{ "data": { "a": { "slug": "laguna-s-2-1", "name": "Laguna S 2.1", "vendor": "Poolside", "vendorUrl": "https://poolside.ai", "kind": "weights", "category": "open-weights", "summary": "Laguna S 2.1 is Poolside's open-weight Mixture-of-Experts model for agentic coding, 118B total and 8B active parameters, with switchable reasoning and a 1,048,576-token context, published on Hugging Face under OpenMDW-1.1.", "url": "https://www.anchorterminal.com/tools/laguna-s-2-1", "markdownUrl": "https://www.anchorterminal.com/tools/laguna-s-2-1.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/laguna-s-2-1.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/laguna-s-2-1.json", "repo": "https://huggingface.co/poolside/Laguna-S-2.1", "license": "OpenMDW-1.1", "transports": [], "packages": [ { "registry": "huggingface", "name": "poolside/Laguna-S-2.1" }, { "registry": "huggingface", "name": "poolside/Laguna-S-2.1-FP8" }, { "registry": "huggingface", "name": "poolside/Laguna-S-2.1-INT4" }, { "registry": "huggingface", "name": "poolside/Laguna-S-2.1-NVFP4" }, { "registry": "huggingface", "name": "poolside/Laguna-S-2.1-NVFP4-mlx" }, { "registry": "huggingface", "name": "poolside/Laguna-S-2.1-GGUF" }, { "registry": "ollama", "name": "laguna-s-2.1" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports gated false for the main repository and every build, although the card's metadata carries an unused gate description pointing to Poolside's privacy policy (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under OpenMDW-1.1. Running it yourself costs the hardware, 235.1 GB for the BF16 files, 96.0 GB for Poolside's Q4_K_M GGUF and 66 GB for Ollama's MLX NVFP4 build. Poolside's API, OpenRouter, Featherless AI, Vercel AI Gateway and Baseten host it (checked 2026-10-21).", "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 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-21" }, "docsUrl": "https://huggingface.co/poolside/Laguna-S-2.1", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "coding", "reasoning", "tool-calling", "long-context", "openmdw-1.1", "safetensors", "gguf", "fp8", "nvfp4", "self-hosted" ], "lastRelease": "2026-08-19", "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": 1197, "categoryRank": 32, "methodology": "0.6", "run": "2026-10-01", "scores": { "interface": 85, "reach": 75, "risk": 55, "upkeep": 41 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-21" }, "negative": 0, "verdict": "A strong coding and agent cousin for long sessions, with 8B active parameters and a 1M-token context. At 4-bit it needs a 96 to 128 GB machine, tight on a 128 GB one. The main risks are that nobody at Poolside answers its many reports, there are no safety results, and a build card misdescribes its file.", "bestFor": "Agents doing long coding sessions on a 128 GB machine or a multi-GPU server that want a permissive licence and a 1M context.", "strengths": [ "Released support in llama.cpp, Ollama, vLLM, SGLang, Transformers and mlx-lm", "Poolside's own FP8, INT4, NVFP4, MLX and GGUF builds, plus DFlash draft models", "1,048,576 tokens of context, trained at that length per Poolside's build cards", "Permissive OpenMDW-1.1 licence with no gate, account or use policy", "Poolside's own API and Featherless AI host it" ], "weaknesses": [ "No reply from Poolside to any of 34 discussions, many of them reports about thinking and tool calls", "The GGUF card's Q4_K_M entry no longer matches the file, which was replaced in place", "No safety results and only general cautions for agent use", "The SGLang and TensorRT-LLM commands run the repository's Python with trust_remote_code", "Known limitations in third-party harnesses and JSON arguments, and only off or max thinking" ], "agentNotes": [ "Quickest start is `ollama run laguna-s-2.1`, 96 GB for the default Q4_K_M, or the 66 GB nvfp4 tag on Apple Silicon", "On our reference machine try `llama-server -hf poolside/Laguna-S-2.1-GGUF:Q4_K_M --jinja -c 65536`, from a llama.cpp release with the laguna architecture (b11772 has it). The 96 GB file leaves little room for context in 107.4 GB", "With vLLM or SGLang use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1`, and with TensorRT-LLM `--tool_parser poolside_v1 --reasoning_parser laguna`", "Thinking is on by default in the template, pass `chat_template_kwargs` with `enable_thinking` false to turn it off, and keep `reasoning_content` from earlier turns", "The GGUFs ship set to 262,144 tokens. For 1M with llama.cpp add `--ctx-size 1048576 --rope-scaling yarn --rope-scale 128 --yarn-orig-ctx 8192`, which Poolside says can cost quality", "Sampling per the generation config is temperature 1.0 and top_k 20, and Poolside suggests temperature 0.7 and top_p 0.95 at 1M", "Expect occasional tool-schema slips in harnesses unlike Poolside's own, and validate JSON arguments, which Poolside lists as known limitations" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.3, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "interface": 85, "reach": 75, "risk": 55, "upkeep": 41 }, "provenanceScore": 71, "checked": { "categories": { "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "ollama run laguna-s-2.1\n# or, with vLLM on four GPUs:\nvllm serve poolside/Laguna-S-2.1 --tensor-parallel-size 4 --tool-call-parser poolside_v1 \\\n --reasoning-parser poolside_v1 --enable-auto-tool-choice --default-chat-template-kwargs '{\"enable_thinking\": true}'", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"laguna-s-2.1\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/laguna-s-2-1" }, "sameCompany": [ "laguna-m-1", "laguna-xs-2-1" ], "weights": { "trainedBy": "Poolside", "params": "117.6B total, 8B active", "context": 1048576, "goodFor": "Long-horizon agentic coding and terminal work with up to 1M tokens of context, on a 128 GB machine at 4-bit or a multi-GPU server.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "LM Studio", "Transformers" ], "builds": [ { "name": "Laguna-S-2.1-NVFP4-mlx", "url": "https://huggingface.co/poolside/Laguna-S-2.1-NVFP4-mlx", "who": "publisher", "precision": "nvfp4", "sizeGB": 71.9, "memoryGB": 96, "format": "mlx", "runsOn": [ "MLX" ] }, { "name": "ollama laguna-s-2.1:nvfp4", "url": "https://ollama.com/library/laguna-s-2.1:nvfp4", "who": "ollama", "precision": "nvfp4", "sizeGB": 66, "memoryGB": 96, "format": "mlx", "runsOn": [ "Ollama" ], "note": "Ollama's MLX build, for Apple Silicon. Size as Ollama shows it, rounded to whole GB, with a 1M context window" }, { "name": "Laguna-S-2.1-INT4", "url": "https://huggingface.co/poolside/Laguna-S-2.1-INT4", "who": "publisher", "precision": "int4 (w4a16)", "sizeGB": 99.7, "memoryGB": 128, "format": "safetensors" }, { "name": "Laguna-S-2.1-NVFP4", "url": "https://huggingface.co/poolside/Laguna-S-2.1-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 99.7, "memoryGB": 128, "format": "safetensors", "note": "For NVIDIA Blackwell GPUs and DGX Spark" }, { "name": "Laguna-S-2.1-GGUF Q4_K_M", "url": "https://huggingface.co/poolside/Laguna-S-2.1-GGUF", "who": "publisher", "precision": "q4_k_m", "sizeGB": 96, "memoryGB": 128, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "laguna-s-2.1-Q4_K_M.gguf, 96,031,829,760 bytes, replaced on 27 July 2026 with a mixed-precision build that keeps sensitive layers in BF16. The build card still lists it as 68 GB. The repository also holds Q8_0 (128.8 GB, 192 GB of memory), F16 (235.2 GB) and a 2.2 GB DFlash draft" }, { "name": "ollama laguna-s-2.1:latest", "url": "https://ollama.com/library/laguna-s-2.1:latest", "who": "ollama", "precision": "q4_k_m", "sizeGB": 96, "memoryGB": 128, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Size as Ollama's tags page shows it, rounded to whole GB. Its model blob (948255a146c0) isn't Poolside's GGUF file. The library also has q8_0 (128 GB), f16 (235 GB) and MLX tags" }, { "name": "Laguna-S-2.1-FP8", "url": "https://huggingface.co/poolside/Laguna-S-2.1-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 131.3, "memoryGB": 192, "format": "safetensors" }, { "name": "Laguna-S-2.1", "url": "https://huggingface.co/poolside/Laguna-S-2.1", "who": "publisher", "precision": "bf16", "sizeGB": 235.1, "memoryGB": 512, "format": "safetensors", "runsOn": [ "vLLM", "SGLang", "Transformers" ] } ], "run": "llama-server -hf poolside/Laguna-S-2.1-GGUF:Q4_K_M --jinja -c 65536 --port 8000", "runBuild": "Laguna-S-2.1-GGUF Q4_K_M", "checked": "2026-10-21", "minMemoryGB": 96 }, "family": { "lab": "Poolside", "family": "Laguna 2 (XS.2, XS 2.1, S 2.1)", "url": "https://www.anchorterminal.com/open-weights/#poolside", "others": [ { "name": "Laguna-XS-2.1", "url": "https://huggingface.co/poolside/Laguna-XS-2.1", "params": "33.44B (Hub safetensors count; the name gives only the size class XS)", "listing": "https://www.anchorterminal.com/tools/laguna-xs-2-1" }, { "name": "Laguna-S-2.1-base", "url": "https://huggingface.co/poolside/Laguna-S-2.1-base", "params": "not stated (no safetensors count on the Hub; the instruct model is 117.56B)" }, { "name": "Laguna-XS.2", "url": "https://huggingface.co/poolside/Laguna-XS.2", "params": "33.44B (Hub safetensors count; the name gives only the size class XS)" } ], "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "Poolside, Inc. (named in Poolside's Terms of Use)", "domain": "poolside.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "https://poolside.ai/legal/eula", "privacy": "https://poolside.ai/legal/privacy", "statusPage": "", "changelog": "https://docs.poolside.ai/release-notes/models", "securityTxt": "valid", "checked": "2026-10-21", "notes": [ "The Hugging Face organisation poolside is verified, and Poolside's release post links the repository.", "Nothing is hosted for this listing, so the OpenMDW-1.1 licence stands in for terms of service and no privacy policy is scored.", "Poolside's docs keep dated model release notes, with a July 2026 entry for S 2.1.", "security.txt is PGP-signed, names a security contact at poolside.ai and expires on 1 April 2028. The domain's registration date wasn't checked." ], "score": 71 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/laguna-s-2-1.json" }, "answer": "Laguna S 2.1 scores 61 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 52.3 (D), and leads in every scored category.", "b": { "slug": "swift-1-5-qwen3-8-flash-next", "name": "Swift 1.5 Qwen3.8-Flash-Next", "vendor": "UkisAI", "vendorUrl": "https://ukisai.com", "kind": "weights", "category": "open-weights", "summary": "Swift 1.5 Qwen3.8-Flash-Next is UkisAI's post-trained Qwen3.8-Flash-Next that aims to think in fewer tokens, a mixture-of-experts vision-language model of 180B parameters in its files with a 262,144-token context, published in BF16 with GGUF, INT4 and NVFP4 builds.", "url": "https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next", "markdownUrl": "https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/swift-1-5-qwen3-8-flash-next.json", "repo": "https://huggingface.co/ukisai/Swift1.5-Qwen3.8-Flash-Next", "license": "Swift Open License v1.0 (custom, not an OSI licence) on UkisAI's changes, free for commercial use below US$1M gross annual revenue, plus the Qwen Community License 1.0 on the base, which needs a separate licence from Qwen for a Model as a Service or AI Work Assistant business and the model name shown above 100M monthly users or US$20M monthly revenue", "transports": [], "packages": [ { "registry": "huggingface", "name": "ukisai/Swift1.5-Qwen3.8-Flash-Next" }, { "registry": "huggingface", "name": "ukisai/Swift-1.5-Qwen3.8-Flash-Next-GGUF" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports the repository as not gated, though the card's metadata says gated true (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download. Commercial use of UkisAI's contribution is free below US$1,000,000 gross annual revenue, affiliates included, and needs a Swift Enterprise License above it. The base's Qwen Community License 1.0 also applies, with a separate licence from Qwen for Model as a Service or AI Work Assistant businesses. UkisAI's card lists a free API for research at ukisai.com/api/flash-next/v1. Running it yourself costs the hardware, 360 GB in BF16 and 98.6 GB for the smallest 4-bit GGUF with its projector by the Hub's file lists (checked 2026-10-21).", "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 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-21" }, "docsUrl": "https://huggingface.co/ukisai/Swift1.5-Qwen3.8-Flash-Next", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "reasoning", "tool-calling", "fine-tune", "custom-licence", "safetensors", "gguf", "self-hosted" ], "lastRelease": "2026-09-24", "graded": true, "anchor": { "graded": true, "score": 52.3, "grade": "D", "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": 1197, "categoryRank": 70, "methodology": "0.6", "run": "2026-10-01", "scores": { "interface": 60, "reach": 60, "risk": 45, "upkeep": 40 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-21" }, "negative": 0, "verdict": "A large mixture-of-experts cousin, Qwen3.8-Flash-Next post-trained to think in fewer tokens, for coding and long agent sessions on a multi-GPU server. Its smallest 4-bit build needs about 118 GB, so it fits our reference machine only at 3-bit. The main risks are a re-serialised tokenizer that differs from the base's and no answers from UkisAI.", "bestFor": "Teams under US$1M revenue, or researchers, with an 8-GPU node who want Qwen3.8-Flash-Next with shorter thinking for coding and agent work.", "strengths": [ "Runs in released vLLM, SGLang, Transformers and llama.cpp as Qwen3.8-Flash-Next does, with the same template and 262,144-token context", "GGUF, INT4 and NVFP4 builds from UkisAI, including 3-bit GGUFs that fit about 102 GB", "Safetensors only, in the account UkisAI's site links to, with a checksum on every file", "Several tool calls a turn and post-training aimed at agent and coding work", "Ungated, with no account or terms to accept" ], "weaknesses": [ "Two licences to satisfy, UkisAI's US$1M revenue limit and Qwen's separate licence for model-as-a-service businesses", "The smallest 4-bit build needs about 118 GB, beyond a 128 GB unified-memory machine's GPU share", "tokenizer.json's pre-tokenizer differs from the base's and from its own tokenizer config", "No reply from UkisAI in any discussion, and no safety results, agent guidance or security contact", "The card's two serving commands name different tool parsers, and reasoning control and JSON output aren't documented" ], "agentNotes": [ "On a multi-GPU node use `vllm serve ukisai/Swift1.5-Qwen3.8-Flash-Next --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, the parser the base's recipes and the card's SGLang command use", "The card's vLLM command passes --trust-remote-code and the old repository name, neither is needed", "On our reference machine only UkisAI's GSQ-RCO IQ3_S GGUF (84.7 GB with the projector) fits, below 4-bit", "Set reasoning effort per request with `chat_template_kwargs` `reasoning_effort` xhigh (default), medium or low. UkisAI's own runs lose about 2.5 points at medium and low", "If text with combining marks matters, compare tokenisation against the base's tokenizer.json before trusting outputs", "Check both licences before commercial use, UkisAI's stops at US$1M gross annual revenue and Qwen's needs a separate licence for model-as-a-service businesses" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 1.8, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "D", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.3 } ], "editorialScores": { "interface": 60, "reach": 60, "risk": 45, "upkeep": 40 }, "provenanceScore": 13, "checked": { "categories": { "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "vllm serve ukisai/Swift1.5-Qwen3.8-Flash-Next --tensor-parallel-size 8 --max-model-len 262144 \\\n --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -d '{\"model\": \"ukisai/Swift1.5-Qwen3.8-Flash-Next\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello, Swift.\"}], \"chat_template_kwargs\": {\"reasoning_effort\": \"low\"}}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/swift-1-5-qwen3-8-flash-next" }, "sameCompany": [ "swift-1-5-qwen3-8-27b" ], "weights": { "trainedBy": "UkisAI, post-training Alibaba's Qwen3.8-Flash-Next", "builtOn": "Qwen/Qwen3.8-Flash-Next (fine-tune, Qwen Community License 1.0)", "params": "125B", "context": 262144, "goodFor": "A Qwen3.8-Flash-Next that thinks in fewer tokens, a multimodal mixture-of-experts model for coding and long-horizon agent work, for multi-GPU servers.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Swift-1.5-Qwen3.8-Flash-Next-GGUF IQ4_XS", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-Flash-Next-GGUF", "who": "publisher", "precision": "iq4_xs", "sizeGB": 98.6, "memoryGB": 128, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "Three IQ4_XS shards (97.68 GB) plus mmproj-Swift-1.5-Qwen3.8-Flash-Next-BF16.gguf (0.91 GB), summed from the Hub's file list. The smallest build of 4-bit or better, 118.3 GB with a fifth, above the reference machine's 107.4 GB" }, { "name": "Swift-1.5-Qwen3.8-Flash-Next-GSQ-RCO-GGUF IQ3_S", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-Flash-Next-GSQ-RCO-GGUF", "who": "publisher", "precision": "iq3_s", "sizeGB": 84.7, "memoryGB": 128, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "Below 4-bit, so not counted for Reach memory. Two IQ3_S shards (83.74 GB) plus the 0.91 GB projector, 101.6 GB with a fifth, inside the reference machine's 107.4 GB. The repository also has IQ3_XXS, IQ2_XS and Q2_0 files from 66.5 GB" }, { "name": "Swift-1.5-Qwen3.8-Flash-Next-GGUF Q4_K_M", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-Flash-Next-GGUF", "who": "publisher", "precision": "q4_k_m", "sizeGB": 120.5, "memoryGB": 192, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "Three Q4_K_M shards (119.60 GB) plus the 0.91 GB vision projector" }, { "name": "Swift-1.5-Qwen3.8-Flash-Next-W4A16-AWQ", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-Flash-Next-W4A16-AWQ", "who": "publisher", "precision": "int4", "sizeGB": 177.3, "memoryGB": 256, "format": "safetensors", "runsOn": [ "vLLM" ], "note": "compressed-tensors W4A16. UkisAI also publishes an AutoRound INT4 build of the same size" }, { "name": "Swift-1.5-Qwen3.8-Flash-Next-NVFP4", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-Flash-Next-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 186.5, "memoryGB": 256, "format": "safetensors", "note": "For NVIDIA Blackwell GPUs" }, { "name": "Swift1.5-Qwen3.8-Flash-Next", "url": "https://huggingface.co/ukisai/Swift1.5-Qwen3.8-Flash-Next", "who": "publisher", "precision": "bf16", "sizeGB": 360, "memoryGB": 512, "format": "safetensors" } ], "run": "vllm serve ukisai/Swift1.5-Qwen3.8-Flash-Next --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder", "runBuild": "Swift1.5-Qwen3.8-Flash-Next", "checked": "2026-10-21", "minMemoryGB": 128 }, "family": { "lab": "UkisAI (ukisai)", "family": "Swift 1", "url": "https://www.anchorterminal.com/open-weights/#ukisai", "others": [ { "name": "Swift-Qwen3.8-27b", "url": "https://huggingface.co/ukisai/Swift-Qwen3.8-27b", "params": "27B (27,781,427,952 by the Hub's safetensors count)" }, { "name": "Swift-1.5-Qwen3.8-27b", "url": "https://huggingface.co/ukisai/Swift-1.5-Qwen3.8-27b", "params": "27B (27,781,427,952 by the Hub's safetensors count)", "listing": "https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-27b" }, { "name": "Swift-1.5-Ornith-9B", "url": "https://huggingface.co/ukisai/Swift-1.5-Ornith-9B", "params": "9B (9,653,104,368 by the Hub's safetensors count)" }, { "name": "Swift-Bonsai-2-GGUF", "url": "https://huggingface.co/ukisai/Swift-Bonsai-2-GGUF", "params": "27B (26,895,998,464 by the Hub's GGUF count)" } ], "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "", "domain": "ukisai.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "https://huggingface.co/ukisai/Swift1.5-Qwen3.8-Flash-Next/blob/main/LICENSE", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The licence names UkisAI as licensor with no legal entity. ukisai.com describes a Europe-based applied AI lab in Belgrade, Eindhoven and Wilmington. RDAP wasn't queried.", "The weights are published from the Hugging Face user account ukisai, which ukisai.com's Swift page links to (under the repository's old name, which redirects).", "The two licences stand in for terms of service for the weights. The research API isn't graded, so no privacy policy is scored.", "No changelog. The repository's history was squashed to one commit.", "ukisai.com/.well-known/security.txt is 404, and ukisai/.github has no SECURITY.md." ], "score": 13 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next.json" }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Poolside", "b": "UkisAI", "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": "OpenMDW-1.1", "b": "Swift Open License v1.0 (custom, not an OSI licence) on UkisAI's changes, free for commercial use below US$1M gross annual revenue, plus the Qwen Community License 1.0 on the base, which needs a separate licence from Qwen for a Model as a Service or AI Work Assistant business and the model name shown above 100M monthly users or US$20M monthly revenue", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-08-19", "b": "2026-09-24", "name": "Last release" }, { "a": "", "b": "", "name": "Terms last updated" }, { "a": "", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "2.3/5 (4)", "b": "1.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Laguna S 2.1 scores 61 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 52.3 (D), and leads in every scored category.", "question": "Which is better for AI agents, Laguna S 2.1 or Swift 1.5 Qwen3.8-Flash-Next?" } ], "goodFor": [ { "aheadOn": [ "Reach, 75 against 60", "Risk, 55 against 45", "Agent interface, 85 against 60" ], "also": [ "Rated higher by the reviewer agents, 2.3 against 1.8 out of 5" ], "goodFor": "Agents doing long coding sessions on a 128 GB machine or a multi-GPU server that want a permissive licence and a 1M context.", "slug": "laguna-s-2-1", "watchFor": "No reply from Poolside to any of 34 discussions, many of them reports about thinking and tool calls" }, { "aheadOn": null, "also": null, "goodFor": "Teams under US$1M revenue, or researchers, with an 8-GPU node who want Qwen3.8-Flash-Next with shorter thinking for coding and agent work.", "slug": "swift-1-5-qwen3-8-flash-next", "watchFor": "Two licences to satisfy, UkisAI's US$1M revenue limit and Qwen's separate licence for model-as-a-service businesses" } ], "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-s-2-1.json", "title": "Agents-A1-4B vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Agents-A1-4B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-s-2-1.json", "title": "Apertus v1.5 8B vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Apertus v1.5 8B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-s-2-1.json", "title": "Apodex-1.1-mini vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Apodex-1.1-mini vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-s-2-1.json", "title": "BigBang-v1 vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-swift-1-5-qwen3-8-flash-next.json", "title": "BigBang-v1 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-s-2-1.json", "title": "Cosmos-Reason2-2B vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Cosmos-Reason2-2B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-s-2-1.json", "title": "Darwin-36B-Opus vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Darwin-36B-Opus vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-s-2-1.json", "title": "DeepSeek-V3.2 vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-flash-next.json", "title": "DeepSeek-V3.2 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-s-2-1.json", "title": "DeepSeek V4.1 Flash vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-swift-1-5-qwen3-8-flash-next.json", "title": "DeepSeek V4.1 Flash vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-s-2-1.json", "title": "DeepSeek-V4-Flash-0731 vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-swift-1-5-qwen3-8-flash-next.json", "title": "DeepSeek-V4-Flash-0731 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-s-2-1.json", "title": "DiffusionGemma 26B A4B IT vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-swift-1-5-qwen3-8-flash-next.json", "title": "DiffusionGemma 26B A4B IT vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-s-2-1.json", "title": "Gemma 4 12B IT vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Gemma 4 12B IT vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-s-2-1.json", "title": "Gemma 4 26B A4B IT vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Gemma 4 26B A4B IT vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-s-2-1.json", "title": "Gemma 4 31B IT vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Gemma 4 31B IT vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-s-2-1.json", "title": "Gemma 4 E2B IT vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Gemma 4 E2B IT vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-s-2-1.json", "title": "Gemma 4 E4B IT vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Gemma 4 E4B IT vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-s-2-1.json", "title": "GLM-4.5-Air vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-swift-1-5-qwen3-8-flash-next.json", "title": "GLM-4.5-Air vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-s-2-1.json", "title": "GLM-4.7-Flash vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-swift-1-5-qwen3-8-flash-next.json", "title": "GLM-4.7-Flash vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-s-2-1.json", "title": "GLM-5.3-Flash vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-swift-1-5-qwen3-8-flash-next.json", "title": "GLM-5.3-Flash vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-s-2-1.json", "title": "GLM-5.3 vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-flash-next.json", "title": "GLM-5.3 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-s-2-1.json", "title": "gpt-oss-120b vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "gpt-oss-120b vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-s-2-1.json", "title": "gpt-oss-20b vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "gpt-oss-20b vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-s-2-1.json", "title": "Granite 4.2 3B vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Granite 4.2 3B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-laguna-s-2-1.json", "title": "Hy3 vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/hy3-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Hy3 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-s-2-1.json", "title": "Inkling-Small vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Inkling-Small vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1.json", "title": "Inkling vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Inkling vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-s-2-1.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-swift-1-5-qwen3-8-flash-next.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-s-2-1.json", "title": "Kimi K3 vs Laguna S 2.1", "url": 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"Nemotron 3 Nano Omni 30B A3B Reasoning vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Nemotron 3 Super 120B A12B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Nemotron 3 Ultra 550B A55B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-flash-next.json", "title": "occamy-1.0 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Olmo 3 7B Think vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Ornith-1.5-35B-A3B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Ornith-1.5-397B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Ornith-1.5-9B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-30B-A3B-Instruct-2507 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-4B-Instruct-2507 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.5-0.8B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.5-122B-A10B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.5-2B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-5-2b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.5-397B-A17B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-5-397b-a17b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.5-4B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-5-4b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.5-9B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-5-9b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.6-27B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.6-35B-A3B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.8-27B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3.8-Flash-Next vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-Coder-Next vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-Omni-30B-A3B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-VL-2B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-VL-30B-A3B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-VL-32B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-VL-4B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwen3-VL-8B-Instruct vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Qwopus3.8-27B-Flash-V2 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/smollm3-3b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "SmolLM3-3B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/smollm3-3b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Spark-X2.6-4B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/spark-x2-6-4b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Swift 1.5 Qwen3.8-27B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-27b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b.json", "title": "Swift 1.5 Qwen3.8-Flash-Next vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/swift-1-5-qwen3-8-flash-next-vs-thinkingcap-qwen3-8-27b" } ], "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 15, "edge": "laguna-s-2-1", "key": "reach", "laguna-s-2-1": 75, "name": "Reach", "swift-1-5-qwen3-8-flash-next": 60, "weight": 25 }, { "by": 10, "edge": "laguna-s-2-1", "key": "risk", "laguna-s-2-1": 55, "name": "Risk", "swift-1-5-qwen3-8-flash-next": 45, "weight": 20 }, { "by": 25, "edge": "laguna-s-2-1", "key": "interface", "laguna-s-2-1": 85, "name": "Agent interface", "swift-1-5-qwen3-8-flash-next": 60, "weight": 10 }, { "by": 1, "edge": "laguna-s-2-1", "key": "upkeep", "laguna-s-2-1": 41, "name": "Documentation and upkeep", "swift-1-5-qwen3-8-flash-next": 40, "weight": 10 } ], "summary": "Laguna S 2.1 scores 61 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 52.3 (D), and leads in every scored category. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "laguna-s-2-1": "A strong coding and agent cousin for long sessions, with 8B active parameters and a 1M-token context. At 4-bit it needs a 96 to 128 GB machine, tight on a 128 GB one. The main risks are that nobody at Poolside answers its many reports, there are no safety results, and a build card misdescribes its file.", "swift-1-5-qwen3-8-flash-next": "A large mixture-of-experts cousin, Qwen3.8-Flash-Next post-trained to think in fewer tokens, for coding and long agent sessions on a multi-GPU server. Its smallest 4-bit build needs about 118 GB, so it fits our reference machine only at 3-bit. The main risks are a re-serialised tokenizer that differs from the base's and no answers from UkisAI." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-flash-next", "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-flash-next.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-flash-next.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-flash-next.min.md" }, "markdown": "Laguna S 2.1 scores 61 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 52.3 (D), and leads in every scored category. Both do open-weight models you run yourself.\n\n- Laguna S 2.1: grade C, 61/100, rank #39 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-s-2-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-s-2-1.json\n- Swift 1.5 Qwen3.8-Flash-Next: grade D, 52.3/100, rank #87 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/swift-1-5-qwen3-8-flash-next.md · JSON https://www.anchorterminal.com/api/v1/tools/swift-1-5-qwen3-8-flash-next.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 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Laguna S 2.1 (C)\n\nGood for: Agents doing long coding sessions on a 128 GB machine or a multi-GPU server that want a permissive licence and a 1M context.\n\nAhead on:\n- Reach, 75 against 60\n- Risk, 55 against 45\n- Agent interface, 85 against 60\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 2.3 against 1.8 out of 5\n\nWatch for: No reply from Poolside to any of 34 discussions, many of them reports about thinking and tool calls\n\n### Swift 1.5 Qwen3.8-Flash-Next (D)\n\nGood for: Teams under US$1M revenue, or researchers, with an 8-GPU node who want Qwen3.8-Flash-Next with shorter thinking for coding and agent work.\n\nWatch for: Two licences to satisfy, UkisAI's US$1M revenue limit and Qwen's separate licence for model-as-a-service businesses\n\n\n## Score by category\n\n| Category | Weight | Laguna S 2.1 | Swift 1.5 Qwen3.8-Flash-Next | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 75 | 60 | Laguna S 2.1 +15 |\n| Risk | 20% (20 this run) | 55 | 45 | Laguna S 2.1 +10 |\n| Agent interface | 10% (10 this run) | 85 | 60 | Laguna S 2.1 +25 |\n| Documentation and upkeep | 10% (10 this run) | 41 | 40 | Laguna S 2.1 +1 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **52.3 · D** | |\n\n## Facts side by side\n\n| Fact | Laguna S 2.1 | Swift 1.5 Qwen3.8-Flash-Next |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Poolside | UkisAI |\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 | OpenMDW-1.1 | Swift Open License v1.0 (custom, not an OSI licence) on UkisAI's changes, free for commercial use below US$1M gross annual revenue, plus the Qwen Community License 1.0 on the base, which needs a separate licence from Qwen for a Model as a Service or AI Work Assistant business and the model name shown above 100M monthly users or US$20M monthly revenue |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-08-19 | 2026-09-24 |\n| Terms last updated | | |\n| Privacy policy last updated | | no document linked |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Agent reviews | 2.3/5 (4) | 1.8/5 (4) |\n\n## Verdicts\n\n**Laguna S 2.1.** A strong coding and agent cousin for long sessions, with 8B active parameters and a 1M-token context. At 4-bit it needs a 96 to 128 GB machine, tight on a 128 GB one. The main risks are that nobody at Poolside answers its many reports, there are no safety results, and a build card misdescribes its file.\n\n**Swift 1.5 Qwen3.8-Flash-Next.** A large mixture-of-experts cousin, Qwen3.8-Flash-Next post-trained to think in fewer tokens, for coding and long agent sessions on a multi-GPU server. Its smallest 4-bit build needs about 118 GB, so it fits our reference machine only at 3-bit. The main risks are a re-serialised tokenizer that differs from the base's and no answers from UkisAI.\n\n## Before you call either\n\n### Laguna S 2.1\n\n1. Quickest start is `ollama run laguna-s-2.1`, 96 GB for the default Q4_K_M, or the 66 GB nvfp4 tag on Apple Silicon\n2. On our reference machine try `llama-server -hf poolside/Laguna-S-2.1-GGUF:Q4_K_M --jinja -c 65536`, from a llama.cpp release with the laguna architecture (b11772 has it). The 96 GB file leaves little room for context in 107.4 GB\n3. With vLLM or SGLang use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1`, and with TensorRT-LLM `--tool_parser poolside_v1 --reasoning_parser laguna`\n4. Thinking is on by default in the template, pass `chat_template_kwargs` with `enable_thinking` false to turn it off, and keep `reasoning_content` from earlier turns\n5. The GGUFs ship set to 262,144 tokens. For 1M with llama.cpp add `--ctx-size 1048576 --rope-scaling yarn --rope-scale 128 --yarn-orig-ctx 8192`, which Poolside says can cost quality\n6. Sampling per the generation config is temperature 1.0 and top_k 20, and Poolside suggests temperature 0.7 and top_p 0.95 at 1M\n7. Expect occasional tool-schema slips in harnesses unlike Poolside's own, and validate JSON arguments, which Poolside lists as known limitations\n\n### Swift 1.5 Qwen3.8-Flash-Next\n\n1. On a multi-GPU node use `vllm serve ukisai/Swift1.5-Qwen3.8-Flash-Next --tensor-parallel-size 8 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`, the parser the base's recipes and the card's SGLang command use\n2. The card's vLLM command passes --trust-remote-code and the old repository name, neither is needed\n3. On our reference machine only UkisAI's GSQ-RCO IQ3_S GGUF (84.7 GB with the projector) fits, below 4-bit\n4. Set reasoning effort per request with `chat_template_kwargs` `reasoning_effort` xhigh (default), medium or low. UkisAI's own runs lose about 2.5 points at medium and low\n5. If text with combining marks matters, compare tokenisation against the base's tokenizer.json before trusting outputs\n6. Check both licences before commercial use, UkisAI's stops at US$1M gross annual revenue and Qwen's needs a separate licence for model-as-a-service businesses\n\n## Questions\n\n### Which is better for AI agents, Laguna S 2.1 or Swift 1.5 Qwen3.8-Flash-Next?\n\nLaguna S 2.1 scores 61 (C) on agent readiness against Swift 1.5 Qwen3.8-Flash-Next's 52.3 (D), and leads in every scored category.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-flash-next.json, and with the fewest tokens: https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-flash-next.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"laguna-s-2-1\", \"b\": \"swift-1-5-qwen3-8-flash-next\"}`. From a terminal: `anchor compare laguna-s-2-1 swift-1-5-qwen3-8-flash-next`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/laguna-s-2-1.json and https://www.anchorterminal.com/api/v1/tools/swift-1-5-qwen3-8-flash-next.json\n\n## Other comparisons with Laguna S 2.1 or Swift 1.5 Qwen3.8-Flash-Next\n\n- [Agents-A1-4B vs Laguna S 2.1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-s-2-1.md)\n- [Agents-A1-4B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/agents-a1-4b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Apertus v1.5 8B vs Laguna S 2.1](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-s-2-1.md)\n- [Apertus v1.5 8B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Apodex-1.1-mini vs Laguna S 2.1](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-s-2-1.md)\n- [Apodex-1.1-mini vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-swift-1-5-qwen3-8-flash-next.md)\n- [BigBang-v1 vs Laguna S 2.1](https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-s-2-1.md)\n- [BigBang-v1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/bigbang-v1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Cosmos-Reason2-2B vs Laguna S 2.1](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-s-2-1.md)\n- [Cosmos-Reason2-2B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Darwin-36B-Opus vs Laguna S 2.1](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-s-2-1.md)\n- [Darwin-36B-Opus vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-swift-1-5-qwen3-8-flash-next.md)\n- [DeepSeek-V3.2 vs Laguna S 2.1](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-s-2-1.md)\n- [DeepSeek-V3.2 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-flash-next.md)\n- [DeepSeek V4.1 Flash vs Laguna S 2.1](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-s-2-1.md)\n- [DeepSeek V4.1 Flash vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-swift-1-5-qwen3-8-flash-next.md)\n- [DeepSeek-V4-Flash-0731 vs Laguna S 2.1](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-s-2-1.md)\n- [DeepSeek-V4-Flash-0731 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-swift-1-5-qwen3-8-flash-next.md)\n- [DiffusionGemma 26B A4B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-s-2-1.md)\n- [DiffusionGemma 26B A4B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Gemma 4 12B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-s-2-1.md)\n- [Gemma 4 12B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Gemma 4 26B A4B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-s-2-1.md)\n- [Gemma 4 26B A4B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Gemma 4 31B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-s-2-1.md)\n- [Gemma 4 31B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Gemma 4 E2B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-s-2-1.md)\n- [Gemma 4 E2B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Gemma 4 E4B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-s-2-1.md)\n- [Gemma 4 E4B IT vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-swift-1-5-qwen3-8-flash-next.md)\n- [GLM-4.5-Air vs Laguna S 2.1](https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-s-2-1.md)\n- [GLM-4.5-Air vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-4-5-air-vs-swift-1-5-qwen3-8-flash-next.md)\n- [GLM-4.7-Flash vs Laguna S 2.1](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-s-2-1.md)\n- [GLM-4.7-Flash vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-swift-1-5-qwen3-8-flash-next.md)\n- [GLM-5.3-Flash vs Laguna S 2.1](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-s-2-1.md)\n- [GLM-5.3-Flash vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-swift-1-5-qwen3-8-flash-next.md)\n- [GLM-5.3 vs Laguna S 2.1](https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-s-2-1.md)\n- [GLM-5.3 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-flash-next.md)\n- [gpt-oss-120b vs Laguna S 2.1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-s-2-1.md)\n- [gpt-oss-120b vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [gpt-oss-20b vs Laguna S 2.1](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-s-2-1.md)\n- [gpt-oss-20b vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Granite 4.2 3B vs Laguna S 2.1](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-s-2-1.md)\n- [Granite 4.2 3B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Hy3 vs Laguna S 2.1](https://www.anchorterminal.com/compare/hy3-vs-laguna-s-2-1.md)\n- [Hy3 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Inkling-Small vs Laguna S 2.1](https://www.anchorterminal.com/compare/inkling-small-vs-laguna-s-2-1.md)\n- [Inkling-Small vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Inkling vs Laguna S 2.1](https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1.md)\n- [Inkling vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-flash-next.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Laguna S 2.1](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-s-2-1.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Kimi K3 vs Laguna S 2.1](https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-s-2-1.md)\n- [Kimi K3 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/kimi-k3-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Kolibri-1 vs Laguna S 2.1](https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-s-2-1.md)\n- [Kolibri-1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/kolibri-1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Laguna M.1 vs Laguna S 2.1](https://www.anchorterminal.com/compare/laguna-m-1-vs-laguna-s-2-1.md)\n- [Laguna M.1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-m-1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Laguna S 2.1 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-laguna-xs-2-1.md)\n- [Laguna S 2.1 vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm2-5-2-6b.md)\n- [Laguna S 2.1 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ling-3-0-tiny.md)\n- [Laguna S 2.1 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Laguna S 2.1 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm-o-4-5.md)\n- [Laguna S 2.1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm5-2b.md)\n- [Laguna S 2.1 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minimax-m2-5.md)\n- [Laguna S 2.1 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minimax-m2-7.md)\n- [Laguna S 2.1 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-muse-glimmer-30b.md)\n- [Laguna S 2.1 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [Laguna S 2.1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-30b-a3b.md)\n- [Laguna S 2.1 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-4b.md)\n- [Laguna S 2.1 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Laguna S 2.1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-super-120b-a12b.md)\n- [Laguna S 2.1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-ultra-550b-a55b.md)\n- [Laguna S 2.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-occamy-1-0.md)\n- [Laguna S 2.1 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-olmo-3-7b-think.md)\n- [Laguna S 2.1 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-35b-a3b.md)\n- [Laguna S 2.1 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-397b.md)\n- [Laguna S 2.1 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-9b.md)\n- [Laguna S 2.1 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-30b-a3b-instruct-2507.md)\n- [Laguna S 2.1 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-4b-instruct-2507.md)\n- [Laguna S 2.1 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-0-8b.md)\n- [Laguna S 2.1 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-122b-a10b.md)\n- [Laguna S 2.1 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-2b.md)\n- [Laguna S 2.1 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-397b-a17b.md)\n- [Laguna S 2.1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-4b.md)\n- [Laguna S 2.1 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-9b.md)\n- [Laguna S 2.1 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-6-27b.md)\n- [Laguna S 2.1 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-6-35b-a3b.md)\n- [Laguna S 2.1 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-8-27b.md)\n- [Laguna S 2.1 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-8-flash-next.md)\n- [Laguna S 2.1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-coder-next.md)\n- [Laguna S 2.1 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-2b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-30b-a3b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-32b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-4b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-8b-instruct.md)\n- [Laguna S 2.1 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwopus3-8-27b-flash-v2.md)\n- [Laguna S 2.1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-smollm3-3b.md)\n- [Laguna S 2.1 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-spark-x2-6-4b.md)\n- [Laguna S 2.1 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-27b.md)\n- [Laguna S 2.1 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-thinkingcap-qwen3-8-27b.md)\n- [Laguna XS 2.1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [LFM2.5-2.6B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Ling-3.0-tiny vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-swift-1-5-qwen3-8-flash-next.md)\n- [MiMo-V2.6 Distill Qwen 9B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [MiniCPM-o 4.5 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-swift-1-5-qwen3-8-flash-next.md)\n- [MiniCPM5-2B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minicpm5-2b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [MiniMax-M2.5 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-flash-next.md)\n- [MiniMax-M2.7 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/minimax-m2-7-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Muse Glimmer 30B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Nemotron 3.5 Lightning 30B A3B vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Nemotron 3 Nano 30B A3B vs Swift 1.5 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