{ "data": { "a": { "slug": "glm-5-3-flash", "name": "GLM-5.3-Flash", "vendor": "Z.ai", "vendorUrl": "https://z.ai", "kind": "weights", "category": "open-weights", "summary": "GLM-5.3-Flash is Z.ai's open-weight multimodal mixture-of-experts model, 320B parameters with 18B active and a 1,048,576-token context, published on Hugging Face in FP8 and BF16 under the MIT licence.", "url": "https://www.anchorterminal.com/tools/glm-5-3-flash", "markdownUrl": "https://www.anchorterminal.com/tools/glm-5-3-flash.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/glm-5-3-flash.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/glm-5-3-flash.json", "repo": "https://huggingface.co/zai-org/GLM-5.3-Flash", "license": "MIT", "transports": [], "packages": [ { "registry": "huggingface", "name": "zai-org/GLM-5.3-Flash" }, { "registry": "huggingface", "name": "zai-org/GLM-5.3-Flash-BF16" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under the MIT licence. Z.ai also sells hosted access as glm-5.3-flash on its own API, which isn't graded here. Running the weights yourself costs the hardware, 328.4 GB for the FP8 files and 642.7 GB for BF16 (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/zai-org/GLM-5.3-Flash", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "reasoning", "tool-calling", "mit", "safetensors", "fp8", "self-hosted" ], "lastRelease": "2026-08-26", "graded": true, "anchor": { "graded": true, "score": 65.1, "grade": "B", "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": 13, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 75, "interface": 70, "reach": 60, "risk": 55, "upkeep": 58 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "An MIT-licensed multimodal agent and coding model with a 1M-token context and several tool calls per turn, served by vLLM, SGLang, llama.cpp and Transformers. Z.ai's smallest build is 328 GB in FP8, so it needs a multi-GPU server. The main risk is that nothing on safety or prompt injection is published and there is no way to report a flaw.", "bestFor": "Teams with a multi-GPU server who want an MIT-licensed multimodal agent model with a 1M-token context, or agents that call it through a hosted provider", "strengths": [ "MIT weights with no use policy, downloadable with no account", "Model code in released llama.cpp b11768, vLLM 0.32.0, SGLang 0.5.22 and Transformers 5.16.1", "Safetensors only, no remote code, files in Z.ai's own organisation with a SHA-256 per shard", "1,048,576 tokens of native context and several tool calls per turn in the chat template", "Chat template changed as recently as 15 October 2026, and hosted by Z.ai and six other providers for agents without the hardware" ], "weaknesses": [ "Z.ai's smallest build is 328.4 GB in FP8, and no Ollama or LM Studio local build exists", "No safety evaluation, agent-use guidance or security contact", "Thinking is always on, and reasoning_effort only lowers it to low", "The tool-call format lives only in the chat template, with the parser named by the runtimes", "The card leaves out intended use, limitations, context length and knowledge cut-off, and no zai-org reply on discussions since 28 September" ], "agentNotes": [ "Start it with `vllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47` (vLLM 0.32.0 or later, about 386 GB of GPU memory per vLLM's recipe)", "Use the glm47 tool-call and reasoning parsers in vLLM or SGLang; calls come back as tool_call blocks with arg_key and arg_value pairs", "Pass `chat_template_kwargs: {\"reasoning_effort\": \"low\"}` for short tasks; anything other than low or high falls back to max", "Don't rely on `thinking: false` from SGLang's cookbook, since the template has no such switch and always opens a think block", "Set `clear_thinking: true` in chat use, since the default keeps earlier reasoning in the prompt", "On a 128 GB machine only third-party low-bit builds come near fitting, none of them from Z.ai" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "B", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 65.1 } ], "editorialScores": { "capability": 75, "interface": 70, "reach": 60, "risk": 55, "upkeep": 58 }, "provenanceScore": 53, "checked": { "categories": { "capability": "2026-10-21", "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 0.32.0 or later, per vLLM's recipe (FP8, about 386 GB of GPU memory)\nvllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 \\\n --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"zai-org/GLM-5.3-Flash\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"chat_template_kwargs\": {\"reasoning_effort\": \"low\"}}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/glm-5-3-flash" }, "sameCompany": [ "glm-4-5-air", "glm-4-7-flash", "glm-5-3" ], "weights": { "trainedBy": "Z.ai", "params": "320B", "active": "18B", "context": 1048576, "goodFor": "Multimodal agent and coding model: text, images and video in, text out, with tool calling and always-on reasoning.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "GLM-5.3-Flash-FP4-Local", "url": "https://huggingface.co/nvidia/GLM-5.3-Flash-FP4-Local", "who": "NVIDIA", "precision": "nvfp4", "sizeGB": 177.5, "memoryGB": 256, "format": "safetensors", "note": "NVIDIA's own FP4 build (Model Optimizer), made for NVIDIA Blackwell GPUs such as DGX Spark and RTX PRO 6000; FP4 kernels don't run on the AMD reference machine. Not the publisher's build, so it doesn't count toward Reach's memory item. Size summed from the Hub's file list on 21 October 2026." }, { "name": "GLM-5.3-Flash-NVFP4", "url": "https://huggingface.co/nvidia/GLM-5.3-Flash-NVFP4", "who": "NVIDIA", "precision": "nvfp4", "sizeGB": 204.4, "memoryGB": 256, "format": "safetensors", "note": "NVIDIA's own FP4 build (Model Optimizer), made for NVIDIA Blackwell GPUs such as DGX Spark and RTX PRO 6000; FP4 kernels don't run on the AMD reference machine. Not the publisher's build, so it doesn't count toward Reach's memory item. Size summed from the Hub's file list on 21 October 2026." }, { "name": "GLM-5.3-Flash", "url": "https://huggingface.co/zai-org/GLM-5.3-Flash", "who": "publisher", "precision": "fp8", "sizeGB": 328.3, "memoryGB": 512, "format": "safetensors" }, { "name": "GLM-5.3-Flash-BF16", "url": "https://huggingface.co/zai-org/GLM-5.3-Flash-BF16", "who": "publisher", "precision": "bf16", "sizeGB": 642.7, "memoryGB": 1024, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)" ] } ], "run": "vllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47", "runBuild": "GLM-5.3-Flash", "checked": "2026-10-21", "minMemoryGB": 256 }, "family": { "lab": "Z.ai (Zhipu AI)", "family": "GLM-5", "url": "https://www.anchorterminal.com/open-weights/#zai", "others": [ { "name": "GLM-5", "url": "https://huggingface.co/zai-org/GLM-5", "params": "744B-A40B" }, { "name": "GLM-5.1", "url": "https://huggingface.co/zai-org/GLM-5.1", "params": "744B-A40B" }, { "name": "GLM-5.2", "url": "https://huggingface.co/zai-org/GLM-5.2", "params": "744B-A40B" }, { "name": "GLM-5.3", "url": "https://huggingface.co/zai-org/GLM-5.3", "params": "744B-A40B", "listing": "https://www.anchorterminal.com/tools/glm-5-3" } ], "olderCount": 19, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "Z.AI Co., Ltd (named in the licence's copyright line)", "domain": "z.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/zai-org/GLM-5.3-Flash/commits/main", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The LICENSE file reads Copyright (c) 2026 Z.AI Co., Ltd. The registration date of z.ai couldn't be read, since the RDAP service answered 429 on 21 October 2026.", "Nothing is hosted, so the MIT licence stands in for terms of service and no privacy policy is scored.", "The changelog is the repository's commit history. Early messages say only \"update\"; later ones say what changed (a chat template fix on 4 September, evaluation results on 7 September and 12 October, a chat template speed-up on 15 October).", "z.ai/.well-known/security.txt and docs.z.ai/.well-known/security.txt answered 404 on 21 October 2026." ], "score": 53 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/glm-5-3-flash.json" }, "answer": "GLM-5.3-Flash scores 65.1 (B) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 3 of 5 scored categories. Olmo 3 7B Think leads on reach and risk.", "b": { "slug": "olmo-3-7b-think", "name": "Olmo 3 7B Think", "vendor": "Ai2 (Allen Institute for AI)", "vendorUrl": "https://allenai.org", "kind": "weights", "category": "open-weights", "summary": "Olmo 3 7B Think is Ai2's fully open 7B reasoning model for maths, code and step-by-step answers, with training data, code and checkpoints published, a 65,536-token context and thinking always on, released in November 2025 under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/olmo-3-7b-think", "markdownUrl": "https://www.anchorterminal.com/tools/olmo-3-7b-think.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/olmo-3-7b-think.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/olmo-3-7b-think.json", "repo": "https://huggingface.co/allenai/Olmo-3-7B-Think", "license": "Apache-2.0, with Ai2's Responsible Use Guidelines named on the card", "transports": [], "packages": [ { "registry": "huggingface", "name": "allenai/Olmo-3-7B-Think" }, { "registry": "ollama", "name": "olmo-3:7b-think" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. The card says it is intended for research and educational use in line with Ai2's Responsible Use Guidelines, which list disallowed uses outside research. Running it yourself costs the hardware, 14.6 GB in BF16 and 4.5 GB for Ollama's 4-bit build (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/allenai/Olmo-3-7B-Think", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "dense", "reasoning", "fully-open", "open-data", "apache-2.0", "safetensors", "self-hosted" ], "lastRelease": "2026-06-25", "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": 69, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 28, "interface": 35, "reach": 75, "risk": 75, "upkeep": 52 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "A fully open 7B reasoning cousin for maths, code and step-by-step answers, with every dataset and checkpoint published and its safety results rerunnable. Ollama's 4-bit build needs about 5.4 GB. It always thinks, wasn't trained for tool calls, has 65K of context, and Ai2 hasn't answered its discussions.", "bestFor": "Researchers and agents that want a small fully open reasoning model for maths and code, with its training data on hand", "strengths": [ "Training data, code, checkpoints and evaluation harness all published, the data with sources and sizes", "Safety results published with a harness to rerun them", "Ollama's 4-bit build fits in about 5.4 GB, and released llama.cpp, Ollama, vLLM, LM Studio and Transformers run it", "Safetensors only with no repository code, a checksum on every file and no gate", "Apache 2.0 with no revenue threshold" ], "weaknesses": [ "Not trained for tool calling, and the tool format lives only in the template", "Thinking is always on with no way to turn it off, and 65,536 tokens of context", "Ai2 publishes no quantised build and no provider hosts it", "The card binds use to Ai2's Responsible Use Guidelines, which Ai2 can change", "No Ai2 reply in the discussions, and the template's default prompt contradicts the card" ], "agentNotes": [ "Quickest start is `ollama run olmo-3:7b-think`, about 4.5 GB", "With vLLM, `vllm serve allenai/Olmo-3-7B-Think --max-model-len 65536`; vLLM runs it through its Transformers backend", "Sample at temperature 0.6 and top_p 0.95 with up to 32,768 output tokens, as the card recommends, since thinking traces are long", "Every reply starts with a think block; strip it yourself or use a reasoning parser that reads think tags", "Pass your own system prompt; the template's default says the cut-off is November 2024 and that no functions are available", "For tool calls use Olmo 3 7B Instruct instead, which Ai2 trained for function calling", "A discussion reports endless reasoning loops when served with vLLM, unanswered, so cap max_tokens", "Check the use against Ai2's Responsible Use Guidelines, which bar automated social-media posting and undisclosed automated content outside research" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "D", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 52.3 } ], "editorialScores": { "capability": 28, "interface": 35, "reach": 75, "risk": 75, "upkeep": 52 }, "provenanceScore": 71, "checked": { "categories": { "capability": "2026-10-21", "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 olmo-3:7b-think\n# or\nvllm serve allenai/Olmo-3-7B-Think --max-model-len 65536", "http": "curl http://localhost:11434/api/chat \\\n -d '{\"model\": \"olmo-3:7b-think\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"options\": {\"temperature\": 0.6, \"top_p\": 0.95}}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/olmo-3-7b-think" }, "weights": { "trainedBy": "Ai2 (Allen Institute for AI)", "builtOn": "allenai/Olmo-3-7B-Think-DPO", "params": "7.3B", "context": 65536, "goodFor": "Fully open 7B reasoning model for maths, code and step-by-step answers in English, with published training data and checkpoints for research, always thinking, not trained for tool calls.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "LM Studio", "Transformers" ], "builds": [ { "name": "ollama olmo-3:7b-think-q4_K_M", "url": "https://ollama.com/library/olmo-3:7b-think-q4_K_M", "who": "ollama", "precision": "q4_k_m", "sizeGB": 4.5, "memoryGB": 8, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Digest b8d4c92ac9c1, also the 7b-think and latest tags. q8_0 is 7.8 GB and fp16 15 GB. Sizes as Ollama's tags page shows them" }, { "name": "LM Studio allenai/olmo-3-7b-think (Q4_K_M GGUF)", "url": "https://huggingface.co/lmstudio-community/Olmo-3-7B-Think-GGUF", "who": "lmstudio", "precision": "q4_k_m", "sizeGB": 4.5, "memoryGB": 8, "format": "gguf", "runsOn": [ "LM Studio", "llama.cpp" ], "note": "Olmo-3-7B-Think-Q4_K_M.gguf, 4.47 GB from the Hub's file list. The catalogue entry also lists Q6_K, Q8_0 and MLX 4, 6 and 8-bit builds; the MLX 4-bit is 4.12 GB (Mac only)" }, { "name": "Olmo-3-7B-Think", "url": "https://huggingface.co/allenai/Olmo-3-7B-Think", "who": "publisher", "precision": "bf16", "sizeGB": 14.6, "memoryGB": 24, "format": "safetensors", "runsOn": [ "vLLM", "Transformers" ] } ], "run": "vllm serve allenai/Olmo-3-7B-Think --max-model-len 65536", "runBuild": "Olmo-3-7B-Think", "checked": "2026-10-21", "minMemoryGB": 8 }, "family": { "lab": "Ai2 (Allen Institute for AI)", "family": "Olmo 3 (3, 3.1)", "url": "https://www.anchorterminal.com/open-weights/#ai2", "others": [ { "name": "Olmo-3.1-7B-RL-Zero-Math", "url": "https://huggingface.co/allenai/Olmo-3.1-7B-RL-Zero-Math", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3.1-7B-RL-Zero-Code", "url": "https://huggingface.co/allenai/Olmo-3.1-7B-RL-Zero-Code", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3.1-32B-Think", "url": "https://huggingface.co/allenai/Olmo-3.1-32B-Think", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3.1-32B-Instruct", "url": "https://huggingface.co/allenai/Olmo-3.1-32B-Instruct", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3-7B-RL-Zero-Mix", "url": "https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-Mix", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-Instruct-DPO", "url": "https://huggingface.co/allenai/Olmo-3-7B-Instruct-DPO", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-Instruct", "url": "https://huggingface.co/allenai/Olmo-3-7B-Instruct", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-32B-Think", "url": "https://huggingface.co/allenai/Olmo-3-32B-Think", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3.1-32B-Instruct-SFT", "url": "https://huggingface.co/allenai/Olmo-3.1-32B-Instruct-SFT", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3.1-32B-Instruct-DPO", "url": "https://huggingface.co/allenai/Olmo-3.1-32B-Instruct-DPO", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3-7B-Think-DPO", "url": "https://huggingface.co/allenai/Olmo-3-7B-Think-DPO", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-RL-Zero-Math", "url": "https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-Math", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-RL-Zero-IF", "url": "https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-IF", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-RL-Zero-General", "url": "https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-General", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-RL-Zero-Code", "url": "https://huggingface.co/allenai/Olmo-3-7B-RL-Zero-Code", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-7B-Instruct-SFT", "url": "https://huggingface.co/allenai/Olmo-3-7B-Instruct-SFT", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-32B-Think-SFT", "url": "https://huggingface.co/allenai/Olmo-3-32B-Think-SFT", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3-32B-Think-DPO", "url": "https://huggingface.co/allenai/Olmo-3-32B-Think-DPO", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3-1125-32B", "url": "https://huggingface.co/allenai/Olmo-3-1125-32B", "params": "32B (Hub safetensors count 32.23B)" }, { "name": "Olmo-3-7B-Think-SFT", "url": "https://huggingface.co/allenai/Olmo-3-7B-Think-SFT", "params": "7B (Hub safetensors count 7.30B)" }, { "name": "Olmo-3-1025-7B", "url": "https://huggingface.co/allenai/Olmo-3-1025-7B", "params": "7B (Hub safetensors count 7.30B)" } ], "olderCount": 95, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "The Allen Institute for Artificial Intelligence (Ai2), a 501(c)(3) nonprofit, per its Responsible Use Guidelines", "domain": "allenai.org", "domainRegistered": "2010-12-03", "endpointOnVendorDomain": null, "terms": "https://allenai.org/terms", "privacy": "https://allenai.org/privacy-policy", "statusPage": "", "changelog": "", "securityTxt": "expired", "checked": "2026-10-21", "notes": [ "RDAP for allenai.org gives a registration date of 3 December 2010.", "Nothing is hosted, so the licence stands in for terms of service and no privacy policy is scored. Ai2's guidelines say its website terms also govern use of its tools.", "allenai.org serves a security.txt with a contact and an Expires date of 31 July 2026, which has passed. The Responsible Use Guidelines name a channel for bugs and security concerns with Ai2's models.", "No changelog. 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"https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-ornith-1-5-9b.json", "title": "Olmo 3 7B Think vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Olmo 3 7B Think vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-4b-instruct-2507.json", "title": "Olmo 3 7B Think vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-0-8b.json", "title": "Olmo 3 7B Think vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-122b-a10b.json", "title": "Olmo 3 7B Think vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-2b.json", "title": "Olmo 3 7B Think vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-397b-a17b.json", "title": "Olmo 3 7B Think vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-4b.json", "title": "Olmo 3 7B Think vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-9b.json", "title": "Olmo 3 7B Think vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-27b.json", "title": "Olmo 3 7B Think vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-35b-a3b.json", "title": "Olmo 3 7B Think vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-27b.json", "title": "Olmo 3 7B Think vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-flash-next.json", "title": "Olmo 3 7B Think vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-next.json", "title": "Olmo 3 7B Think vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-2b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-32b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-4b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-8b-instruct.json", "title": "Olmo 3 7B Think vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwopus3-8-27b-flash-v2.json", "title": "Olmo 3 7B Think vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-smollm3-3b.json", "title": "Olmo 3 7B Think vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-spark-x2-6-4b.json", "title": "Olmo 3 7B Think vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-swift-1-5-qwen3-8-27b.json", "title": "Olmo 3 7B Think vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-swift-1-5-qwen3-8-27b" }, { "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/olmo-3-7b-think-vs-thinkingcap-qwen3-8-27b.json", "title": "Olmo 3 7B Think vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-thinkingcap-qwen3-8-27b" } ], "scores": [ { "by": 47, "edge": "glm-5-3-flash", "glm-5-3-flash": 75, "key": "capability", "name": "Capability", "olmo-3-7b-think": 28, "weight": 35 }, { "by": 15, "edge": "olmo-3-7b-think", "glm-5-3-flash": 60, "key": "reach", "name": "Reach", "olmo-3-7b-think": 75, "weight": 25 }, { "by": 20, "edge": "olmo-3-7b-think", "glm-5-3-flash": 55, "key": "risk", "name": "Risk", "olmo-3-7b-think": 75, "weight": 20 }, { "by": 35, "edge": "glm-5-3-flash", "glm-5-3-flash": 70, "key": "interface", "name": "Agent interface", "olmo-3-7b-think": 35, "weight": 10 }, { "by": 6, "edge": "glm-5-3-flash", "glm-5-3-flash": 58, "key": "upkeep", "name": "Documentation and upkeep", "olmo-3-7b-think": 52, "weight": 10 } ], "summary": "GLM-5.3-Flash scores 65.1 (B) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 3 of 5 scored categories. Olmo 3 7B Think leads on reach and risk. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "glm-5-3-flash": "An MIT-licensed multimodal agent and coding model with a 1M-token context and several tool calls per turn, served by vLLM, SGLang, llama.cpp and Transformers. Z.ai's smallest build is 328 GB in FP8, so it needs a multi-GPU server. The main risk is that nothing on safety or prompt injection is published and there is no way to report a flaw.", "olmo-3-7b-think": "A fully open 7B reasoning cousin for maths, code and step-by-step answers, with every dataset and checkpoint published and its safety results rerunnable. Ollama's 4-bit build needs about 5.4 GB. It always thinks, wasn't trained for tool calls, has 65K of context, and Ai2 hasn't answered its discussions." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-olmo-3-7b-think", "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-olmo-3-7b-think.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-olmo-3-7b-think.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-olmo-3-7b-think.min.md" }, "markdown": "GLM-5.3-Flash scores 65.1 (B) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 3 of 5 scored categories. Olmo 3 7B Think leads on reach and risk. Both do open-weight models you run yourself.\n\n- GLM-5.3-Flash: grade B, 65.1/100, rank #16 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/glm-5-3-flash.md · JSON https://www.anchorterminal.com/api/v1/tools/glm-5-3-flash.json\n- Olmo 3 7B Think: grade D, 52.3/100, rank #86 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/olmo-3-7b-think.md · JSON https://www.anchorterminal.com/api/v1/tools/olmo-3-7b-think.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### GLM-5.3-Flash (B)\n\nGood for: Teams with a multi-GPU server who want an MIT-licensed multimodal agent model with a 1M-token context, or agents that call it through a hosted provider\n\nAhead on:\n- Capability, 75 against 28\n- Agent interface, 70 against 35\n- Documentation and upkeep, 58 against 52\n\nWatch for: Z.ai's smallest build is 328.4 GB in FP8, and no Ollama or LM Studio local build exists\n\n### Olmo 3 7B Think (D)\n\nGood for: Researchers and agents that want a small fully open reasoning model for maths and code, with its training data on hand\n\nAhead on:\n- Reach, 75 against 60\n- Risk, 75 against 55\n\nWatch for: Not trained for tool calling, and the tool format lives only in the template\n\n\n## Score by category\n\n| Category | Weight | GLM-5.3-Flash | Olmo 3 7B Think | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 75 | 28 | GLM-5.3-Flash +47 |\n| Reach | 25% (25 this run) | 60 | 75 | Olmo 3 7B Think +15 |\n| Risk | 20% (20 this run) | 55 | 75 | Olmo 3 7B Think +20 |\n| Agent interface | 10% (10 this run) | 70 | 35 | GLM-5.3-Flash +35 |\n| Documentation and upkeep | 10% (10 this run) | 58 | 52 | GLM-5.3-Flash +6 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **65.1 · B** | **52.3 · D** | |\n\n## Facts side by side\n\n| Fact | GLM-5.3-Flash | Olmo 3 7B Think |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Z.ai | Ai2 (Allen Institute for AI) |\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 | MIT | Apache-2.0, with Ai2's Responsible Use Guidelines named on the card |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-08-26 | 2026-06-25 |\n| Terms last updated | no document linked | |\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 | 2.8/5 (4) | 2.8/5 (4) |\n\n## Verdicts\n\n**GLM-5.3-Flash.** An MIT-licensed multimodal agent and coding model with a 1M-token context and several tool calls per turn, served by vLLM, SGLang, llama.cpp and Transformers. Z.ai's smallest build is 328 GB in FP8, so it needs a multi-GPU server. The main risk is that nothing on safety or prompt injection is published and there is no way to report a flaw.\n\n**Olmo 3 7B Think.** A fully open 7B reasoning cousin for maths, code and step-by-step answers, with every dataset and checkpoint published and its safety results rerunnable. Ollama's 4-bit build needs about 5.4 GB. It always thinks, wasn't trained for tool calls, has 65K of context, and Ai2 hasn't answered its discussions.\n\n## Before you call either\n\n### GLM-5.3-Flash\n\n1. Start it with `vllm serve zai-org/GLM-5.3-Flash --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser glm47 --reasoning-parser glm47` (vLLM 0.32.0 or later, about 386 GB of GPU memory per vLLM's recipe)\n2. Use the glm47 tool-call and reasoning parsers in vLLM or SGLang; calls come back as tool_call blocks with arg_key and arg_value pairs\n3. Pass `chat_template_kwargs: {\"reasoning_effort\": \"low\"}` for short tasks; anything other than low or high falls back to max\n4. Don't rely on `thinking: false` from SGLang's cookbook, since the template has no such switch and always opens a think block\n5. Set `clear_thinking: true` in chat use, since the default keeps earlier reasoning in the prompt\n6. On a 128 GB machine only third-party low-bit builds come near fitting, none of them from Z.ai\n\n### Olmo 3 7B Think\n\n1. Quickest start is `ollama run olmo-3:7b-think`, about 4.5 GB\n2. With vLLM, `vllm serve allenai/Olmo-3-7B-Think --max-model-len 65536`; vLLM runs it through its Transformers backend\n3. Sample at temperature 0.6 and top_p 0.95 with up to 32,768 output tokens, as the card recommends, since thinking traces are long\n4. Every reply starts with a think block; strip it yourself or use a reasoning parser that reads think tags\n5. Pass your own system prompt; the template's default says the cut-off is November 2024 and that no functions are available\n6. For tool calls use Olmo 3 7B Instruct instead, which Ai2 trained for function calling\n7. A discussion reports endless reasoning loops when served with vLLM, unanswered, so cap max_tokens\n8. Check the use against Ai2's Responsible Use Guidelines, which bar automated social-media posting and undisclosed automated content outside research\n\n## Questions\n\n### Which is better for AI agents, GLM-5.3-Flash or Olmo 3 7B Think?\n\nGLM-5.3-Flash scores 65.1 (B) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 3 of 5 scored categories. Olmo 3 7B Think leads on reach and risk.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/glm-5-3-flash-vs-olmo-3-7b-think.json, and with the fewest tokens: https://www.anchorterminal.com/compare/glm-5-3-flash-vs-olmo-3-7b-think.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"glm-5-3-flash\", \"b\": \"olmo-3-7b-think\"}`. From a terminal: `anchor compare glm-5-3-flash olmo-3-7b-think`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/glm-5-3-flash.json and https://www.anchorterminal.com/api/v1/tools/olmo-3-7b-think.json\n\n## Other comparisons with GLM-5.3-Flash or Olmo 3 7B Think\n\n- [Agents-A1-4B vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/agents-a1-4b-vs-glm-5-3-flash.md)\n- [Agents-A1-4B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/agents-a1-4b-vs-olmo-3-7b-think.md)\n- [Apertus v1.5 8B vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-glm-5-3-flash.md)\n- [Apertus v1.5 8B vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-olmo-3-7b-think.md)\n- [Apodex-1.1-mini vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-glm-5-3-flash.md)\n- [Apodex-1.1-mini vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-olmo-3-7b-think.md)\n- [BigBang-v1 vs 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