{ "data": { "a": { "slug": "glm-5-3", "name": "GLM-5.3", "vendor": "Z.ai (Zhipu AI)", "vendorUrl": "https://z.ai", "kind": "weights", "category": "open-weights", "summary": "GLM-5.3 is Z.ai's open-weight mixture-of-experts model for coding and long-horizon agent work, 744B parameters with 40B active and a 1M-token context, published on Hugging Face in FP8 and BF16 under its own licence.", "url": "https://www.anchorterminal.com/tools/glm-5-3", "markdownUrl": "https://www.anchorterminal.com/tools/glm-5-3.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/glm-5-3.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/glm-5-3.json", "repo": "https://huggingface.co/zai-org/GLM-5.3", "license": "GLM-5.3 License (MIT-style, with a security review for the largest model-as-a-service operators)", "transports": [], "packages": [ { "registry": "huggingface", "name": "zai-org/GLM-5.3" }, { "registry": "huggingface", "name": "zai-org/GLM-5.3-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 GLM-5.3 License. A licensee running a model-as-a-service business with more than US$10 billion of revenue in 12 months must pass Z.AI's security review before commercial use. Running it yourself costs the hardware, 755.7 GB of FP8 files (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", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "reasoning", "tool-calling", "coding", "long-context", "custom-licence", "safetensors", "fp8", "self-hosted" ], "lastRelease": "2026-10-14", "graded": true, "anchor": { "graded": true, "score": 64.6, "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": 14, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 80, "interface": 70, "reach": 55, "risk": 50, "upkeep": 58 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "A large coding and long-horizon agent model with a 1M-token context, several tool calls per turn and three reasoning budgets. Z.ai's smallest build is 756 GB in FP8, so it needs an 8-GPU server, Z.ai's API or a provider. The main risks are no published safety work, no way to report a flaw, and thinking that can't be turned off.", "bestFor": "Teams with an 8-GPU server who want an open coding and long-horizon agent model with a 1M-token context, or agents that call it through Z.ai or a hosted provider", "strengths": [ "Model code in released llama.cpp b11768, vLLM 0.28.0, SGLang 0.5.22 and Transformers 5.12.0", "1,048,576 tokens of native context and three reasoning budgets per request", "Template renders several tool calls per turn, parsed by glm47 in vLLM and SGLang", "Safetensors only, no remote code, files in Z.ai's own organisation with a SHA-256 per shard", "Downloadable with no account, and hosted by Z.ai and five live providers on Hugging Face" ], "weaknesses": [ "Z.ai's smallest build is 755.6 GB in FP8, with no local Ollama or LM Studio build", "No safety evaluation, agent-use guidance or security contact", "Thinking is always on, and reasoning_effort only lowers it", "Commercial use by model-as-a-service operators above US$10 billion revenue needs Z.AI's security review", "The card leaves out limitations, architecture, parameters and cut-off, and zai-org answered 2 of 16 discussions, none since 8 September" ], "agentNotes": [ "Start it with `vllm serve zai-org/GLM-5.3 --kv-cache-dtype fp8 --tensor-parallel-size 8 --speculative-config.method mtp --speculative-config.num_speculative_tokens 5 --tool-call-parser glm47 --reasoning-parser glm47 --enable-auto-tool-choice --served-model-name glm-5.3` (vLLM 0.28.0 or later, 8xH200 or 8xH20 per vLLM's recipe)", "Use the glm47 tool-call and reasoning parsers in vLLM or SGLang; SGLang's cookbook says glm45 leaves the calls as plain text", "Pass `chat_template_kwargs: {\"reasoning_effort\": \"low\"}` for short tasks; anything other than low or high falls back to max", "Pass `clear_thinking: true` in chat use, since the template keeps earlier reasoning by default", "Don't send `enable_thinking: false`; the template ignores it and always opens a think block", "Validate JSON output yourself, since structured output is documented only for Z.ai's hosted API", "No Z.ai build fits a 128 GB machine; the full 1M context needs 8xB200 per vLLM's recipe" ], "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": 64.6 } ], "editorialScores": { "capability": 80, "interface": 70, "reach": 55, "risk": 50, "upkeep": 58 }, "provenanceScore": 68, "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's recipe, FP8 on one 8xH200 node\nuv pip install \"vllm\u003e=0.28.0\" --torch-backend=auto\nvllm serve zai-org/GLM-5.3 --kv-cache-dtype fp8 --tensor-parallel-size 8 \\\n --speculative-config.method mtp --speculative-config.num_speculative_tokens 5 \\\n --tool-call-parser glm47 --reasoning-parser glm47 --enable-auto-tool-choice \\\n --served-model-name glm-5.3", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"glm-5.3\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n \"chat_template_kwargs\": {\"reasoning_effort\": \"low\", \"clear_thinking\": true}\n }'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/glm-5-3" }, "sameCompany": [ "glm-4-5-air", "glm-4-7-flash", "glm-5-3-flash" ], "weights": { "trainedBy": "Z.ai", "builtOn": "GLM-5.2's base model (same base, new post-training)", "params": "744B", "active": "40B", "context": 1048576, "goodFor": "Large model for coding and long-horizon agent work with tool calling and always-on reasoning, text only.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "GLM-5.3", "url": "https://huggingface.co/zai-org/GLM-5.3", "who": "publisher", "precision": "fp8", "sizeGB": 755.6, "memoryGB": 1024, "format": "safetensors" }, { "name": "GLM-5.3-BF16", "url": "https://huggingface.co/zai-org/GLM-5.3-BF16", "who": "publisher", "precision": "bf16", "sizeGB": 1506.7, "memoryGB": 2048, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)" ] } ], "run": "vllm serve zai-org/GLM-5.3 --kv-cache-dtype fp8 --tensor-parallel-size 8 --speculative-config.method mtp --speculative-config.num_speculative_tokens 5 --tool-call-parser glm47 --reasoning-parser glm47 --enable-auto-tool-choice --served-model-name glm-5.3", "runBuild": "GLM-5.3", "checked": "2026-10-21", "minMemoryGB": 1024 }, "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-Flash", "url": "https://huggingface.co/zai-org/GLM-5.3-Flash", "params": "320B-A18B", "listing": "https://www.anchorterminal.com/tools/glm-5-3-flash" } ], "olderCount": 19, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "JINGSHENG HENGXING TECHNOLOGY PTE.LTD (operator of Z.ai per its terms of use, and registrant of z.ai). The licence names Z.AI", "domain": "z.ai", "domainRegistered": "2017-12-15", "domainNote": "z.ai was registered in 2017 and transferred in October 2024, so its age says little about the company's.", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/zai-org/GLM-5.3/commits/main", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "Z.ai's terms of use name JINGSHENG HENGXING TECHNOLOGY PTE.LTD as the operator of Z.ai, and RDAP names the same company as the registrant of z.ai. The weights' LICENSE names Z.AI as the copyright holder.", "Nothing is hosted for this listing, so the GLM-5.3 License stands in for terms of service and no privacy policy is scored.", "The changelog is the repository's commit history, 11 commits from 27 August to 14 October 2026, whose messages say what changed (two chat template fixes, on 4 September and 14 October, and evaluation results).", "z.ai/.well-known/security.txt and docs.z.ai/.well-known/security.txt answered 404 on 21 October 2026." ], "score": 68 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/glm-5-3.json" }, "answer": "GLM-5.3 scores 64.6 (B) on agent readiness against occamy-1.0's 61 (C), and leads in 0 of 4 scored categories. occamy-1.0 leads on reach, risk and documentation and upkeep.", "b": { "slug": "occamy-1-0", "name": "occamy-1.0", "vendor": "Accio (Accio-Lab)", "vendorUrl": "https://accio-lab.github.io/occamy/", "kind": "weights", "category": "open-weights", "summary": "Occamy-1.0 is Accio's open-weight agent model for long multi-step work with tools, files and code, a fine-tune of Qwen3.6-35B-A3B (35B mixture of experts, 3B active) published on Hugging Face under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/occamy-1-0", "markdownUrl": "https://www.anchorterminal.com/tools/occamy-1-0.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/occamy-1-0.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/occamy-1-0.json", "repo": "https://huggingface.co/Accio-Lab/occamy-1.0", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "Accio-Lab/occamy-1.0" }, { "registry": "huggingface", "name": "Accio-Lab/occamy-1.0-FP8" }, { "registry": "huggingface", "name": "Accio-Lab/occamy-1.0-NVFP4" }, { "registry": "huggingface", "name": "Accio-Lab/occamy-1.0-GGUF" }, { "registry": "huggingface", "name": "Accio-Lab/occamy-1.0-APEX-GGUF" }, { "registry": "huggingface", "name": "Accio-Lab/occamy-1.0-MLX-4bit" }, { "registry": "huggingface", "name": "Accio-Lab/occamy-1.0-MLX-mxfp4" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The main repository and all of Accio's build repositories are not gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0, the same licence as the Qwen3.6-35B-A3B base. Running it yourself costs the hardware, 70.2 GB for BF16 and 18.4 GB for the smallest 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/Accio-Lab/occamy-1.0", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "reasoning", "tool-calling", "agent", "coding", "derivative", "apache-2.0", "safetensors", "gguf", "mlx", "fp8", "nvfp4", "self-hosted" ], "lastRelease": "2026-10-02", "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": 44, "methodology": "0.6", "run": "2026-10-01", "scores": { "interface": 70, "reach": 85, "risk": 55, "upkeep": 74 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-10-21" }, "negative": 0, "verdict": "A Qwen3.6-35B-A3B fine-tuned for long agent work with tools, files and code, under plain Apache 2.0, and Accio's 4-bit builds run in about 23 GB. The main gaps are no safety results, agent guidance or security contact, and every benchmark figure is Accio's own.", "bestFor": "Agents that want an Apache 2.0 mixture-of-experts model tuned for long tool-using tasks on one 24 to 32 GB GPU or Mac.", "strengths": [ "Apache 2.0 like its base, with nothing gated", "Accio publishes FP8, NVFP4, GGUF and MLX builds, the 4-bit ones within 24 GB", "Same architecture and template as Qwen3.6-35B-A3B, so released llama.cpp, vLLM, SGLang and Transformers run it", "A technical report, the supervised data mix with token counts and a published data subset", "MD5 and SHA-256 checksums for every file" ], "weaknesses": [ "No safety results, prompt-injection guidance or security contact", "No hosted API or inference provider", "Tool-calling format and structured output aren't documented beyond the template and parser name", "Languages and a knowledge cut-off aren't stated", "The MLX builds await Apple Metal acceptance, per Accio's own cards" ], "agentNotes": [ "Serve with `--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` on vLLM 0.19.0 or SGLang 0.5.10 and later", "BF16 is 70.2 GB, so on a 128 GB machine run it without the card's 8-way tensor parallelism", "Keep the whole assistant message, reasoning and tool calls included, in later turns, as the card says", "Sampling per the card is temperature 1.0, top_p 0.95, top_k 20 and presence_penalty 1.5", "With the GGUFs, NFC-normalise input text and read TOKENIZER.md, since the files store qwen2 pre-tokenizer metadata", "The base's MTP layer isn't in this checkpoint, Accio-Lab/occamy-1.0-MTP is an experimental separate head" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 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": 70, "reach": 85, "risk": 55, "upkeep": 74 }, "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 Accio-Lab/occamy-1.0 --max-model-len 262144 --reasoning-parser qwen3 \\\n --enable-auto-tool-choice --tool-call-parser qwen3_coder\n# or a 4-bit GGUF with llama.cpp:\nllama-server -hf Accio-Lab/occamy-1.0-GGUF:Q4_K_M --jinja -c 131072", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -d '{\"model\": \"Accio-Lab/occamy-1.0\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/occamy-1-0" }, "weights": { "trainedBy": "Accio (Accio-Lab)", "builtOn": "Qwen/Qwen3.6-35B-A3B (Apache 2.0), declared in the card's metadata (base_model) and text as the post-trained starting checkpoint. Same qwen3_5_moe architecture and config apart from the removed MTP layer, and the same chat template. Occamy is also Apache 2.0", "params": "35B (3B active)", "active": "3B", "context": 262144, "goodFor": "Mixture-of-experts agent model for long multi-step work with tools, files, code and office tasks, text and images in, thinking on by default.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "occamy-1.0-MLX-mxfp4", "url": "https://huggingface.co/Accio-Lab/occamy-1.0-MLX-mxfp4", "who": "publisher", "precision": "mxfp4", "sizeGB": 18.4, "memoryGB": 24, "format": "mlx", "runsOn": [ "MLX" ], "note": "Text only. Apple Metal acceptance pending, per the card" }, { "name": "occamy-1.0-MLX-4bit", "url": "https://huggingface.co/Accio-Lab/occamy-1.0-MLX-4bit", "who": "publisher", "precision": "mlx-4bit", "sizeGB": 19.5, "memoryGB": 24, "format": "mlx", "runsOn": [ "MLX" ], "note": "Text only. Apple Metal acceptance pending, per the card" }, { "name": "occamy-1.0-IQ4_XS", "url": "https://huggingface.co/Accio-Lab/occamy-1.0-GGUF/blob/main/occamy-1.0-IQ4_XS.gguf", "who": "publisher", "precision": "iq4_xs", "sizeGB": 18.7, "memoryGB": 24, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ], "note": "Image input needs the 0.90 GB mmproj file. Input should be NFC-normalised, per the card" }, { "name": "occamy-1.0-APEX-Compact", "url": "https://huggingface.co/Accio-Lab/occamy-1.0-APEX-GGUF/blob/main/occamy-1.0-APEX-Compact.gguf", "who": "publisher", "precision": "mixed-q3-q4", "sizeGB": 16.5, "memoryGB": 24, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ], "note": "Most routed experts at Q3_K, so it doesn't count as a 4-bit build for the memory line" }, { "name": "occamy-1.0-NVFP4", "url": "https://huggingface.co/Accio-Lab/occamy-1.0-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 23.9, "memoryGB": 32, "format": "safetensors", "note": "Expert-only mixed precision, checked on H200 with Marlin W4A16, per the card" }, { "name": "occamy-1.0-Q4_K_M", "url": "https://huggingface.co/Accio-Lab/occamy-1.0-GGUF/blob/main/occamy-1.0-Q4_K_M.gguf", "who": "publisher", "precision": "q4_k_m", "sizeGB": 21.2, "memoryGB": 32, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ] }, { "name": "occamy-1.0-FP8", "url": "https://huggingface.co/Accio-Lab/occamy-1.0-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 36.6, "memoryGB": 48, "format": "safetensors", "runsOn": [ "vLLM", "SGLang" ] }, { "name": "occamy-1.0-Q8_0", "url": "https://huggingface.co/Accio-Lab/occamy-1.0-GGUF/blob/main/occamy-1.0-Q8_0.gguf", "who": "publisher", "precision": "q8_0", "sizeGB": 36.9, "memoryGB": 48, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ] }, { "name": "occamy-1.0", "url": "https://huggingface.co/Accio-Lab/occamy-1.0", "who": "publisher", "precision": "bf16", "sizeGB": 70.2, "memoryGB": 96, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)", "Transformers" ] } ], "run": "vllm serve Accio-Lab/occamy-1.0 --max-model-len 262144 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder", "runBuild": "occamy-1.0", "checked": "2026-10-21", "minMemoryGB": 24 }, "family": { "lab": "Accio (Accio-Lab)", "family": "occamy", "url": "https://www.anchorterminal.com/open-weights/#accio-lab", "others": [ { "name": "occamy-1.0-MTP", "url": "https://huggingface.co/Accio-Lab/occamy-1.0-MTP", "params": "not stated (draft head only)" } ], "olderCount": 4, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "", "domain": "accio-lab.github.io", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "No legal entity is named on the card, the report or the repository. The report's byline is Accio Team, and the Hugging Face organisation Accio-Lab (fullname Accio, 15 members) isn't verified. The GitHub README and the project website link the organisation.", "Nothing is hosted, so the licence stands in for terms of service and no privacy policy is scored.", "The project website is a GitHub Pages site drawn by script, so its text couldn't be read beyond the title.", "No SECURITY.md in Accio-Lab/occamy. The README sends bug reports and feature requests to GitHub issues." ], "score": 13 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/occamy-1-0.json" }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Z.ai (Zhipu AI)", "b": "Accio (Accio-Lab)", "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": "GLM-5.3 License (MIT-style, with a security review for the largest model-as-a-service operators)", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-14", "b": "2026-10-02", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "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": "2.8/5 (4)", "b": "3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "GLM-5.3 scores 64.6 (B) on agent readiness against occamy-1.0's 61 (C), and leads in 0 of 4 scored categories. occamy-1.0 leads on reach, risk and documentation and upkeep.", "question": "Which is better for AI agents, GLM-5.3 or occamy-1.0?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Teams with an 8-GPU server who want an open coding and long-horizon agent model with a 1M-token context, or agents that call it through Z.ai or a hosted provider", "slug": "glm-5-3", "watchFor": "Z.ai's smallest build is 755.6 GB in FP8, with no local Ollama or LM Studio build" }, { "aheadOn": [ "Reach, 85 against 55", "Risk, 55 against 50", "Documentation and upkeep, 74 against 58" ], "also": null, "goodFor": "Agents that want an Apache 2.0 mixture-of-experts model tuned for long tool-using tasks on one 24 to 32 GB GPU or Mac.", "slug": "occamy-1-0", "watchFor": "No safety results, prompt-injection guidance or security contact" } ], "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-glm-5-3.json", "title": "Agents-A1-4B vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-occamy-1-0.json", "title": "Agents-A1-4B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-glm-5-3.json", "title": "Apertus v1.5 8B vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-occamy-1-0.json", "title": "Apertus v1.5 8B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-glm-5-3.json", "title": "Apodex-1.1-mini vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-occamy-1-0.json", "title": "Apodex-1.1-mini vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-5-3.json", "title": "BigBang-v1 vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-occamy-1-0.json", "title": "BigBang-v1 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3.json", "title": "Cosmos-Reason2-2B vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-occamy-1-0.json", "title": "Cosmos-Reason2-2B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-5-3.json", "title": "Darwin-36B-Opus vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-occamy-1-0.json", "title": "Darwin-36B-Opus vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3.json", "title": "DeepSeek-V3.2 vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-occamy-1-0.json", "title": "DeepSeek-V3.2 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-glm-5-3.json", "title": "DeepSeek V4.1 Flash vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-occamy-1-0.json", "title": "DeepSeek V4.1 Flash vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-glm-5-3.json", "title": "DeepSeek-V4-Flash-0731 vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-occamy-1-0.json", "title": "DeepSeek-V4-Flash-0731 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-glm-5-3.json", "title": "DiffusionGemma 26B A4B IT vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-occamy-1-0.json", "title": "DiffusionGemma 26B A4B IT vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-glm-5-3.json", "title": "Gemma 4 12B IT vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-occamy-1-0.json", "title": "Gemma 4 12B IT vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-glm-5-3.json", "title": "Gemma 4 26B A4B IT vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-occamy-1-0.json", "title": "Gemma 4 26B A4B IT vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-glm-5-3.json", "title": "Gemma 4 31B IT vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-occamy-1-0.json", "title": "Gemma 4 31B IT vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-glm-5-3.json", "title": "Gemma 4 E2B IT vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-occamy-1-0.json", "title": "Gemma 4 E2B IT vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-glm-5-3.json", "title": "Gemma 4 E4B IT vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-occamy-1-0.json", "title": "Gemma 4 E4B IT vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-glm-5-3.json", "title": "GLM-4.5-Air vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-occamy-1-0.json", "title": "GLM-4.5-Air vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-glm-5-3.json", "title": "GLM-4.7-Flash vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-occamy-1-0.json", "title": "GLM-4.7-Flash vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-occamy-1-0.json", "title": "GLM-5.3-Flash vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-glm-5-3-flash.json", "title": "GLM-5.3 vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-120b.json", "title": "GLM-5.3 vs gpt-oss-120b", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-120b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-20b.json", "title": "GLM-5.3 vs gpt-oss-20b", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-20b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-3b.json", "title": "GLM-5.3 vs Granite 4.2 3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-hy3.json", "title": "GLM-5.3 vs Hy3", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling.json", "title": "GLM-5.3 vs Inkling", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-small.json", "title": "GLM-5.3 vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-internvl3-5-gpt-oss-20b-a4b-preview.json", "title": "GLM-5.3 vs InternVL3.5-GPT-OSS-20B-A4B-Preview", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-internvl3-5-gpt-oss-20b-a4b-preview" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3.json", "title": "GLM-5.3 vs Kimi K3", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-kolibri-1.json", "title": "GLM-5.3 vs Kolibri-1", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-kolibri-1" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-m-1.json", "title": "GLM-5.3 vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-m-1" }, { "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-laguna-xs-2-1.json", "title": "GLM-5.3 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm2-5-2-6b.json", "title": "GLM-5.3 vs LFM2.5-2.6B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-lfm2-5-2-6b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-0-tiny.json", "title": "GLM-5.3 vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-0-tiny" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-mimo-v2-6-distill-qwen-9b.json", "title": "GLM-5.3 vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-o-4-5.json", "title": "GLM-5.3 vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b.json", "title": "GLM-5.3 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-5.json", "title": "GLM-5.3 vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-7.json", "title": "GLM-5.3 vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-muse-glimmer-30b.json", "title": "GLM-5.3 vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "GLM-5.3 vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-30b-a3b.json", "title": "GLM-5.3 vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-4b.json", "title": "GLM-5.3 vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "GLM-5.3 vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-super-120b-a12b.json", "title": "GLM-5.3 vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-ultra-550b-a55b.json", "title": "GLM-5.3 vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-olmo-3-7b-think.json", "title": "GLM-5.3 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-35b-a3b.json", "title": "GLM-5.3 vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-397b.json", "title": "GLM-5.3 vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-9b.json", "title": "GLM-5.3 vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-30b-a3b-instruct-2507.json", "title": "GLM-5.3 vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-4b-instruct-2507.json", "title": "GLM-5.3 vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-0-8b.json", "title": "GLM-5.3 vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-122b-a10b.json", "title": "GLM-5.3 vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-2b.json", "title": "GLM-5.3 vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-397b-a17b.json", "title": "GLM-5.3 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-4b.json", "title": "GLM-5.3 vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-9b.json", "title": "GLM-5.3 vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-27b.json", "title": "GLM-5.3 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-35b-a3b.json", "title": "GLM-5.3 vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-27b.json", "title": "GLM-5.3 vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-flash-next.json", "title": "GLM-5.3 vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-30b-a3b-instruct.json", "title": "GLM-5.3 vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-next.json", "title": "GLM-5.3 vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-omni-30b-a3b-instruct.json", "title": "GLM-5.3 vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-2b-instruct.json", "title": "GLM-5.3 vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-30b-a3b-instruct.json", "title": "GLM-5.3 vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-32b-instruct.json", "title": "GLM-5.3 vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-4b-instruct.json", "title": "GLM-5.3 vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-8b-instruct.json", "title": "GLM-5.3 vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwopus3-8-27b-flash-v2.json", "title": "GLM-5.3 vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-smollm3-3b.json", "title": "GLM-5.3 vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-spark-x2-6-4b.json", "title": "GLM-5.3 vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-27b.json", "title": "GLM-5.3 vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-27b" }, { "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/glm-5-3-vs-thinkingcap-qwen3-8-27b.json", "title": "GLM-5.3 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-occamy-1-0.json", "title": "gpt-oss-120b vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-occamy-1-0.json", "title": "gpt-oss-20b vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-occamy-1-0.json", "title": "Granite 4.2 3B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-occamy-1-0.json", "title": "Hy3 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/hy3-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-occamy-1-0.json", "title": "Inkling-Small vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-occamy-1-0.json", "title": "Inkling vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/inkling-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-occamy-1-0.json", "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0.json", "title": "Kimi K3 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-occamy-1-0.json", "title": "Kolibri-1 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0.json", "title": "Laguna M.1 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-occamy-1-0.json", "title": "Laguna S 2.1 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-occamy-1-0.json", "title": "Laguna XS 2.1 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-occamy-1-0.json", "title": "LFM2.5-2.6B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-occamy-1-0.json", "title": "Ling-3.0-tiny vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-occamy-1-0.json", "title": "MiMo-V2.6 Distill Qwen 9B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-occamy-1-0.json", "title": "MiniCPM-o 4.5 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-occamy-1-0.json", "title": "MiniCPM5-2B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-occamy-1-0.json", "title": "MiniMax-M2.5 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-occamy-1-0.json", "title": "MiniMax-M2.7 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-occamy-1-0.json", "title": "Muse Glimmer 30B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-occamy-1-0.json", "title": "Nemotron 3.5 Lightning 30B A3B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-occamy-1-0.json", "title": "Nemotron 3 Nano 30B A3B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-occamy-1-0.json", "title": "Nemotron 3 Nano 4B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-occamy-1-0.json", "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-occamy-1-0.json", "title": "Nemotron 3 Super 120B A12B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-occamy-1-0.json", "title": "Nemotron 3 Ultra 550B A55B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-olmo-3-7b-think.json", "title": "occamy-1.0 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-35b-a3b.json", "title": "occamy-1.0 vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-397b.json", "title": "occamy-1.0 vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-9b.json", "title": "occamy-1.0 vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-30b-a3b-instruct-2507.json", "title": "occamy-1.0 vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507.json", "title": "occamy-1.0 vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-0-8b.json", "title": "occamy-1.0 vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-122b-a10b.json", "title": "occamy-1.0 vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-2b.json", "title": "occamy-1.0 vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-397b-a17b.json", "title": "occamy-1.0 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-4b.json", "title": "occamy-1.0 vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-9b.json", "title": "occamy-1.0 vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-27b.json", "title": "occamy-1.0 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-35b-a3b.json", "title": "occamy-1.0 vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-27b.json", "title": "occamy-1.0 vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-flash-next.json", "title": "occamy-1.0 vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-30b-a3b-instruct.json", "title": "occamy-1.0 vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-next.json", "title": "occamy-1.0 vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-omni-30b-a3b-instruct.json", "title": "occamy-1.0 vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-2b-instruct.json", "title": "occamy-1.0 vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-30b-a3b-instruct.json", "title": "occamy-1.0 vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-32b-instruct.json", "title": "occamy-1.0 vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-4b-instruct.json", "title": "occamy-1.0 vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-8b-instruct.json", "title": "occamy-1.0 vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwopus3-8-27b-flash-v2.json", "title": "occamy-1.0 vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-smollm3-3b.json", "title": "occamy-1.0 vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-spark-x2-6-4b.json", "title": "occamy-1.0 vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-27b.json", "title": "occamy-1.0 vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-27b" }, { "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/occamy-1-0-vs-thinkingcap-qwen3-8-27b.json", "title": "occamy-1.0 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-thinkingcap-qwen3-8-27b" } ], "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 30, "edge": "occamy-1-0", "glm-5-3": 55, "key": "reach", "name": "Reach", "occamy-1-0": 85, "weight": 25 }, { "by": 5, "edge": "occamy-1-0", "glm-5-3": 50, "key": "risk", "name": "Risk", "occamy-1-0": 55, "weight": 20 }, { "by": 0, "edge": "", "glm-5-3": 70, "key": "interface", "name": "Agent interface", "occamy-1-0": 70, "weight": 10 }, { "by": 16, "edge": "occamy-1-0", "glm-5-3": 58, "key": "upkeep", "name": "Documentation and upkeep", "occamy-1-0": 74, "weight": 10 } ], "summary": "GLM-5.3 scores 64.6 (B) on agent readiness against occamy-1.0's 61 (C), and leads in 0 of 4 scored categories. occamy-1.0 leads on reach, risk and documentation and upkeep. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "glm-5-3": "A large coding and long-horizon agent model with a 1M-token context, several tool calls per turn and three reasoning budgets. Z.ai's smallest build is 756 GB in FP8, so it needs an 8-GPU server, Z.ai's API or a provider. The main risks are no published safety work, no way to report a flaw, and thinking that can't be turned off.", "occamy-1-0": "A Qwen3.6-35B-A3B fine-tuned for long agent work with tools, files and code, under plain Apache 2.0, and Accio's 4-bit builds run in about 23 GB. The main gaps are no safety results, agent guidance or security contact, and every benchmark figure is Accio's own." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0", "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0.min.md" }, "markdown": "GLM-5.3 scores 64.6 (B) on agent readiness against occamy-1.0's 61 (C), and leads in 0 of 4 scored categories. occamy-1.0 leads on reach, risk and documentation and upkeep. Both do open-weight models you run yourself.\n\n- GLM-5.3: grade B, 64.6/100, rank #17 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/glm-5-3.md · JSON https://www.anchorterminal.com/api/v1/tools/glm-5-3.json\n- occamy-1.0: grade C, 61/100, rank #51 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/occamy-1-0.md · JSON https://www.anchorterminal.com/api/v1/tools/occamy-1-0.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 (B)\n\nGood for: Teams with an 8-GPU server who want an open coding and long-horizon agent model with a 1M-token context, or agents that call it through Z.ai or a hosted provider\n\nWatch for: Z.ai's smallest build is 755.6 GB in FP8, with no local Ollama or LM Studio build\n\n### occamy-1.0 (C)\n\nGood for: Agents that want an Apache 2.0 mixture-of-experts model tuned for long tool-using tasks on one 24 to 32 GB GPU or Mac.\n\nAhead on:\n- Reach, 85 against 55\n- Risk, 55 against 50\n- Documentation and upkeep, 74 against 58\n\nWatch for: No safety results, prompt-injection guidance or security contact\n\n\n## Score by category\n\n| Category | Weight | GLM-5.3 | occamy-1.0 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 55 | 85 | occamy-1.0 +30 |\n| Risk | 20% (20 this run) | 50 | 55 | occamy-1.0 +5 |\n| Agent interface | 10% (10 this run) | 70 | 70 | even |\n| Documentation and upkeep | 10% (10 this run) | 58 | 74 | occamy-1.0 +16 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **64.6 · B** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | GLM-5.3 | occamy-1.0 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Z.ai (Zhipu AI) | Accio (Accio-Lab) |\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 | GLM-5.3 License (MIT-style, with a security review for the largest model-as-a-service operators) | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-14 | 2026-10-02 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | 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) | 3/5 (4) |\n\n## Verdicts\n\n**GLM-5.3.** A large coding and long-horizon agent model with a 1M-token context, several tool calls per turn and three reasoning budgets. Z.ai's smallest build is 756 GB in FP8, so it needs an 8-GPU server, Z.ai's API or a provider. The main risks are no published safety work, no way to report a flaw, and thinking that can't be turned off.\n\n**occamy-1.0.** A Qwen3.6-35B-A3B fine-tuned for long agent work with tools, files and code, under plain Apache 2.0, and Accio's 4-bit builds run in about 23 GB. The main gaps are no safety results, agent guidance or security contact, and every benchmark figure is Accio's own.\n\n## Before you call either\n\n### GLM-5.3\n\n1. Start it with `vllm serve zai-org/GLM-5.3 --kv-cache-dtype fp8 --tensor-parallel-size 8 --speculative-config.method mtp --speculative-config.num_speculative_tokens 5 --tool-call-parser glm47 --reasoning-parser glm47 --enable-auto-tool-choice --served-model-name glm-5.3` (vLLM 0.28.0 or later, 8xH200 or 8xH20 per vLLM's recipe)\n2. Use the glm47 tool-call and reasoning parsers in vLLM or SGLang; SGLang's cookbook says glm45 leaves the calls as plain text\n3. Pass `chat_template_kwargs: {\"reasoning_effort\": \"low\"}` for short tasks; anything other than low or high falls back to max\n4. Pass `clear_thinking: true` in chat use, since the template keeps earlier reasoning by default\n5. Don't send `enable_thinking: false`; the template ignores it and always opens a think block\n6. Validate JSON output yourself, since structured output is documented only for Z.ai's hosted API\n7. No Z.ai build fits a 128 GB machine; the full 1M context needs 8xB200 per vLLM's recipe\n\n### occamy-1.0\n\n1. Serve with `--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder` on vLLM 0.19.0 or SGLang 0.5.10 and later\n2. BF16 is 70.2 GB, so on a 128 GB machine run it without the card's 8-way tensor parallelism\n3. Keep the whole assistant message, reasoning and tool calls included, in later turns, as the card says\n4. Sampling per the card is temperature 1.0, top_p 0.95, top_k 20 and presence_penalty 1.5\n5. With the GGUFs, NFC-normalise input text and read TOKENIZER.md, since the files store qwen2 pre-tokenizer metadata\n6. The base's MTP layer isn't in this checkpoint, Accio-Lab/occamy-1.0-MTP is an experimental separate head\n\n## Questions\n\n### Which is better for AI agents, GLM-5.3 or occamy-1.0?\n\nGLM-5.3 scores 64.6 (B) on agent readiness against occamy-1.0's 61 (C), and leads in 0 of 4 scored categories. occamy-1.0 leads on reach, risk and documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0.json, and with the fewest tokens: https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"glm-5-3\", \"b\": \"occamy-1-0\"}`. From a terminal: `anchor compare glm-5-3 occamy-1-0`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/glm-5-3.json and https://www.anchorterminal.com/api/v1/tools/occamy-1-0.json\n\n## Other comparisons with GLM-5.3 or occamy-1.0\n\n- [Agents-A1-4B vs GLM-5.3](https://www.anchorterminal.com/compare/agents-a1-4b-vs-glm-5-3.md)\n- [Agents-A1-4B vs occamy-1.0](https://www.anchorterminal.com/compare/agents-a1-4b-vs-occamy-1-0.md)\n- [Apertus v1.5 8B vs GLM-5.3](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-glm-5-3.md)\n- [Apertus v1.5 8B vs occamy-1.0](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-occamy-1-0.md)\n- [Apodex-1.1-mini vs GLM-5.3](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-glm-5-3.md)\n- [Apodex-1.1-mini vs occamy-1.0](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-occamy-1-0.md)\n- [BigBang-v1 vs GLM-5.3](https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-5-3.md)\n- [BigBang-v1 vs occamy-1.0](https://www.anchorterminal.com/compare/bigbang-v1-vs-occamy-1-0.md)\n- [Cosmos-Reason2-2B vs GLM-5.3](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-glm-5-3.md)\n- [Cosmos-Reason2-2B vs occamy-1.0](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-occamy-1-0.md)\n- [Darwin-36B-Opus vs GLM-5.3](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-glm-5-3.md)\n- [Darwin-36B-Opus vs occamy-1.0](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-occamy-1-0.md)\n- [DeepSeek-V3.2 vs GLM-5.3](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3.md)\n- [DeepSeek-V3.2 vs occamy-1.0](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-occamy-1-0.md)\n- [DeepSeek V4.1 Flash vs GLM-5.3](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-glm-5-3.md)\n- [DeepSeek V4.1 Flash vs occamy-1.0](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-occamy-1-0.md)\n- [DeepSeek-V4-Flash-0731 vs GLM-5.3](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-glm-5-3.md)\n- [DeepSeek-V4-Flash-0731 vs occamy-1.0](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-occamy-1-0.md)\n- [DiffusionGemma 26B A4B IT vs GLM-5.3](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-glm-5-3.md)\n- [DiffusionGemma 26B A4B IT vs occamy-1.0](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-occamy-1-0.md)\n- [Gemma 4 12B IT vs GLM-5.3](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-glm-5-3.md)\n- [Gemma 4 12B IT vs occamy-1.0](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-occamy-1-0.md)\n- [Gemma 4 26B A4B IT vs GLM-5.3](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-glm-5-3.md)\n- [Gemma 4 26B A4B IT vs occamy-1.0](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-occamy-1-0.md)\n- [Gemma 4 31B IT vs GLM-5.3](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-glm-5-3.md)\n- [Gemma 4 31B IT vs occamy-1.0](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-occamy-1-0.md)\n- [Gemma 4 E2B IT vs GLM-5.3](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-glm-5-3.md)\n- [Gemma 4 E2B IT vs occamy-1.0](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-occamy-1-0.md)\n- [Gemma 4 E4B IT vs GLM-5.3](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-glm-5-3.md)\n- [Gemma 4 E4B IT vs occamy-1.0](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-occamy-1-0.md)\n- [GLM-4.5-Air vs GLM-5.3](https://www.anchorterminal.com/compare/glm-4-5-air-vs-glm-5-3.md)\n- [GLM-4.5-Air vs occamy-1.0](https://www.anchorterminal.com/compare/glm-4-5-air-vs-occamy-1-0.md)\n- [GLM-4.7-Flash vs GLM-5.3](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-glm-5-3.md)\n- [GLM-4.7-Flash vs occamy-1.0](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-occamy-1-0.md)\n- [GLM-5.3-Flash vs occamy-1.0](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-occamy-1-0.md)\n- [GLM-5.3 vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/glm-5-3-vs-glm-5-3-flash.md)\n- [GLM-5.3 vs gpt-oss-120b](https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-120b.md)\n- [GLM-5.3 vs gpt-oss-20b](https://www.anchorterminal.com/compare/glm-5-3-vs-gpt-oss-20b.md)\n- [GLM-5.3 vs Granite 4.2 3B](https://www.anchorterminal.com/compare/glm-5-3-vs-granite-4-2-3b.md)\n- [GLM-5.3 vs Hy3](https://www.anchorterminal.com/compare/glm-5-3-vs-hy3.md)\n- [GLM-5.3 vs Inkling](https://www.anchorterminal.com/compare/glm-5-3-vs-inkling.md)\n- [GLM-5.3 vs Inkling-Small](https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-small.md)\n- [GLM-5.3 vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/glm-5-3-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [GLM-5.3 vs Kimi K3](https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3.md)\n- [GLM-5.3 vs Kolibri-1](https://www.anchorterminal.com/compare/glm-5-3-vs-kolibri-1.md)\n- [GLM-5.3 vs Laguna M.1](https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-m-1.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 Laguna XS 2.1](https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-xs-2-1.md)\n- [GLM-5.3 vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/glm-5-3-vs-lfm2-5-2-6b.md)\n- [GLM-5.3 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/glm-5-3-vs-ling-3-0-tiny.md)\n- [GLM-5.3 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/glm-5-3-vs-mimo-v2-6-distill-qwen-9b.md)\n- [GLM-5.3 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm-o-4-5.md)\n- [GLM-5.3 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/glm-5-3-vs-minicpm5-2b.md)\n- [GLM-5.3 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-5.md)\n- [GLM-5.3 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-7.md)\n- [GLM-5.3 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/glm-5-3-vs-muse-glimmer-30b.md)\n- [GLM-5.3 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [GLM-5.3 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-30b-a3b.md)\n- [GLM-5.3 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-4b.md)\n- [GLM-5.3 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [GLM-5.3 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-super-120b-a12b.md)\n- [GLM-5.3 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/glm-5-3-vs-nemotron-3-ultra-550b-a55b.md)\n- [GLM-5.3 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/glm-5-3-vs-olmo-3-7b-think.md)\n- [GLM-5.3 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-35b-a3b.md)\n- [GLM-5.3 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-397b.md)\n- [GLM-5.3 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/glm-5-3-vs-ornith-1-5-9b.md)\n- [GLM-5.3 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-30b-a3b-instruct-2507.md)\n- [GLM-5.3 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-4b-instruct-2507.md)\n- [GLM-5.3 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-0-8b.md)\n- [GLM-5.3 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-122b-a10b.md)\n- [GLM-5.3 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-2b.md)\n- [GLM-5.3 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-397b-a17b.md)\n- [GLM-5.3 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-4b.md)\n- [GLM-5.3 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-5-9b.md)\n- [GLM-5.3 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-27b.md)\n- [GLM-5.3 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-6-35b-a3b.md)\n- [GLM-5.3 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-27b.md)\n- [GLM-5.3 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-8-flash-next.md)\n- [GLM-5.3 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-30b-a3b-instruct.md)\n- [GLM-5.3 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-coder-next.md)\n- [GLM-5.3 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-omni-30b-a3b-instruct.md)\n- [GLM-5.3 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-2b-instruct.md)\n- [GLM-5.3 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-30b-a3b-instruct.md)\n- [GLM-5.3 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-32b-instruct.md)\n- [GLM-5.3 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-4b-instruct.md)\n- [GLM-5.3 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/glm-5-3-vs-qwen3-vl-8b-instruct.md)\n- [GLM-5.3 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/glm-5-3-vs-qwopus3-8-27b-flash-v2.md)\n- [GLM-5.3 vs SmolLM3-3B](https://www.anchorterminal.com/compare/glm-5-3-vs-smollm3-3b.md)\n- [GLM-5.3 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/glm-5-3-vs-spark-x2-6-4b.md)\n- [GLM-5.3 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/glm-5-3-vs-swift-1-5-qwen3-8-27b.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- [GLM-5.3 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/glm-5-3-vs-thinkingcap-qwen3-8-27b.md)\n- [gpt-oss-120b vs occamy-1.0](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-occamy-1-0.md)\n- [gpt-oss-20b vs occamy-1.0](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-occamy-1-0.md)\n- [Granite 4.2 3B vs occamy-1.0](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-occamy-1-0.md)\n- [Hy3 vs occamy-1.0](https://www.anchorterminal.com/compare/hy3-vs-occamy-1-0.md)\n- [Inkling-Small vs occamy-1.0](https://www.anchorterminal.com/compare/inkling-small-vs-occamy-1-0.md)\n- [Inkling vs occamy-1.0](https://www.anchorterminal.com/compare/inkling-vs-occamy-1-0.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs occamy-1.0](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-occamy-1-0.md)\n- [Kimi K3 vs occamy-1.0](https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0.md)\n- [Kolibri-1 vs occamy-1.0](https://www.anchorterminal.com/compare/kolibri-1-vs-occamy-1-0.md)\n- [Laguna M.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-m-1-vs-occamy-1-0.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 XS 2.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-occamy-1-0.md)\n- [LFM2.5-2.6B vs occamy-1.0](https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-occamy-1-0.md)\n- [Ling-3.0-tiny vs occamy-1.0](https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-occamy-1-0.md)\n- [MiMo-V2.6 Distill Qwen 9B vs occamy-1.0](https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-occamy-1-0.md)\n- [MiniCPM-o 4.5 vs occamy-1.0](https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-occamy-1-0.md)\n- [MiniCPM5-2B vs occamy-1.0](https://www.anchorterminal.com/compare/minicpm5-2b-vs-occamy-1-0.md)\n- [MiniMax-M2.5 vs occamy-1.0](https://www.anchorterminal.com/compare/minimax-m2-5-vs-occamy-1-0.md)\n- [MiniMax-M2.7 vs occamy-1.0](https://www.anchorterminal.com/compare/minimax-m2-7-vs-occamy-1-0.md)\n- [Muse Glimmer 30B vs occamy-1.0](https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-occamy-1-0.md)\n- [Nemotron 3.5 Lightning 30B A3B vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-occamy-1-0.md)\n- [Nemotron 3 Nano 30B A3B vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-occamy-1-0.md)\n- [Nemotron 3 Nano 4B vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-occamy-1-0.md)\n- [Nemotron 3 Nano Omni 30B A3B Reasoning vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-occamy-1-0.md)\n- [Nemotron 3 Super 120B A12B vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-occamy-1-0.md)\n- [Nemotron 3 Ultra 550B A55B vs occamy-1.0](https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-occamy-1-0.md)\n- [occamy-1.0 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/occamy-1-0-vs-olmo-3-7b-think.md)\n- [occamy-1.0 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-35b-a3b.md)\n- [occamy-1.0 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-397b.md)\n- [occamy-1.0 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/occamy-1-0-vs-ornith-1-5-9b.md)\n- [occamy-1.0 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-30b-a3b-instruct-2507.md)\n- [occamy-1.0 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507.md)\n- [occamy-1.0 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-0-8b.md)\n- [occamy-1.0 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-122b-a10b.md)\n- [occamy-1.0 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-2b.md)\n- [occamy-1.0 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-397b-a17b.md)\n- [occamy-1.0 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-4b.md)\n- [occamy-1.0 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-5-9b.md)\n- [occamy-1.0 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-27b.md)\n- [occamy-1.0 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-6-35b-a3b.md)\n- [occamy-1.0 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-27b.md)\n- [occamy-1.0 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-8-flash-next.md)\n- [occamy-1.0 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-30b-a3b-instruct.md)\n- [occamy-1.0 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-coder-next.md)\n- [occamy-1.0 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-omni-30b-a3b-instruct.md)\n- [occamy-1.0 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-2b-instruct.md)\n- [occamy-1.0 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-30b-a3b-instruct.md)\n- [occamy-1.0 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-32b-instruct.md)\n- [occamy-1.0 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-4b-instruct.md)\n- [occamy-1.0 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-vl-8b-instruct.md)\n- [occamy-1.0 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/occamy-1-0-vs-qwopus3-8-27b-flash-v2.md)\n- [occamy-1.0 vs SmolLM3-3B](https://www.anchorterminal.com/compare/occamy-1-0-vs-smollm3-3b.md)\n- [occamy-1.0 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/occamy-1-0-vs-spark-x2-6-4b.md)\n- [occamy-1.0 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-27b.md)\n- [occamy-1.0 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/occamy-1-0-vs-swift-1-5-qwen3-8-flash-next.md)\n- [occamy-1.0 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/occamy-1-0-vs-thinkingcap-qwen3-8-27b.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-21", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.6", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "GLM-5.3 vs occamy-1.0", "url": "" } ], "description": "GLM-5.3 scores 64.6 (B) to occamy-1.0's 61 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "GLM-5.3 B 64.6", "occamy-1.0 C 61", "scores" ], "h1": "GLM-5.3 vs occamy-1.0", "image": "https://www.anchorterminal.com/assets/og/compare-glm-5-3-vs-occamy-1-0.png", "path": "/compare/glm-5-3-vs-occamy-1-0", "published": "2026-10-01", "section": "tools", "title": "GLM-5.3 vs occamy-1.0 for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-21", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-occamy-1-0" }, "tokens": { "markdown": 5650, "slim": 480 }, "version": 1 }