tool-calling", "long-context", "custom-licence", "safetensors", "gguf", "mlx", "onnx", "self-hosted" ], "lastRelease": "2026-11-09", "graded": true, "anchor": { "graded": true, "score": 61, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1518, "categoryRank": 55, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 100, "reach": 85, "risk": 40, "upkeep": 67 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "A 1.73B model that fits an 8 GB machine with room to spare, with a documented tool-call format, deferred tools, a thinking switch and a 256K context. It runs today in llama.cpp, Ollama and LM Studio only, loads in Transformers through repository code, and has no safety results, security contact or data sources.", "bestFor": "Agents on a laptop, phone or small server that need tool calling and a long context from a model under 2 GB at 4 bits", "strengths": [ "Fits an 8 GB machine from Liquid's own GGUF, at 1.10 GB for Q4_K_M", "The card and docs document the tool-call format, deferred tools and tool search", "A 256K-token context, trained in mid-training per the card", "Thinking can be turned off per request", "Liquid's own API serves it, and its guide documents JSON Schema output" ], "weaknesses": [ "vLLM and SGLang have no released support, though the card lists both", "Loading in Transformers runs code from the repository", "No safety results and no security contact", "Liquid says turning thinking off can be inconsistent", "The licence stops free commercial use at $10M in annual revenue", "Training data is described without sources or a cut-off" ], "agentNotes": [ "Start it with `llama-server -hf LiquidAI/LFM3-1.7B-GGUF:Q4_K_M --jinja` or `ollama run lfm3`", "Use temperature 0.1, top_k 50 and repetition penalty 1.1 for chat, tools and agents, per the card", "Pass `enable_thinking=False` for direct answers, and expect it to reason anyway on hard tasks", "For a large tool catalogue mark tools `defer_loading` and give it a search tool", "Don't plan on vLLM or SGLang until a release carries LFM3", "Liquid doesn't recommend it for agentic coding or complex multi-step reasoning" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "interface": 100, "reach": 85, "risk": 40, "upkeep": 67 }, "provenanceScore": 73, "checked": { "categories": { "interface": "2026-11-10", "reach": "2026-11-10", "risk": "2026-11-10", "upkeep": "2026-11-10" }, "last": "2026-11-10", "oldest": "2026-11-10", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "llama-server -hf LiquidAI/LFM3-1.7B-GGUF:Q4_K_M --jinja\n# or\nollama run lfm3", "http": "curl http://localhost:8080/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -d '{\"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/lfm3-1-7b" }, "sameCompany": [ "liquid-d1", "lfm2-5-2-6b", "lfm3-audio-2b", "lfm3-omni-2b", "lfm3-vl-2b" ], "weights": { "trainedBy": "Liquid AI", "builtOn": "LiquidAI/LFM3-1.7B-Base", "params": "1.73B", "context": 262144, "goodFor": "Small on-device agent model for tool calling, tool search over large catalogues, structured output and long-context work on a laptop or phone, not for agentic coding or complex multi-step reasoning.", "runtimes": [ "llama.cpp", "Ollama", "LM Studio" ], "builds": [ { "name": "LFM3-1.7B", "url": "https://huggingface.co/LiquidAI/LFM3-1.7B", "who": "publisher", "precision": "bf16", "sizeGB": 3.46, "memoryGB": 8, "format": "safetensors", "runsOn": [ "Transformers" ], "note": "Loads in Transformers with the repository's own code. Liquid also publishes FP8 (2.21 GB) and NVFP4 (1.83 GB) safetensors builds, which the card pairs with SGLang, and an ONNX repository" }, { "name": "LFM3-1.7B-GGUF Q8_0", "url": "https://huggingface.co/LiquidAI/LFM3-1.7B-GGUF", "who": "publisher", "precision": "q8_0", "sizeGB": 1.85, "memoryGB": 8, "format": "gguf", "runsOn": [ "llama.cpp", "LM Studio" ] }, { "name": "LFM3-1.7B-GGUF Q4_K_M", "url": "https://huggingface.co/LiquidAI/LFM3-1.7B-GGUF", "who": "publisher", "precision": "q4_k_m", "sizeGB": 1.1, "memoryGB": 8, "format": "gguf", "runsOn": [ "llama.cpp", "LM Studio" ], "note": "LFM3-1.7B-Q4_K_M.gguf, from the Hub's file list. The repository also holds a quantisation-aware LFM3-1.7B-QAD-Q4_0.gguf (1.05 GB), Q8_0, F16 and BF16 files" }, { "name": "LFM3-1.7B-MLX-4bit", "url": "https://huggingface.co/LiquidAI/LFM3-1.7B-MLX-4bit", "who": "publisher", "precision": "4bit", "sizeGB": 0.97, "memoryGB": 8, "format": "mlx", "runsOn": [ "MLX" ], "note": "Liquid also publishes 5, 6 and 8-bit and BF16 MLX builds" }, { "name": "ollama lfm3", "url": "https://ollama.com/library/lfm3", "who": "ollama", "precision": "q4_k_m", "sizeGB": 1.1, "memoryGB": 8, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Ollama's library build, size as its tags page shows it on 10 November 2026. The library also has q8_0, bf16, mxfp8 and nvfp4 tags" } ], "run": "llama-server -hf LiquidAI/LFM3-1.7B-GGUF:Q4_K_M --jinja", "runBuild": "LFM3-1.7B-GGUF Q4_K_M", "checked": "2026-11-10", "minMemoryGB": 8 }, "family": { "lab": "Liquid AI", "family": "LFM3", "url": "https://www.anchorterminal.com/open-weights/#liquid", "others": [ { "name": "LFM3-1.7B-Base", "url": "https://huggingface.co/LiquidAI/LFM3-1.7B-Base", "params": "1.73B" }, { "name": "LFM3-VL-2B", "url": "https://huggingface.co/LiquidAI/LFM3-VL-2B", "params": "1.92B", "listing": "https://www.anchorterminal.com/tools/lfm3-vl-2b" }, { "name": "LFM3-Omni-2B", "url": "https://huggingface.co/LiquidAI/LFM3-Omni-2B", "params": "2.17B", "listing": "https://www.anchorterminal.com/tools/lfm3-omni-2b" }, { "name": "LFM3-Audio-2B", "url": "https://huggingface.co/LiquidAI/LFM3-Audio-2B", "params": "2.00B", "listing": "https://www.anchorterminal.com/tools/lfm3-audio-2b" } ] }, "area": "models", "provenance": { "legalEntity": "Liquid AI, Inc. (the licensor named in the LFM Open License)", "domain": "liquid.ai", "domainRegistered": "2017-12-16", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/LiquidAI/LFM3-1.7B/commits/main", "securityTxt": "none", "checked": "2026-11-10", "notes": [ "The licence names Liquid AI, Inc. as licensor. The domain's registration date is as recorded on the liquid-d1 listing on 8 October 2026", "www.liquid.ai/.well-known/security.txt answered 404 on 10 November 2026" ], "score": 73 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/lfm3-1-7b.json" }, "answer": "LFM3-1.7B and Ornith-1.5-122B score within a point of each other on agent readiness, 61 (C) and 61 (C). Ornith-1.5-122B leads on risk.", "b": { "slug": "ornith-1-5-122b", "name": "Ornith-1.5-122B", "vendor": "Ornith", "vendorUrl": "https://ornith.ai", "kind": "weights", "category": "open-weights", "summary": "Ornith-1.5-122B is Ornith's open-weight mixture-of-experts reasoning model for coding and agent work, about 125B parameters on Qwen3.5's architecture with a 262,144-token context, published in BF16, FP8, NVFP4, GGUF and MLX and marked MIT.", "url": "https://www.anchorterminal.com/tools/ornith-1-5-122b", "markdownUrl": "https://www.anchorterminal.com/tools/ornith-1-5-122b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/ornith-1-5-122b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/ornith-1-5-122b.json", "dns": "ornith-1-5-122b.grade.anchorterminal.com", "repo": "https://huggingface.co/ornith-ai/Ornith-1.5-122B", "license": "MIT", "transports": [], "packages": [ { "registry": "huggingface", "name": "ornith-ai/Ornith-1.5-122B" }, { "registry": "huggingface", "name": "ornith-ai/Ornith-1.5-122B-GGUF" }, { "registry": "huggingface", "name": "ornith-ai/Ornith-1.5-122B-FP8" }, { "registry": "huggingface", "name": "ornith-ai/Ornith-1.5-122B-NVFP4" }, { "registry": "huggingface", "name": "ornith-ai/Ornith-1.5-122B-MLX-4bit" }, { "registry": "ollama", "name": "ornith-1.5:122b-q4_K_M" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The main repository and Ornith's six build repositories for this size are not gated (checked 2026-11-10).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under the MIT licence named in the card's metadata. The repository has no LICENSE file, and the card's licence link returns 404. Running it yourself costs the hardware, about 250 GB for the BF16 files, 69.7 GB for Ornith's MLX 4-bit build or 75.8 GB for its Q4_K_M GGUF (checked 2026-11-10).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-10" }, "docsUrl": "https://huggingface.co/ornith-ai/Ornith-1.5-122B", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "reasoning", "tool-calling", "coding", "mit", "safetensors", "gguf", "mlx", "fp8", "nvfp4", "self-hosted" ], "lastRelease": "2026-10-24", "graded": true, "anchor": { "graded": true, "score": 61, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1518, "categoryRank": 64, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 85, "reach": 75, "risk": 50, "upkeep": 36 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "The largest Ornith that fits a 128 GB machine, a coding and terminal-agent cousin on Qwen3.5-122B-A10B's architecture with XML tool calls and 262,144 tokens of context. Its 4-bit builds need 84 to 93 GB. The main risk is an absent publisher, with no licence file, safety results or replies, and a card that misstates the hardware.", "bestFor": "Local coding and terminal agents on a 128 GB unified-memory machine or a 96 GB GPU setup, where a clear licence file and an answering publisher aren't required", "strengths": [ "4-bit builds from Ornith itself in GGUF, MLX and NVFP4, at 70 to 78 GB, plus Ollama's Q4_K_M", "Runs in vLLM, SGLang, Transformers, llama.cpp, Ollama and LM Studio from their released versions", "The card names the tool and reasoning parsers for vLLM and SGLang, with a tool-call example", "262,144 tokens of native context", "Safetensors and GGUF only, no gate and no code in the repository" ], "weaknesses": [ "No LICENSE file though the card links one, and no notice for the Apache 2.0 Qwen3.5 and Gemma 4 work it builds on", "No safety evaluation, agent-use guidance or security contact", "The card says a single 80 GB GPU serves it, which its 250 GB of BF16 files don't fit, and names a Mobile variant that isn't published", "Ornith answered none of the 5 discussions, and the MLX builds were uploaded again with no note", "The two chat templates disagree on keeping earlier reasoning, and structured output isn't documented" ], "agentNotes": [ "Start it with `ollama run ornith-1.5:122b-q4_K_M`, or `llama-server -hf ornith-ai/Ornith-1.5-122B-GGUF:Q4_K_M --jinja -c 262144`", "Budget about 92 GB for the Q4_K_M GGUF with a working context, and less context if the machine has under 100 GB for the model", "In vLLM pass `--enable-auto-tool-choice --tool-call-parser qwen3_xml --reasoning-parser qwen3`, and in SGLang `--tool-call-parser qwen3_coder --reasoning-parser qwen3`, so tool calls and reasoning come back parsed", "Thinking is on by default. Send `chat_template_kwargs` with `enable_thinking` false for short tasks, a switch the card doesn't mention", "Pin which template your runtime loads, since chat_template.jinja keeps earlier reasoning and the tokenizer_config.json template drops it", "Use temperature 0.6, top_p 0.95, top_k 20 for coding and temperature 1.0 for general tasks, as the card recommends", "Add mmproj-Ornith-1.5-122B-BF16.gguf (0.9 GB) for image input in llama.cpp, and validate JSON output yourself, since structured output isn't documented" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "interface": 85, "reach": 75, "risk": 50, "upkeep": 36 }, "provenanceScore": 19, "checked": { "categories": { "interface": "2026-11-10", "reach": "2026-11-10", "risk": "2026-11-10", "upkeep": "2026-11-10" }, "last": "2026-11-10", "oldest": "2026-11-10", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "ollama run ornith-1.5:122b-q4_K_M\n# or, with llama.cpp and Ornith's own GGUF:\nllama-server -hf ornith-ai/Ornith-1.5-122B-GGUF:Q4_K_M --jinja -c 262144\n# or, with the card's vLLM command (abridged):\nvllm serve ornith-ai/Ornith-1.5-122B --served-model-name Ornith-1.5-122B --max-model-len 262144 \\\n --enable-auto-tool-choice --tool-call-parser qwen3_xml --reasoning-parser qwen3", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"ornith-1.5:122b-q4_K_M\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/ornith-1-5-122b" }, "sameCompany": [ "ornith-1-5-35b-a3b", "ornith-1-5-397b", "ornith-1-5-9b" ], "weights": { "trainedBy": "Ornith", "builtOn": "Qwen3.5-122B-A10B, inferred. Not declared in the metadata. Same qwen3_5_moe architecture and an identical parameter count to Qwen3.5-122B-A10B (Apache 2.0); the card says Ornith-1.0 was built on Qwen3.5 and Gemma 4 and that 1.5 extends it", "params": "125B", "context": 262144, "goodFor": "Coding and terminal-agent mixture-of-experts model with tool calling and thinking on by default, text and images in, the largest Ornith that fits a 128 GB machine at 4 bits.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Ornith-1.5-122B-NVFP4", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-122B-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 77.7, "memoryGB": 96, "format": "safetensors", "note": "NVFP4 needs NVIDIA Blackwell" }, { "name": "Ornith-1.5-122B-Q4_K_M", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-122B-GGUF/blob/main/Ornith-1.5-122B-Q4_K_M.gguf", "who": "publisher", "precision": "q4_k_m", "sizeGB": 75.8, "memoryGB": 96, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ], "note": "Add mmproj-Ornith-1.5-122B-BF16.gguf (0.9 GB) for image input" }, { "name": "Ornith-1.5-122B-MLX-4bit", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-122B-MLX-4bit", "who": "publisher", "precision": "4bit", "sizeGB": 69.7, "memoryGB": 96, "format": "mlx", "note": "MLX runs on Apple silicon only" }, { "name": "ollama ornith-1.5:122b-q4_K_M", "url": "https://ollama.com/library/ornith-1.5:122b-q4_K_M", "who": "ollama", "precision": "q4_k_m", "sizeGB": 77, "memoryGB": 96, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Q4_K_M (76 GB) with a BF16 vision projector (912 MB), as Ollama's tag page shows it, rounded to whole GB. The 73 GB ornith-1.5:122b tag is marked for MLX and llama.cpp and its quantisation wasn't established, so it isn't listed as a build" }, { "name": "Ornith-1.5-122B-Q6_K", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-122B-GGUF/blob/main/Ornith-1.5-122B-Q6_K.gguf", "who": "publisher", "precision": "q6_k", "sizeGB": 102.4, "memoryGB": 128, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ] }, { "name": "Ornith-1.5-122B-Q5_K_M", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-122B-GGUF/blob/main/Ornith-1.5-122B-Q5_K_M.gguf", "who": "publisher", "precision": "q5_k_m", "sizeGB": 88.7, "memoryGB": 128, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ] }, { "name": "Ornith-1.5-122B-FP8", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-122B-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 133, "memoryGB": 192, "format": "safetensors", "runsOn": [ "vLLM", "SGLang" ], "note": "Too big for the 128 GB reference machine" }, { "name": "Ornith-1.5-122B-Q8_0", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-122B-GGUF/blob/main/Ornith-1.5-122B-Q8_0.gguf", "who": "publisher", "precision": "q8_0", "sizeGB": 132.6, "memoryGB": 192, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ], "note": "Too big for the 128 GB reference machine" }, { "name": "Ornith-1.5-122B-MLX-8bit", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-122B-MLX-8bit", "who": "publisher", "precision": "8bit", "sizeGB": 130.7, "memoryGB": 192, "format": "mlx", "note": "MLX runs on Apple silicon only" }, { "name": "Ornith-1.5-122B", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-122B", "who": "publisher", "precision": "bf16", "sizeGB": 250.2, "memoryGB": 512, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)" ], "note": "Too big for the 128 GB reference machine" }, { "name": "Ornith-1.5-122B-BF16", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-122B-GGUF/blob/main/Ornith-1.5-122B-BF16.gguf", "who": "publisher", "precision": "bf16", "sizeGB": 249.4, "memoryGB": 512, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ], "note": "Too big for the 128 GB reference machine" }, { "name": "Ornith-1.5-122B-MLX", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-122B-MLX", "who": "publisher", "precision": "bf16", "sizeGB": 245.2, "memoryGB": 512, "format": "mlx", "note": "MLX runs on Apple silicon only" } ], "run": "ollama run ornith-1.5:122b-q4_K_M", "runBuild": "ollama ornith-1.5:122b-q4_K_M", "checked": "2026-11-10", "minMemoryGB": 96 }, "family": { "lab": "Ornith", "family": "Ornith-1", "url": "https://www.anchorterminal.com/open-weights/#ornith", "others": [ { "name": "Ornith-1.0-9B", "url": "https://huggingface.co/ornith-ai/Ornith-1.0-9B", "params": "9B (dense)" }, { "name": "Ornith-1.0-35B", "url": "https://huggingface.co/ornith-ai/Ornith-1.0-35B", "params": "35B (MoE)" }, { "name": "Ornith-1.0-397B", "url": "https://huggingface.co/ornith-ai/Ornith-1.0-397B", "params": "397B (MoE)" }, { "name": "Ornith-1.5-9B", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-9B", "params": "9B (dense)", "listing": "https://www.anchorterminal.com/tools/ornith-1-5-9b" }, { "name": "Ornith-1.5-9B-DFlash", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-9B-DFlash", "params": "1.29B (Hub safetensors count)" }, { "name": "Ornith-1.5-35B-A3B", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-35B-A3B", "params": "35B total, 3B active (MoE)", "listing": "https://www.anchorterminal.com/tools/ornith-1-5-35b-a3b" }, { "name": "Ornith-1.5-35B-A3B-DFlash", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-35B-A3B-DFlash", "params": "0.39B (Hub safetensors count)" }, { "name": "Ornith-1.5-397B", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-397B", "params": "397B (MoE)", "listing": "https://www.anchorterminal.com/tools/ornith-1-5-397b" }, { "name": "Ornith-1.5-397B-DFlash", "url": "https://huggingface.co/ornith-ai/Ornith-1.5-397B-DFlash", "params": "1.29B (Hub safetensors count)" } ] }, "area": "models", "provenance": { "legalEntity": "", "domain": "ornith.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-11-10", "notes": [ "No legal entity named on the card, the blog or the repository. The citation reads Ornith Team. Ollama's copy of the licence names deepreinforce.ai as the copyright holder.", "Nothing is hosted, so the licence stands in for terms of service and no privacy policy is scored. The licence is MIT in the card's metadata only; the LICENSE file the card links returns 404.", "No changelog for the files. The commit messages are uploads, deletions and README updates.", "ornith.ai/.well-known/security.txt redirects to the home page, so there is no security.txt.", "unchecked: the domain's registration date." ], "score": 19 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/ornith-1-5-122b.json" }, "edges": [ { "by": 31, "category": "upkeep", "leads": "lfm3-1-7b", "name": "Documentation and upkeep", "reasons": { "a": "Model card 17, Intended use (local agents, tool calling, structured outputs, fine-tuning), a limitation (not recommended for agentic coding or complex multi-step reasoning), architecture (24 layers: 13 gated short convolutions, 5 sliding-window and 6 global attention), parameters (1.73B), context (256K) and 16 languages. Training data 5, A general description: 22T tokens of pre-training in two stages with the kinds of data added since LFM2, 1.75T tokens of supervised fine-tuning, then mixed reinforcement learning, distillation from six specialist teachers and agentic reinforcement learning. Last change 20, the last commit, on 9 November 2026, added the OpenVINO checkpoint to the card's inference table, a day before this check. Responsiveness 10, Of the 22 discussions that aren't pull requests (27 October to 8 November 2026), 7 have a reply from a LiquidAI member, which is some. Version policy 5, LFM3 came out in new repositories and the LFM2.5 models stay in theirs. File health 10, Config, template and card agree on the lfm3 architecture, the 262,144-token context and the thinking switch. 17 + 5 + 20 + 10 + 5 + 10 = 67.", "b": "Model card 11, it covers intended use, architecture, parameters and context but not limitations, languages or a knowledge cut-off. Training data 5, a description of the method with no data or cut-off. Last change 20, a folder upload to the MLX builds on 24 October 2026, 17 days ago. Responsiveness 0, Ornith answered none of the 5 questions and reports. Version policy 0, the MLX builds were uploaded a second time four days after the first with no note. File health 0, the card links a missing LICENSE, states hardware its own files don't fit and names a variant that doesn't exist, and the two chat templates differ. 11 + 5 + 20 + 0 + 0 + 0 = 36." }, "scores": { "a": 67, "b": 36 } }, { "by": 15, "category": "interface", "leads": "lfm3-1-7b", "name": "Agent interface", "reasons": { "a": "Chat template 20, chat_template.jinja in the repository (12,129 characters), with roles, tools, deferred tools, tool results and the thinking switch. Tool-calling format 25, the card and Liquid's tool-use page document tools passed through `tools=` in apply_chat_template, calls returned as XML and results sent back as tool messages. Trained tool calling 20, the template loops over every entry in an assistant turn's tool_calls, so several calls fit in one turn, and the card says the model was trained on tool calls and agentic traces and with reinforcement learning inside agent harnesses. Structured output 15, Liquid's API guide documents `response_format` with a JSON Schema, with lfm3-1.7b as the model in its examples, and says the schema is checked before generation starts. Reasoning control 10, the card documents `enable_thinking=False` in the chat template to turn reasoning off per request, with reasoning on by default inside think tags, and `preserve_thinking` for earlier turns. Context 10, 256K tokens per the card, which says the mid-training stage extended the context window to 256K, and max_position_embeddings 262144 in config.json. 20 + 25 + 20 + 15 + 10 + 10 = 100.", "b": "Chat template 20, a Jinja file in the repository. Tool-calling format 25, the card shows how tools go in and how calls come back and names the parser for vLLM and SGLang. Trained tool calling 20, Ornith trains it on agent tasks and the template renders several calls in one turn. Structured output 0, not documented or claimed. Reasoning control 10, Ornith's template reads enable_thinking per request and the card says the reasoning comes back in reasoning_content, though the card doesn't name the switch. Context 10, 262,144 tokens native." }, "scores": { "a": 100, "b": 85 } }, { "by": 10, "category": "reach", "leads": "lfm3-1-7b", "name": "Reach", "reasons": { "a": "Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB, and 1.10 GB × 1.2 = 1.3 GB, which fits 8 GB, well inside the 16 GB line. Runtimes 15, Released llama.cpp has the lfm3 architecture (src/models/lfm3.cpp at b12242), Ollama's library has an lfm3 entry, and LM Studio's catalogue runs the architecture (its liquid/lfm3-vl-2b entry; lmstudio-community publishes a GGUF of this model). Builds 15, Liquid's GGUF repository holds Q4_0, Q4_K_M, Q8_0, F16 and BF16 files, and Liquid publishes 4-bit and 8-bit MLX builds and an ONNX repository, all in the LiquidAI organisation. Terms 10, the LFM Open License v1.0, a custom licence that lets anyone use it commercially for free below a threshold of $10M annual revenue. Download 10, the Hub API reports gated false for the model and its GGUF, MLX and ONNX repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, Liquid's own API lists lfm3-1.7b among its models, so the publisher hosts it. 30 + 15 + 15 + 10 + 10 + 5 = 85.", "b": "Memory 10, since Ornith's own MLX 4-bit build is 69.7 GB and needs about 83.6 GB with the fifth added, over 64 GB and inside the reference machine's 107.4 GB, as do its Q4_K_M GGUF, its NVFP4 build and Ollama's build. Runtimes 25, the most the line gives, from vLLM 0.33.0, SGLang 0.5.23, Transformers 5.22.2, llama.cpp's qwen35moe architecture, Ollama's library and LM Studio's catalogue for the qwen35moe architecture. Builds 15, Ornith publishes FP8, NVFP4, GGUF and MLX at several precisions. Terms 15, MIT as named in the card's metadata, with nothing added, read by its terms though the repository has no licence file. Download 10, nothing is gated. Hosted 0, Ornith runs no API and no inference provider serves it. 10 + 25 + 15 + 15 + 10 + 0 = 75." }, "scores": { "a": 85, "b": 75 } }, { "by": 10, "category": "risk", "leads": "ornith-1-5-122b", "name": "Risk", "reasons": { "a": "File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, files in the LiquidAI organisation, which Liquid's docs page for the model and its blog post link to (10). Safety evaluation 0, no safety results on the card or in Liquid's blog post for the LFM3 family, neither of which mentions safety testing. Agent guidance 0, Nothing on prompt injection, an instruction hierarchy, what refusals cover or safeguards to add. Licence risk 10, 15 less 5 for the $10M annual revenue threshold on commercial use. Security programme 0, no way to report a flaw found. 15 + 15 + 0 + 0 + 10 + 0 = 40.", "b": "File safety 25, safetensors and GGUF only and no Python in any of Ornith's repositories for this size, so the card's --trust-remote-code flag loads nothing from the repository. Provenance 15, the files come from the ornith-ai organisation Ornith's blog links to, with a SHA-256 for every weight file. Safety evaluation 0 and agent guidance 0, nothing published on either. Licence risk 10, MIT carries no policy, threshold or changeable terms, but the card's licence link is broken. Security programme 0, no security.txt, disclosure policy or security contact." }, "scores": { "a": 40, "b": 50 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Liquid AI", "b": "Ornith", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "LFM Open License v1.0 (free commercial use below $10M annual revenue)", "b": "MIT", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "2026-11-09", "b": "2026-10-24", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" } ], "faq": [ { "answer": "LFM3-1.7B and Ornith-1.5-122B score within a point of each other on agent readiness, 61 (C) and 61 (C). Ornith-1.5-122B leads on risk.", "question": "Which is better for AI agents, LFM3-1.7B or Ornith-1.5-122B?" } ], "goodFor": [ { "aheadOn": [ "Reach, 85 against 75", "Agent interface, 100 against 85", "Documentation and upkeep, 67 against 36" ], "also": null, "goodFor": "Agents on a laptop, phone or small server that need tool calling and a long context from a model under 2 GB at 4 bits", "slug": "lfm3-1-7b", "watchFor": "vLLM and SGLang have no released support, though the card lists both" }, { "aheadOn": [ "Risk, 50 against 40" ], "also": null, "goodFor": "Local coding and terminal agents on a 128 GB unified-memory machine or a 96 GB GPU setup, where a clear licence file and an answering publisher aren't required", "slug": "ornith-1-5-122b", "watchFor": "No LICENSE file though the card links one, and no notice for the Apache 2.0 Qwen3.5 and Gemma 4 work it builds on" } ], "history": null, "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-lfm3-1-7b.json", "title": "Agents-A1-4B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-ornith-1-5-122b.json", "title": "Agents-A1-4B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lfm3-1-7b.json", "title": "Apertus v1.5 8B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-ornith-1-5-122b.json", "title": "Apertus v1.5 8B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lfm3-1-7b.json", "title": "Apodex-1.1-mini vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-ornith-1-5-122b.json", "title": "Apodex-1.1-mini vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-1-7b.json", "title": "Arete-27B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-ornith-1-5-122b.json", "title": "Arete-27B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-1-7b.json", "title": "BigBang-v1 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-ornith-1-5-122b.json", "title": "BigBang-v1 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-lfm3-1-7b.json", "title": "Carbon-X vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-122b.json", "title": "Carbon-X vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/cola2-vs-lfm3-1-7b.json", "title": "Cola2 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/cola2-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/cola2-vs-ornith-1-5-122b.json", "title": "Cola2 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/cola2-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lfm3-1-7b.json", "title": "Cosmos-Reason2-2B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ornith-1-5-122b.json", "title": "Cosmos-Reason2-2B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-1-7b.json", "title": "Darwin-36B-Opus vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ornith-1-5-122b.json", "title": "Darwin-36B-Opus vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-lfm3-1-7b.json", "title": "DeepSeek-V3.2 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-122b.json", "title": "DeepSeek-V3.2 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-lfm3-1-7b.json", "title": "DeepSeek V4.1 Flash vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-ornith-1-5-122b.json", "title": "DeepSeek V4.1 Flash vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-lfm3-1-7b.json", "title": "DeepSeek-V4-Flash-0731 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-ornith-1-5-122b.json", "title": "DeepSeek-V4-Flash-0731 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-lfm3-1-7b.json", "title": "Devstral Small 2 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-ornith-1-5-122b.json", "title": "Devstral Small 2 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-lfm3-1-7b.json", "title": "DiffusionGemma 26B A4B IT vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-ornith-1-5-122b.json", "title": "DiffusionGemma 26B A4B IT vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-1-7b.json", "title": "EXAONE 4.5 33B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-122b.json", "title": "EXAONE 4.5 33B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-lfm3-1-7b.json", "title": "Gemma 4 12B IT vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-ornith-1-5-122b.json", "title": "Gemma 4 12B IT vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-lfm3-1-7b.json", "title": "Gemma 4 26B A4B IT vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-ornith-1-5-122b.json", "title": "Gemma 4 26B A4B IT vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-lfm3-1-7b.json", "title": "Gemma 4 31B IT vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-ornith-1-5-122b.json", "title": "Gemma 4 31B IT vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-lfm3-1-7b.json", "title": "Gemma 4 E2B IT vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-ornith-1-5-122b.json", "title": "Gemma 4 E2B IT vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-lfm3-1-7b.json", "title": "Gemma 4 E4B IT vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-ornith-1-5-122b.json", "title": "Gemma 4 E4B IT vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-lfm3-1-7b.json", "title": "GLM-4.5-Air vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-ornith-1-5-122b.json", "title": "GLM-4.5-Air vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-lfm3-1-7b.json", "title": "GLM-4.7-Flash vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-ornith-1-5-122b.json", "title": "GLM-4.7-Flash vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-1-7b.json", "title": "GLM-5.3-Flash vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-122b.json", "title": "GLM-5.3-Flash vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-1-7b.json", "title": "GLM-5.3 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-122b.json", "title": "GLM-5.3 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-1-7b.json", "title": "gpt-oss-120b vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ornith-1-5-122b.json", "title": "gpt-oss-120b vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-lfm3-1-7b.json", "title": "gpt-oss-20b vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-ornith-1-5-122b.json", "title": "gpt-oss-20b vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-lfm3-1-7b.json", "title": "Granite 4.2 30B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ornith-1-5-122b.json", "title": "Granite 4.2 30B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-lfm3-1-7b.json", "title": "Granite 4.2 3B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-ornith-1-5-122b.json", "title": "Granite 4.2 3B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-1-7b.json", "title": "Granite 4.2 8B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ornith-1-5-122b.json", "title": "Granite 4.2 8B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-lfm3-1-7b.json", "title": "Hy-Memory-30B-A3B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-ornith-1-5-122b.json", "title": "Hy-Memory-30B-A3B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-lfm3-1-7b.json", "title": "Hy3 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/hy3-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-122b.json", "title": "Hy3 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-lfm3-1-7b.json", "title": "Inkling-Small vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-122b.json", "title": "Inkling-Small vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-1-7b.json", "title": "Inkling vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-122b.json", "title": "Inkling vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-lfm3-1-7b.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-ornith-1-5-122b.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-lfm3-1-7b.json", "title": "Kimi K3.1 Pro vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-ornith-1-5-122b.json", "title": "Kimi K3.1 Pro vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-lfm3-1-7b.json", "title": "Kimi K3 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-122b.json", "title": "Kimi K3 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-lfm3-1-7b.json", "title": "Kolibri-1 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-ornith-1-5-122b.json", "title": "Kolibri-1 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/kronos-vs-lfm3-1-7b.json", "title": "Kronos vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/kronos-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/kronos-vs-ornith-1-5-122b.json", "title": "Kronos vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/kronos-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-1-7b.json", "title": "Laguna M.1 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-122b.json", "title": "Laguna M.1 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm3-1-7b.json", "title": "Laguna S 2.1 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-122b.json", "title": "Laguna S 2.1 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-1-7b.json", "title": "Laguna XS 2.1 vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-122b.json", "title": "Laguna XS 2.1 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-lfm3-1-7b.json", "title": "LBS-27B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-122b.json", "title": "LBS-27B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-lfm3-1-7b.json", "title": "LFM2.5-2.6B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-ornith-1-5-122b.json", "title": "LFM2.5-2.6B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-lfm3-audio-2b.json", "title": "LFM3-1.7B vs LFM3-Audio-2B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-lfm3-audio-2b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-lfm3-omni-2b.json", "title": "LFM3-1.7B vs LFM3-Omni-2B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-lfm3-omni-2b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-lfm3-vl-2b.json", "title": "LFM3-1.7B vs LFM3-VL-2B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-lfm3-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ling-3-0-tiny.json", "title": "LFM3-1.7B vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ling-3-0-tiny" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ling-3-1-flash-1019.json", "title": "LFM3-1.7B vs Ling-3.1-flash-1019", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ling-3-1-flash-1019" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-longcat-2-5.json", "title": "LFM3-1.7B vs LongCat-2.5", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-longcat-2-5" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-mimo-v2-6-distill-qwen-9b.json", "title": "LFM3-1.7B vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-mimo-v2-6-flash-rl.json", "title": "LFM3-1.7B vs MiMo-V2.6-Flash-RL", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-mimo-v2-6-flash-rl" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm-o-4-5.json", "title": "LFM3-1.7B vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm-v-4-7-1b.json", "title": "LFM3-1.7B vs MiniCPM-V 4.7 1B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm-v-4-7-1b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm-v-4-7-35b-a3b.json", "title": "LFM3-1.7B vs MiniCPM-V 4.7 35B-A3B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm-v-4-7-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm5-2b.json", "title": "LFM3-1.7B vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minimax-m2-5.json", "title": "LFM3-1.7B vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minimax-m2-7.json", "title": "LFM3-1.7B vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minimax-m3-1-flash.json", "title": "LFM3-1.7B vs MiniMax-M3.1-Flash", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minimax-m3-1-flash" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-mistral-large-4.json", "title": "LFM3-1.7B vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-muse-glimmer-30b.json", "title": "LFM3-1.7B vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nanbeige-4-2-3b.json", "title": "LFM3-1.7B vs Nanbeige4.2-3B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nanbeige-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nanbeige-4-3-33b.json", "title": "LFM3-1.7B vs Nanbeige4.3-33B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nanbeige-4-3-33b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-5-bolt-e4b-4gb.json", "title": "LFM3-1.7B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-5-bolt-e4b-4gb" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "LFM3-1.7B vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-30b-a3b.json", "title": "LFM3-1.7B vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-4b.json", "title": "LFM3-1.7B vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "LFM3-1.7B vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-super-120b-a12b.json", "title": "LFM3-1.7B vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-ultra-550b-a55b.json", "title": "LFM3-1.7B vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-north-mini-code-1-0.json", "title": "LFM3-1.7B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-occamy-1-0.json", "title": "LFM3-1.7B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-olmo-3-7b-think.json", "title": "LFM3-1.7B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-35b-a3b.json", "title": "LFM3-1.7B vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-397b.json", "title": "LFM3-1.7B vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-9b.json", "title": "LFM3-1.7B vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-otel-2-0-llm-31b-it.json", "title": "LFM3-1.7B vs OTel-2.0-LLM-31B-IT", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-otel-2-0-llm-31b-it" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen-agentworld-35b-a3b.json", "title": "LFM3-1.7B vs Qwen-AgentWorld-35B-A3B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen-agentworld-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-30b-a3b-instruct-2507.json", "title": "LFM3-1.7B vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-4b-instruct-2507.json", "title": "LFM3-1.7B vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-0-8b.json", "title": "LFM3-1.7B vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-122b-a10b.json", "title": "LFM3-1.7B vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-2b.json", "title": "LFM3-1.7B vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-397b-a17b.json", "title": "LFM3-1.7B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-4b.json", "title": "LFM3-1.7B vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-9b.json", "title": "LFM3-1.7B vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-6-27b.json", "title": "LFM3-1.7B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-6-35b-a3b.json", "title": "LFM3-1.7B vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-8-27b.json", "title": "LFM3-1.7B vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-8-flash-next.json", "title": "LFM3-1.7B vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "LFM3-1.7B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-coder-next.json", "title": "LFM3-1.7B vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "LFM3-1.7B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-2b-instruct.json", "title": "LFM3-1.7B vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-30b-a3b-instruct.json", "title": "LFM3-1.7B vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-32b-instruct.json", "title": "LFM3-1.7B vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-4b-instruct.json", "title": "LFM3-1.7B vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-8b-instruct.json", "title": "LFM3-1.7B vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwopus3-8-27b-flash-v2.json", "title": "LFM3-1.7B vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-recursive-flint.json", "title": "LFM3-1.7B vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ripple-65b-preview.json", "title": "LFM3-1.7B vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-sensenova-loop-9b-preview.json", "title": "LFM3-1.7B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-smollm3-3b.json", "title": "LFM3-1.7B vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-spark-x2-6-4b.json", "title": "LFM3-1.7B vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-step-3-7-flash.json", "title": "LFM3-1.7B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-swift-1-5-qwen3-8-27b.json", "title": "LFM3-1.7B vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "LFM3-1.7B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-thinkingcap-qwen3-8-27b.json", "title": "LFM3-1.7B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-unlimited-ocr-2.json", "title": "LFM3-1.7B vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-wevisone-vl-2b.json", "title": "LFM3-1.7B vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-wevisone-vl-4b.json", "title": "LFM3-1.7B vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-zaya1-8b.json", "title": "LFM3-1.7B vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-122b.json", "title": "LFM3-Audio-2B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-ornith-1-5-122b.json", "title": "LFM3-Omni-2B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-ornith-1-5-122b.json", "title": "LFM3-VL-2B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-122b.json", "title": "Ling-3.0-tiny vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-122b.json", "title": "Ling-3.1-flash-1019 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ornith-1-5-122b.json", "title": "LongCat-2.5 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-ornith-1-5-122b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-ornith-1-5-122b.json", "title": "MiMo-V2.6-Flash-RL vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-ornith-1-5-122b.json", "title": "MiniCPM-o 4.5 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-ornith-1-5-122b.json", "title": "MiniCPM-V 4.7 1B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-ornith-1-5-122b.json", "title": "MiniCPM-V 4.7 35B-A3B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-ornith-1-5-122b.json", "title": "MiniCPM5-2B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-ornith-1-5-122b.json", "title": "MiniMax-M2.5 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-ornith-1-5-122b.json", "title": "MiniMax-M2.7 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-ornith-1-5-122b.json", "title": "MiniMax-M3.1-Flash vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-ornith-1-5-122b.json", "title": "Mistral Large 4 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-ornith-1-5-122b.json", "title": "Muse Glimmer 30B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-ornith-1-5-122b.json", "title": "Nanbeige4.2-3B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-ornith-1-5-122b.json", "title": "Nanbeige4.3-33B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-ornith-1-5-122b.json", "title": "NVIDIA Nemotron 3.5 Bolt E4B 4GB vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-ornith-1-5-122b.json", "title": "Nemotron 3.5 Lightning 30B A3B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-ornith-1-5-122b.json", "title": "Nemotron 3 Nano 30B A3B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-ornith-1-5-122b.json", "title": "Nemotron 3 Nano 4B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-ornith-1-5-122b.json", "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-ornith-1-5-122b.json", "title": "Nemotron 3 Super 120B A12B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-ornith-1-5-122b.json", "title": "Nemotron 3 Ultra 550B A55B vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ornith-1-5-122b.json", "title": "North Mini Code 1.0 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-122b.json", "title": "occamy-1.0 vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-ornith-1-5-122b.json", "title": "Olmo 3 7B Think vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ornith-1-5-35b-a3b.json", "title": "Ornith-1.5-122B vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ornith-1-5-397b.json", "title": "Ornith-1.5-122B vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ornith-1-5-9b.json", "title": "Ornith-1.5-122B vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-otel-2-0-llm-31b-it.json", "title": "Ornith-1.5-122B vs OTel-2.0-LLM-31B-IT", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-otel-2-0-llm-31b-it" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen-agentworld-35b-a3b.json", "title": "Ornith-1.5-122B vs Qwen-AgentWorld-35B-A3B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen-agentworld-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Ornith-1.5-122B vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-4b-instruct-2507.json", "title": "Ornith-1.5-122B vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-0-8b.json", "title": "Ornith-1.5-122B vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-122b-a10b.json", "title": "Ornith-1.5-122B vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-2b.json", "title": "Ornith-1.5-122B vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-397b-a17b.json", "title": "Ornith-1.5-122B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-4b.json", "title": "Ornith-1.5-122B vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-9b.json", "title": "Ornith-1.5-122B vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-6-27b.json", "title": "Ornith-1.5-122B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-6-35b-a3b.json", "title": "Ornith-1.5-122B vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-8-27b.json", "title": "Ornith-1.5-122B vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-8-flash-next.json", "title": "Ornith-1.5-122B vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Ornith-1.5-122B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-coder-next.json", "title": "Ornith-1.5-122B vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Ornith-1.5-122B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-2b-instruct.json", "title": "Ornith-1.5-122B vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Ornith-1.5-122B vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-32b-instruct.json", "title": "Ornith-1.5-122B vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-4b-instruct.json", "title": "Ornith-1.5-122B vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-8b-instruct.json", "title": "Ornith-1.5-122B vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwopus3-8-27b-flash-v2.json", "title": "Ornith-1.5-122B vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-recursive-flint.json", "title": "Ornith-1.5-122B vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ripple-65b-preview.json", "title": "Ornith-1.5-122B vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-sensenova-loop-9b-preview.json", "title": "Ornith-1.5-122B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-smollm3-3b.json", "title": "Ornith-1.5-122B vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-spark-x2-6-4b.json", "title": "Ornith-1.5-122B vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-step-3-7-flash.json", "title": "Ornith-1.5-122B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-swift-1-5-qwen3-8-27b.json", "title": "Ornith-1.5-122B vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Ornith-1.5-122B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-thinkingcap-qwen3-8-27b.json", "title": "Ornith-1.5-122B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-unlimited-ocr-2.json", "title": "Ornith-1.5-122B vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-wevisone-vl-2b.json", "title": "Ornith-1.5-122B vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-wevisone-vl-4b.json", "title": "Ornith-1.5-122B vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-zaya1-8b.json", "title": "Ornith-1.5-122B vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-zaya1-8b" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 10, "edge": "lfm3-1-7b", "key": "reach", "lfm3-1-7b": 85, "name": "Reach", "ornith-1-5-122b": 75, "weight": 25 }, { "by": 10, "edge": "ornith-1-5-122b", "key": "risk", "lfm3-1-7b": 40, "name": "Risk", "ornith-1-5-122b": 50, "weight": 20 }, { "by": 15, "edge": "lfm3-1-7b", "key": "interface", "lfm3-1-7b": 100, "name": "Agent interface", "ornith-1-5-122b": 85, "weight": 10 }, { "by": 31, "edge": "lfm3-1-7b", "key": "upkeep", "lfm3-1-7b": 67, "name": "Documentation and upkeep", "ornith-1-5-122b": 36, "weight": 10 } ], "summary": "LFM3-1.7B and Ornith-1.5-122B score within a point of each other on agent readiness, 61 (C) and 61 (C). Ornith-1.5-122B leads on risk. Both do open-weight models you run yourself.", "tasks": null, "tutorials": [], "verdicts": { "lfm3-1-7b": "A 1.73B model that fits an 8 GB machine with room to spare, with a documented tool-call format, deferred tools, a thinking switch and a 256K context. It runs today in llama.cpp, Ollama and LM Studio only, loads in Transformers through repository code, and has no safety results, security contact or data sources.", "ornith-1-5-122b": "The largest Ornith that fits a 128 GB machine, a coding and terminal-agent cousin on Qwen3.5-122B-A10B's architecture with XML tool calls and 262,144 tokens of context. Its 4-bit builds need 84 to 93 GB. The main risk is an absent publisher, with no licence file, safety results or replies, and a card that misstates the hardware." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-122b", "json": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-122b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-122b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-122b.min.md" }, "markdown": "LFM3-1.7B and Ornith-1.5-122B score within a point of each other on agent readiness, 61 (C) and 61 (C). Ornith-1.5-122B leads on risk. Both do open-weight models you run yourself.\n\n- LFM3-1.7B: grade C, 61/100, rank #69 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/lfm3-1-7b.md · JSON https://www.anchorterminal.com/api/v1/tools/lfm3-1-7b.json\n- Ornith-1.5-122B: grade C, 61/100, rank #81 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/ornith-1-5-122b.md · JSON https://www.anchorterminal.com/api/v1/tools/ornith-1-5-122b.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### LFM3-1.7B (C)\n\nGood for: Agents on a laptop, phone or small server that need tool calling and a long context from a model under 2 GB at 4 bits\n\nAhead on:\n- Reach, 85 against 75\n- Agent interface, 100 against 85\n- Documentation and upkeep, 67 against 36\n\nWatch for: vLLM and SGLang have no released support, though the card lists both\n\n### Ornith-1.5-122B (C)\n\nGood for: Local coding and terminal agents on a 128 GB unified-memory machine or a 96 GB GPU setup, where a clear licence file and an answering publisher aren't required\n\nAhead on:\n- Risk, 50 against 40\n\nWatch for: No LICENSE file though the card links one, and no notice for the Apache 2.0 Qwen3.5 and Gemma 4 work it builds on\n\n\n## Why the edge\n\n### Documentation and upkeep: LFM3-1.7B +31\n\n- LFM3-1.7B (67): Model card 17, Intended use (local agents, tool calling, structured outputs, fine-tuning), a limitation (not recommended for agentic coding or complex multi-step reasoning), architecture (24 layers: 13 gated short convolutions, 5 sliding-window and 6 global attention), parameters (1.73B), context (256K) and 16 languages. Training data 5, A general description: 22T tokens of pre-training in two stages with the kinds of data added since LFM2, 1.75T tokens of supervised fine-tuning, then mixed reinforcement learning, distillation from six specialist teachers and agentic reinforcement learning. Last change 20, the last commit, on 9 November 2026, added the OpenVINO checkpoint to the card's inference table, a day before this check. Responsiveness 10, Of the 22 discussions that aren't pull requests (27 October to 8 November 2026), 7 have a reply from a LiquidAI member, which is some. Version policy 5, LFM3 came out in new repositories and the LFM2.5 models stay in theirs. File health 10, Config, template and card agree on the lfm3 architecture, the 262,144-token context and the thinking switch. 17 + 5 + 20 + 10 + 5 + 10 = 67.\n- Ornith-1.5-122B (36): Model card 11, it covers intended use, architecture, parameters and context but not limitations, languages or a knowledge cut-off. Training data 5, a description of the method with no data or cut-off. Last change 20, a folder upload to the MLX builds on 24 October 2026, 17 days ago. Responsiveness 0, Ornith answered none of the 5 questions and reports. Version policy 0, the MLX builds were uploaded a second time four days after the first with no note. File health 0, the card links a missing LICENSE, states hardware its own files don't fit and names a variant that doesn't exist, and the two chat templates differ. 11 + 5 + 20 + 0 + 0 + 0 = 36.\n\n### Agent interface: LFM3-1.7B +15\n\n- LFM3-1.7B (100): Chat template 20, chat_template.jinja in the repository (12,129 characters), with roles, tools, deferred tools, tool results and the thinking switch. Tool-calling format 25, the card and Liquid's tool-use page document tools passed through `tools=` in apply_chat_template, calls returned as XML and results sent back as tool messages. Trained tool calling 20, the template loops over every entry in an assistant turn's tool_calls, so several calls fit in one turn, and the card says the model was trained on tool calls and agentic traces and with reinforcement learning inside agent harnesses. Structured output 15, Liquid's API guide documents `response_format` with a JSON Schema, with lfm3-1.7b as the model in its examples, and says the schema is checked before generation starts. Reasoning control 10, the card documents `enable_thinking=False` in the chat template to turn reasoning off per request, with reasoning on by default inside think tags, and `preserve_thinking` for earlier turns. Context 10, 256K tokens per the card, which says the mid-training stage extended the context window to 256K, and max_position_embeddings 262144 in config.json. 20 + 25 + 20 + 15 + 10 + 10 = 100.\n- Ornith-1.5-122B (85): Chat template 20, a Jinja file in the repository. Tool-calling format 25, the card shows how tools go in and how calls come back and names the parser for vLLM and SGLang. Trained tool calling 20, Ornith trains it on agent tasks and the template renders several calls in one turn. Structured output 0, not documented or claimed. Reasoning control 10, Ornith's template reads enable_thinking per request and the card says the reasoning comes back in reasoning_content, though the card doesn't name the switch. Context 10, 262,144 tokens native.\n\n### Reach: LFM3-1.7B +10\n\n- LFM3-1.7B (85): Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB, and 1.10 GB × 1.2 = 1.3 GB, which fits 8 GB, well inside the 16 GB line. Runtimes 15, Released llama.cpp has the lfm3 architecture (src/models/lfm3.cpp at b12242), Ollama's library has an lfm3 entry, and LM Studio's catalogue runs the architecture (its liquid/lfm3-vl-2b entry; lmstudio-community publishes a GGUF of this model). Builds 15, Liquid's GGUF repository holds Q4_0, Q4_K_M, Q8_0, F16 and BF16 files, and Liquid publishes 4-bit and 8-bit MLX builds and an ONNX repository, all in the LiquidAI organisation. Terms 10, the LFM Open License v1.0, a custom licence that lets anyone use it commercially for free below a threshold of $10M annual revenue. Download 10, the Hub API reports gated false for the model and its GGUF, MLX and ONNX repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, Liquid's own API lists lfm3-1.7b among its models, so the publisher hosts it. 30 + 15 + 15 + 10 + 10 + 5 = 85.\n- Ornith-1.5-122B (75): Memory 10, since Ornith's own MLX 4-bit build is 69.7 GB and needs about 83.6 GB with the fifth added, over 64 GB and inside the reference machine's 107.4 GB, as do its Q4_K_M GGUF, its NVFP4 build and Ollama's build. Runtimes 25, the most the line gives, from vLLM 0.33.0, SGLang 0.5.23, Transformers 5.22.2, llama.cpp's qwen35moe architecture, Ollama's library and LM Studio's catalogue for the qwen35moe architecture. Builds 15, Ornith publishes FP8, NVFP4, GGUF and MLX at several precisions. Terms 15, MIT as named in the card's metadata, with nothing added, read by its terms though the repository has no licence file. Download 10, nothing is gated. Hosted 0, Ornith runs no API and no inference provider serves it. 10 + 25 + 15 + 15 + 10 + 0 = 75.\n\n### Risk: Ornith-1.5-122B +10\n\n- LFM3-1.7B (40): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, files in the LiquidAI organisation, which Liquid's docs page for the model and its blog post link to (10). Safety evaluation 0, no safety results on the card or in Liquid's blog post for the LFM3 family, neither of which mentions safety testing. Agent guidance 0, Nothing on prompt injection, an instruction hierarchy, what refusals cover or safeguards to add. Licence risk 10, 15 less 5 for the $10M annual revenue threshold on commercial use. Security programme 0, no way to report a flaw found. 15 + 15 + 0 + 0 + 10 + 0 = 40.\n- Ornith-1.5-122B (50): File safety 25, safetensors and GGUF only and no Python in any of Ornith's repositories for this size, so the card's --trust-remote-code flag loads nothing from the repository. Provenance 15, the files come from the ornith-ai organisation Ornith's blog links to, with a SHA-256 for every weight file. Safety evaluation 0 and agent guidance 0, nothing published on either. Licence risk 10, MIT carries no policy, threshold or changeable terms, but the card's licence link is broken. Security programme 0, no security.txt, disclosure policy or security contact.\n\n## Score by category\n\n| Category | Weight | LFM3-1.7B | Ornith-1.5-122B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 85 | 75 | LFM3-1.7B +10 |\n| Risk | 20% (20 this run) | 40 | 50 | Ornith-1.5-122B +10 |\n| Agent interface | 10% (10 this run) | 100 | 85 | LFM3-1.7B +15 |\n| Documentation and upkeep | 10% (10 this run) | 67 | 36 | LFM3-1.7B +31 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | LFM3-1.7B | Ornith-1.5-122B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Liquid AI | Ornith |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | | |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | LFM Open License v1.0 (free commercial use below $10M annual revenue) | MIT |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-11-09 | 2026-10-24 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n\n## Verdicts\n\n**LFM3-1.7B.** A 1.73B model that fits an 8 GB machine with room to spare, with a documented tool-call format, deferred tools, a thinking switch and a 256K context. It runs today in llama.cpp, Ollama and LM Studio only, loads in Transformers through repository code, and has no safety results, security contact or data sources.\n\n**Ornith-1.5-122B.** The largest Ornith that fits a 128 GB machine, a coding and terminal-agent cousin on Qwen3.5-122B-A10B's architecture with XML tool calls and 262,144 tokens of context. Its 4-bit builds need 84 to 93 GB. The main risk is an absent publisher, with no licence file, safety results or replies, and a card that misstates the hardware.\n\n## Before you call either\n\n### LFM3-1.7B\n\n1. Start it with `llama-server -hf LiquidAI/LFM3-1.7B-GGUF:Q4_K_M --jinja` or `ollama run lfm3`\n2. Use temperature 0.1, top_k 50 and repetition penalty 1.1 for chat, tools and agents, per the card\n3. Pass `enable_thinking=False` for direct answers, and expect it to reason anyway on hard tasks\n4. For a large tool catalogue mark tools `defer_loading` and give it a search tool\n5. Don't plan on vLLM or SGLang until a release carries LFM3\n6. Liquid doesn't recommend it for agentic coding or complex multi-step reasoning\n\n### Ornith-1.5-122B\n\n1. Start it with `ollama run ornith-1.5:122b-q4_K_M`, or `llama-server -hf ornith-ai/Ornith-1.5-122B-GGUF:Q4_K_M --jinja -c 262144`\n2. Budget about 92 GB for the Q4_K_M GGUF with a working context, and less context if the machine has under 100 GB for the model\n3. In vLLM pass `--enable-auto-tool-choice --tool-call-parser qwen3_xml --reasoning-parser qwen3`, and in SGLang `--tool-call-parser qwen3_coder --reasoning-parser qwen3`, so tool calls and reasoning come back parsed\n4. Thinking is on by default. Send `chat_template_kwargs` with `enable_thinking` false for short tasks, a switch the card doesn't mention\n5. Pin which template your runtime loads, since chat_template.jinja keeps earlier reasoning and the tokenizer_config.json template drops it\n6. Use temperature 0.6, top_p 0.95, top_k 20 for coding and temperature 1.0 for general tasks, as the card recommends\n7. Add mmproj-Ornith-1.5-122B-BF16.gguf (0.9 GB) for image input in llama.cpp, and validate JSON output yourself, since structured output isn't documented\n\n## Questions\n\n### Which is better for AI agents, LFM3-1.7B or Ornith-1.5-122B?\n\nLFM3-1.7B and Ornith-1.5-122B score within a point of each other on agent readiness, 61 (C) and 61 (C). Ornith-1.5-122B leads on risk.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-122b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-122b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"lfm3-1-7b\", \"b\": \"ornith-1-5-122b\"}`. From a terminal: `anchor compare lfm3-1-7b ornith-1-5-122b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/lfm3-1-7b.json and https://www.anchorterminal.com/api/v1/tools/ornith-1-5-122b.json\n\n## Other comparisons with LFM3-1.7B or Ornith-1.5-122B\n\n- [Agents-A1-4B vs LFM3-1.7B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-lfm3-1-7b.md)\n- [Agents-A1-4B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-ornith-1-5-122b.md)\n- [Apertus v1.5 8B vs LFM3-1.7B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lfm3-1-7b.md)\n- [Apertus v1.5 8B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-ornith-1-5-122b.md)\n- [Apodex-1.1-mini vs LFM3-1.7B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lfm3-1-7b.md)\n- [Apodex-1.1-mini vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-ornith-1-5-122b.md)\n- [Arete-27B vs LFM3-1.7B](https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-1-7b.md)\n- [Arete-27B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/arete-27b-vs-ornith-1-5-122b.md)\n- [BigBang-v1 vs LFM3-1.7B](https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-1-7b.md)\n- [BigBang-v1 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/bigbang-v1-vs-ornith-1-5-122b.md)\n- [Carbon-X vs LFM3-1.7B](https://www.anchorterminal.com/compare/carbon-x-vs-lfm3-1-7b.md)\n- [Carbon-X vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/carbon-x-vs-ornith-1-5-122b.md)\n- [Cola2 vs LFM3-1.7B](https://www.anchorterminal.com/compare/cola2-vs-lfm3-1-7b.md)\n- [Cola2 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/cola2-vs-ornith-1-5-122b.md)\n- [Cosmos-Reason2-2B vs LFM3-1.7B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lfm3-1-7b.md)\n- [Cosmos-Reason2-2B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-ornith-1-5-122b.md)\n- [Darwin-36B-Opus vs LFM3-1.7B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-1-7b.md)\n- [Darwin-36B-Opus vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-ornith-1-5-122b.md)\n- [DeepSeek-V3.2 vs LFM3-1.7B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-lfm3-1-7b.md)\n- [DeepSeek-V3.2 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-122b.md)\n- [DeepSeek V4.1 Flash vs LFM3-1.7B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-lfm3-1-7b.md)\n- [DeepSeek V4.1 Flash vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-ornith-1-5-122b.md)\n- [DeepSeek-V4-Flash-0731 vs LFM3-1.7B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-lfm3-1-7b.md)\n- [DeepSeek-V4-Flash-0731 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-ornith-1-5-122b.md)\n- [Devstral Small 2 vs LFM3-1.7B](https://www.anchorterminal.com/compare/devstral-small-2-vs-lfm3-1-7b.md)\n- [Devstral Small 2 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/devstral-small-2-vs-ornith-1-5-122b.md)\n- [DiffusionGemma 26B A4B IT vs LFM3-1.7B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-lfm3-1-7b.md)\n- [DiffusionGemma 26B A4B IT vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-ornith-1-5-122b.md)\n- [EXAONE 4.5 33B vs LFM3-1.7B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-1-7b.md)\n- [EXAONE 4.5 33B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-ornith-1-5-122b.md)\n- [Gemma 4 12B IT vs LFM3-1.7B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-lfm3-1-7b.md)\n- [Gemma 4 12B IT vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-ornith-1-5-122b.md)\n- [Gemma 4 26B A4B IT vs LFM3-1.7B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-lfm3-1-7b.md)\n- [Gemma 4 26B A4B IT vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-ornith-1-5-122b.md)\n- [Gemma 4 31B IT vs LFM3-1.7B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-lfm3-1-7b.md)\n- [Gemma 4 31B IT vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-ornith-1-5-122b.md)\n- [Gemma 4 E2B IT vs LFM3-1.7B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-lfm3-1-7b.md)\n- [Gemma 4 E2B IT vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-ornith-1-5-122b.md)\n- [Gemma 4 E4B IT vs LFM3-1.7B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-lfm3-1-7b.md)\n- [Gemma 4 E4B IT vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-ornith-1-5-122b.md)\n- [GLM-4.5-Air vs LFM3-1.7B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-lfm3-1-7b.md)\n- [GLM-4.5-Air vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-ornith-1-5-122b.md)\n- [GLM-4.7-Flash vs LFM3-1.7B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-lfm3-1-7b.md)\n- [GLM-4.7-Flash vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-ornith-1-5-122b.md)\n- [GLM-5.3-Flash vs LFM3-1.7B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-1-7b.md)\n- [GLM-5.3-Flash vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-ornith-1-5-122b.md)\n- [GLM-5.3 vs LFM3-1.7B](https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-1-7b.md)\n- [GLM-5.3 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-122b.md)\n- [gpt-oss-120b vs LFM3-1.7B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-1-7b.md)\n- [gpt-oss-120b vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-ornith-1-5-122b.md)\n- [gpt-oss-20b vs LFM3-1.7B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-lfm3-1-7b.md)\n- [gpt-oss-20b vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-ornith-1-5-122b.md)\n- [Granite 4.2 30B vs LFM3-1.7B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-lfm3-1-7b.md)\n- [Granite 4.2 30B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ornith-1-5-122b.md)\n- [Granite 4.2 3B vs LFM3-1.7B](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-lfm3-1-7b.md)\n- [Granite 4.2 3B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-ornith-1-5-122b.md)\n- [Granite 4.2 8B vs LFM3-1.7B](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-1-7b.md)\n- [Granite 4.2 8B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-ornith-1-5-122b.md)\n- [Hy-Memory-30B-A3B vs LFM3-1.7B](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-lfm3-1-7b.md)\n- [Hy-Memory-30B-A3B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-ornith-1-5-122b.md)\n- [Hy3 vs LFM3-1.7B](https://www.anchorterminal.com/compare/hy3-vs-lfm3-1-7b.md)\n- [Hy3 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-122b.md)\n- [Inkling-Small vs LFM3-1.7B](https://www.anchorterminal.com/compare/inkling-small-vs-lfm3-1-7b.md)\n- [Inkling-Small vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-122b.md)\n- [Inkling vs LFM3-1.7B](https://www.anchorterminal.com/compare/inkling-vs-lfm3-1-7b.md)\n- [Inkling vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/inkling-vs-ornith-1-5-122b.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs LFM3-1.7B](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-lfm3-1-7b.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-ornith-1-5-122b.md)\n- [Kimi K3.1 Pro vs LFM3-1.7B](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-lfm3-1-7b.md)\n- [Kimi K3.1 Pro vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-ornith-1-5-122b.md)\n- [Kimi K3 vs LFM3-1.7B](https://www.anchorterminal.com/compare/kimi-k3-vs-lfm3-1-7b.md)\n- [Kimi K3 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-122b.md)\n- [Kolibri-1 vs LFM3-1.7B](https://www.anchorterminal.com/compare/kolibri-1-vs-lfm3-1-7b.md)\n- [Kolibri-1 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/kolibri-1-vs-ornith-1-5-122b.md)\n- [Kronos vs LFM3-1.7B](https://www.anchorterminal.com/compare/kronos-vs-lfm3-1-7b.md)\n- [Kronos vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/kronos-vs-ornith-1-5-122b.md)\n- [Laguna M.1 vs LFM3-1.7B](https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-1-7b.md)\n- [Laguna M.1 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/laguna-m-1-vs-ornith-1-5-122b.md)\n- [Laguna S 2.1 vs LFM3-1.7B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm3-1-7b.md)\n- [Laguna S 2.1 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-122b.md)\n- [Laguna XS 2.1 vs LFM3-1.7B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-1-7b.md)\n- [Laguna XS 2.1 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ornith-1-5-122b.md)\n- [LBS-27B vs LFM3-1.7B](https://www.anchorterminal.com/compare/lbs-27b-vs-lfm3-1-7b.md)\n- [LBS-27B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/lbs-27b-vs-ornith-1-5-122b.md)\n- [LFM2.5-2.6B vs LFM3-1.7B](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-lfm3-1-7b.md)\n- [LFM2.5-2.6B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-ornith-1-5-122b.md)\n- [LFM3-1.7B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-lfm3-audio-2b.md)\n- [LFM3-1.7B vs LFM3-Omni-2B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-lfm3-omni-2b.md)\n- [LFM3-1.7B vs LFM3-VL-2B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-lfm3-vl-2b.md)\n- [LFM3-1.7B vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ling-3-0-tiny.md)\n- [LFM3-1.7B vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ling-3-1-flash-1019.md)\n- [LFM3-1.7B vs LongCat-2.5](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-longcat-2-5.md)\n- [LFM3-1.7B vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-mimo-v2-6-distill-qwen-9b.md)\n- [LFM3-1.7B vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-mimo-v2-6-flash-rl.md)\n- [LFM3-1.7B vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm-o-4-5.md)\n- [LFM3-1.7B vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm-v-4-7-1b.md)\n- [LFM3-1.7B vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm-v-4-7-35b-a3b.md)\n- [LFM3-1.7B vs MiniCPM5-2B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minicpm5-2b.md)\n- [LFM3-1.7B vs MiniMax-M2.5](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minimax-m2-5.md)\n- [LFM3-1.7B vs MiniMax-M2.7](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minimax-m2-7.md)\n- [LFM3-1.7B vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-minimax-m3-1-flash.md)\n- [LFM3-1.7B vs Mistral Large 4](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-mistral-large-4.md)\n- [LFM3-1.7B vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-muse-glimmer-30b.md)\n- [LFM3-1.7B vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nanbeige-4-2-3b.md)\n- [LFM3-1.7B vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nanbeige-4-3-33b.md)\n- [LFM3-1.7B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [LFM3-1.7B vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [LFM3-1.7B vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-30b-a3b.md)\n- [LFM3-1.7B vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-4b.md)\n- [LFM3-1.7B vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [LFM3-1.7B vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-super-120b-a12b.md)\n- [LFM3-1.7B vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-nemotron-3-ultra-550b-a55b.md)\n- [LFM3-1.7B vs North Mini Code 1.0](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-north-mini-code-1-0.md)\n- [LFM3-1.7B vs occamy-1.0](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-occamy-1-0.md)\n- [LFM3-1.7B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-olmo-3-7b-think.md)\n- [LFM3-1.7B vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-35b-a3b.md)\n- [LFM3-1.7B vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-397b.md)\n- [LFM3-1.7B vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-9b.md)\n- [LFM3-1.7B vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-otel-2-0-llm-31b-it.md)\n- [LFM3-1.7B vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen-agentworld-35b-a3b.md)\n- [LFM3-1.7B vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-30b-a3b-instruct-2507.md)\n- [LFM3-1.7B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-4b-instruct-2507.md)\n- [LFM3-1.7B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-0-8b.md)\n- [LFM3-1.7B vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-122b-a10b.md)\n- [LFM3-1.7B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-2b.md)\n- [LFM3-1.7B vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-397b-a17b.md)\n- [LFM3-1.7B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-4b.md)\n- [LFM3-1.7B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-5-9b.md)\n- [LFM3-1.7B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-6-27b.md)\n- [LFM3-1.7B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-6-35b-a3b.md)\n- [LFM3-1.7B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-8-27b.md)\n- [LFM3-1.7B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-8-flash-next.md)\n- [LFM3-1.7B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [LFM3-1.7B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-coder-next.md)\n- [LFM3-1.7B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-omni-30b-a3b-instruct.md)\n- [LFM3-1.7B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-2b-instruct.md)\n- [LFM3-1.7B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-30b-a3b-instruct.md)\n- [LFM3-1.7B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-32b-instruct.md)\n- [LFM3-1.7B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-4b-instruct.md)\n- [LFM3-1.7B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwen3-vl-8b-instruct.md)\n- [LFM3-1.7B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-qwopus3-8-27b-flash-v2.md)\n- [LFM3-1.7B vs Recursive Flint](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-recursive-flint.md)\n- [LFM3-1.7B vs Ripple-65B Preview](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ripple-65b-preview.md)\n- [LFM3-1.7B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-sensenova-loop-9b-preview.md)\n- [LFM3-1.7B vs SmolLM3-3B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-smollm3-3b.md)\n- [LFM3-1.7B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-spark-x2-6-4b.md)\n- [LFM3-1.7B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-step-3-7-flash.md)\n- [LFM3-1.7B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-swift-1-5-qwen3-8-27b.md)\n- [LFM3-1.7B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [LFM3-1.7B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-thinkingcap-qwen3-8-27b.md)\n- [LFM3-1.7B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-unlimited-ocr-2.md)\n- [LFM3-1.7B vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-wevisone-vl-2b.md)\n- [LFM3-1.7B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-wevisone-vl-4b.md)\n- [LFM3-1.7B vs ZAYA1-8B](https://www.anchorterminal.com/compare/lfm3-1-7b-vs-zaya1-8b.md)\n- [LFM3-Audio-2B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-122b.md)\n- [LFM3-Omni-2B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/lfm3-omni-2b-vs-ornith-1-5-122b.md)\n- [LFM3-VL-2B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-ornith-1-5-122b.md)\n- [Ling-3.0-tiny vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-ornith-1-5-122b.md)\n- [Ling-3.1-flash-1019 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-ornith-1-5-122b.md)\n- [LongCat-2.5 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/longcat-2-5-vs-ornith-1-5-122b.md)\n- [MiMo-V2.6 Distill Qwen 9B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-ornith-1-5-122b.md)\n- [MiMo-V2.6-Flash-RL vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/mimo-v2-6-flash-rl-vs-ornith-1-5-122b.md)\n- [MiniCPM-o 4.5 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-ornith-1-5-122b.md)\n- [MiniCPM-V 4.7 1B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/minicpm-v-4-7-1b-vs-ornith-1-5-122b.md)\n- [MiniCPM-V 4.7 35B-A3B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/minicpm-v-4-7-35b-a3b-vs-ornith-1-5-122b.md)\n- [MiniCPM5-2B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/minicpm5-2b-vs-ornith-1-5-122b.md)\n- [MiniMax-M2.5 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/minimax-m2-5-vs-ornith-1-5-122b.md)\n- [MiniMax-M2.7 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/minimax-m2-7-vs-ornith-1-5-122b.md)\n- [MiniMax-M3.1-Flash vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-ornith-1-5-122b.md)\n- [Mistral Large 4 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/mistral-large-4-vs-ornith-1-5-122b.md)\n- [Muse Glimmer 30B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-ornith-1-5-122b.md)\n- [Nanbeige4.2-3B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-ornith-1-5-122b.md)\n- [Nanbeige4.3-33B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-ornith-1-5-122b.md)\n- [NVIDIA Nemotron 3.5 Bolt E4B 4GB vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-ornith-1-5-122b.md)\n- [Nemotron 3.5 Lightning 30B A3B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-ornith-1-5-122b.md)\n- [Nemotron 3 Nano 30B A3B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-ornith-1-5-122b.md)\n- [Nemotron 3 Nano 4B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-ornith-1-5-122b.md)\n- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-ornith-1-5-122b.md)\n- [Nemotron 3 Super 120B A12B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-ornith-1-5-122b.md)\n- [Nemotron 3 Ultra 550B A55B vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-ornith-1-5-122b.md)\n- [North Mini Code 1.0 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-ornith-1-5-122b.md)\n- [occamy-1.0 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-122b.md)\n- [Olmo 3 7B Think vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-ornith-1-5-122b.md)\n- [Ornith-1.5-122B vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ornith-1-5-35b-a3b.md)\n- [Ornith-1.5-122B vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ornith-1-5-397b.md)\n- [Ornith-1.5-122B vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ornith-1-5-9b.md)\n- [Ornith-1.5-122B vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-otel-2-0-llm-31b-it.md)\n- [Ornith-1.5-122B vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen-agentworld-35b-a3b.md)\n- [Ornith-1.5-122B vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-30b-a3b-instruct-2507.md)\n- [Ornith-1.5-122B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-4b-instruct-2507.md)\n- [Ornith-1.5-122B vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-0-8b.md)\n- [Ornith-1.5-122B vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-122b-a10b.md)\n- [Ornith-1.5-122B vs Qwen3.5-2B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-2b.md)\n- [Ornith-1.5-122B vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-397b-a17b.md)\n- [Ornith-1.5-122B vs Qwen3.5-4B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-4b.md)\n- [Ornith-1.5-122B vs Qwen3.5-9B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-5-9b.md)\n- [Ornith-1.5-122B vs Qwen3.6-27B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-6-27b.md)\n- [Ornith-1.5-122B vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-6-35b-a3b.md)\n- [Ornith-1.5-122B vs Qwen3.8-27B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-8-27b.md)\n- [Ornith-1.5-122B vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-8-flash-next.md)\n- [Ornith-1.5-122B vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Ornith-1.5-122B vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-coder-next.md)\n- [Ornith-1.5-122B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Ornith-1.5-122B vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-2b-instruct.md)\n- [Ornith-1.5-122B vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-30b-a3b-instruct.md)\n- [Ornith-1.5-122B vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-32b-instruct.md)\n- [Ornith-1.5-122B vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-4b-instruct.md)\n- [Ornith-1.5-122B vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwen3-vl-8b-instruct.md)\n- [Ornith-1.5-122B vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-qwopus3-8-27b-flash-v2.md)\n- [Ornith-1.5-122B vs Recursive Flint](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-recursive-flint.md)\n- [Ornith-1.5-122B vs Ripple-65B Preview](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-ripple-65b-preview.md)\n- [Ornith-1.5-122B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-sensenova-loop-9b-preview.md)\n- [Ornith-1.5-122B vs SmolLM3-3B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-smollm3-3b.md)\n- [Ornith-1.5-122B vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-spark-x2-6-4b.md)\n- [Ornith-1.5-122B vs Step 3.7 Flash](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-step-3-7-flash.md)\n- [Ornith-1.5-122B vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-swift-1-5-qwen3-8-27b.md)\n- [Ornith-1.5-122B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Ornith-1.5-122B vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-thinkingcap-qwen3-8-27b.md)\n- [Ornith-1.5-122B vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-unlimited-ocr-2.md)\n- [Ornith-1.5-122B vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-wevisone-vl-2b.md)\n- [Ornith-1.5-122B vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-wevisone-vl-4b.md)\n- [Ornith-1.5-122B vs ZAYA1-8B](https://www.anchorterminal.com/compare/ornith-1-5-122b-vs-zaya1-8b.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-11", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "LFM3-1.7B vs Ornith-1.5-122B", "url": "" } ], "description": "LFM3-1.7B and Ornith-1.5-122B score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "LFM3-1.7B C 61", "Ornith-1.5-122B C 61", "scores" ], "h1": "LFM3-1.7B vs Ornith-1.5-122B", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/lfm3-1-7b-vs-ornith-1-5-122b", "published": "2026-10-01", "section": "tools", "title": "LFM3-1.7B vs Ornith-1.5-122B for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-10", "url": "https://www.anchorterminal.com/compare/lfm3-1-7b-vs-ornith-1-5-122b" }, "tokens": { "markdown": 9600, "slim": 780 }, "version": 1 }