{
  "data": {
    "a": {
      "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",
      "dns": "olmo-3-7b-think.grade.anchorterminal.com",
      "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": 1518,
        "categoryRank": 103,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "capability": 28,
          "interface": 35,
          "reach": 75,
          "risk": 75,
          "upkeep": 52
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-11-04"
        },
        "negative": 0,
        "verdict": "A fully open 7B reasoning model 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": "0.7",
            "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": 70,
        "checked": {
          "categories": {
            "capability": "2026-11-04",
            "interface": "2026-11-04",
            "reach": "2026-11-04",
            "risk": "2026-11-04",
            "upkeep": "2026-11-04"
          },
          "last": "2026-11-04",
          "oldest": "2026-11-04",
          "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": "2026-11-04",
        "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. The commits are card edits, two configuration fixes from pull requests in November and December 2025, and a parameter-count fix on 25 June 2026.",
          "allenai.org links to huggingface.co/allenai, so the repository is the publisher's own."
        ],
        "score": 70
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/olmo-3-7b-think.json",
      "live": {
        "slug": "olmo-3-7b-think",
        "securityTxt": {
          "url": "https://allenai.org/.well-known/security.txt",
          "state": "expired",
          "expires": "2026-07-31T05:00:00.000Z",
          "checkedAt": "2026-11-10T16:07:23.74126383Z"
        },
        "domain": {
          "domain": "allenai.org",
          "registered": "2010-12-03",
          "source": "https://rdap.publicinterestregistry.org/rdap/domain/allenai.org",
          "checkedAt": "2026-11-08T15:03:50.561358192Z"
        },
        "pages": [
          {
            "url": "https://allenai.org/privacy-policy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-11-10T16:09:31.69478417Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "6575e6dd3713"
          },
          {
            "url": "https://allenai.org/terms",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-11-10T16:09:35.047986684Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "fde9cf039435"
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        ],
        "updatedAt": "2026-11-10T16:09:35.047986684Z"
      }
    },
    "answer": "ZAYA1-8B scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on risk.",
    "b": {
      "slug": "zaya1-8b",
      "name": "ZAYA1-8B",
      "vendor": "Zyphra",
      "vendorUrl": "https://www.zyphra.com",
      "kind": "weights",
      "category": "open-weights",
      "summary": "ZAYA1-8B is Zyphra's open-weight reasoning model, a mixture of experts of 8.4B parameters with 760M active, trained from scratch for maths and coding. Apache 2.0. Zyphra's 4-bit build is 5.9 GB. Released SGLang and Transformers run it.",
      "url": "https://www.anchorterminal.com/tools/zaya1-8b",
      "markdownUrl": "https://www.anchorterminal.com/tools/zaya1-8b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/zaya1-8b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/zaya1-8b.json",
      "dns": "zaya1-8b.grade.anchorterminal.com",
      "repo": "https://huggingface.co/Zyphra/ZAYA1-8B",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "Zyphra/ZAYA1-8B"
        },
        {
          "registry": "huggingface",
          "name": "Zyphra/ZAYA1-8B-FP8-Experts"
        },
        {
          "registry": "huggingface",
          "name": "Zyphra/ZAYA1-8B-MXFP4-Experts"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. None of the repositories is gated (checked 2026-11-10).",
      "pricing": "free",
      "pricingNotes": "Free to download and use under Apache 2.0, per the main repository's metadata. Running it yourself costs little: 5.9 GB with the experts at 4 bits (MXFP4), 9.6 GB in FP8 or 17.7 GB in BF16 (checked 2026-11-10).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-10"
      },
      "docsUrl": "https://huggingface.co/Zyphra/ZAYA1-8B",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "small",
        "reasoning",
        "maths",
        "coding",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "fp8",
        "mxfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-07-02",
      "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": 1518,
        "categoryRank": 67,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 60,
          "reach": 80,
          "risk": 55,
          "upkeep": 50
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety.",
        "bestFor": "People who want a small, fast reasoning model for maths and code and can live without tool calling",
        "strengths": [
          "Apache 2.0, ungated",
          "5.9 GB at 4 bits, 760M parameters active",
          "Released Transformers and SGLang carry the architecture",
          "Zyphra replied in most of the recent discussions",
          "The original checkpoint is kept beside the reshaped one"
        ],
        "weaknesses": [
          "Tool calling needs a parser that only Zyphra's vLLM fork has",
          "Released vLLM and llama.cpp don't run it, and there's no GGUF",
          "The card's install steps use forks",
          "No limitations, context length, languages, data or safety results on the card",
          "Benchmarks on the card are all from Zyphra's own harness"
        ],
        "agentNotes": [
          "Use it for reasoning, maths and code. Don't count on tool calling outside Zyphra's vLLM fork",
          "Run it with Transformers 5.22.2 or SGLang 0.5.23, which have the model built in",
          "Use temperature 1.0 and top_p 0.95 in general, and temperature 0.6 for agent and code work",
          "Download `Zyphra/ZAYA1-8B`, not the legacy repository, for the released runtimes",
          "The quantised repositories have no licence tag. The main one is Apache 2.0"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 60,
          "reach": 80,
          "risk": 55,
          "upkeep": 50
        },
        "provenanceScore": 56,
        "checked": {
          "categories": {
            "interface": "2026-11-10",
            "reach": "2026-11-10",
            "risk": "2026-11-10",
            "upkeep": "2026-11-10"
          },
          "last": "2026-11-10",
          "oldest": "2026-11-10",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "pip install \"sglang\u003e=0.5.23\"\npython -m sglang.launch_server --model-path Zyphra/ZAYA1-8B --reasoning-parser qwen3\n# the card's own route is vLLM from Zyphra's fork, with --tool-call-parser zaya_xml",
        "http": "# SGLang serves an OpenAI-compatible API at http://localhost:30000/v1. The card recommends temperature 1.0\n# and top_p 0.95 in general, and temperature 0.6 for agent and code work"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/zaya1-8b"
      },
      "weights": {
        "trainedBy": "Zyphra",
        "builtOn": "ZAYA1-reasoning-base, Zyphra's own pre-trained model, per the card",
        "params": "8.4B",
        "active": "760M",
        "context": 131072,
        "goodFor": "Long step-by-step reasoning in maths and code on a small machine, and as the model inside a test-time compute harness.",
        "runtimes": [
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "ZAYA1-8B-MXFP4-Experts",
            "url": "https://huggingface.co/Zyphra/ZAYA1-8B-MXFP4-Experts",
            "who": "publisher",
            "precision": "mxfp4",
            "sizeGB": 5.85,
            "memoryGB": 8,
            "format": "safetensors",
            "note": "Zyphra's build with the experts at 4 bits. Which released runtime loads it wasn't established"
          },
          {
            "name": "ZAYA1-8B-FP8-Experts",
            "url": "https://huggingface.co/Zyphra/ZAYA1-8B-FP8-Experts",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 9.64,
            "memoryGB": 12,
            "format": "safetensors",
            "note": "Zyphra's build with the experts in FP8"
          },
          {
            "name": "ZAYA1-8B (BF16 safetensors)",
            "url": "https://huggingface.co/Zyphra/ZAYA1-8B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 17.68,
            "memoryGB": 24,
            "format": "safetensors",
            "runsOn": [
              "SGLang",
              "Transformers"
            ],
            "note": "Four shards, reshaped for Transformers"
          }
        ],
        "run": "python -m sglang.launch_server --model-path Zyphra/ZAYA1-8B --reasoning-parser qwen3",
        "runBuild": "ZAYA1-8B (BF16 safetensors)",
        "checked": "2026-11-10",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "Zyphra",
        "family": "ZAYA1",
        "url": "https://www.anchorterminal.com/open-weights/#zyphra",
        "others": [
          {
            "name": "ZAYA1-VL-8B",
            "url": "https://huggingface.co/Zyphra/ZAYA1-VL-8B"
          },
          {
            "name": "ZAYA1-74B-preview",
            "url": "https://huggingface.co/Zyphra/ZAYA1-74B-preview"
          }
        ]
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Zyphra, named on the card and its site. The legal entity wasn't looked up",
        "domain": "zyphra.com",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/Zyphra/ZAYA1-8B/commits/main",
        "securityTxt": "none",
        "checked": "2026-11-10",
        "notes": [
          "www.zyphra.com's robots.txt allows reading outside /studio and /api. Its about page gives a San Francisco address and names no people in the text read.",
          "The domain's registration date wasn't looked up. www.zyphra.com has no security.txt (404 on 10 November 2026).",
          "Nothing is hosted under this listing, so Apache 2.0 stands in for terms of service and no privacy policy is scored. Zyphra's site lists a cloud product for its open models, which wasn't read.",
          "The changelog is the commit history, 41 commits from 4 May to 26 June 2026."
        ],
        "score": 56
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/zaya1-8b.json"
    },
    "edges": [
      {
        "by": 25,
        "category": "interface",
        "leads": "zaya1-8b",
        "name": "Agent interface",
        "reasons": {
          "a": "The chat template earns 20 for chat_template.jinja in the repository. The tool-calling format earns 10, since only the template and vLLM's own parser describe it. Trained tool calling earns nothing, because Ai2's report says tool calling was trained into the Instruct model, not Think. Structured output earns nothing. Reasoning control earns nothing, since it always thinks. Context earns 5 for 65,536 tokens trained. 20 + 10 + 0 + 0 + 0 + 5 = 35.",
          "b": "Chat template 20, chat_template.jinja in the repository (10,700 characters). Tool-calling format 10, only the template and a fork say it. Trained tool calling 10, the template takes tools and renders calls, and the card recommends settings for agent use, but it doesn't say the model was trained for tool calling or for several calls in a turn, so the lower band. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, the template has an enable_thinking switch, and the card names the qwen3 reasoning parser, which returns the reasoning apart from the answer. Context 10, 131,072 positions in config.json, for an architecture Zyphra trained end to end, so the config is the model's own. 20 + 10 + 10 + 0 + 10 + 10 = 60."
        },
        "scores": {
          "a": 35,
          "b": 60
        }
      },
      {
        "by": 20,
        "category": "risk",
        "leads": "olmo-3-7b-think",
        "name": "Risk",
        "reasons": {
          "a": "File safety earns 25, safetensors only and nothing from the repository runs. Provenance earns 15, files in the allenai organisation Ai2 links to, with a checksum for every file. Safety evaluation earns 20, as Ai2 publishes its safety results and the OLMES harness to rerun them. Agent guidance earns 5 for the card's general cautions. Licence risk earns 5, losing 5 for disallowed uses beyond the law and 5 because Ai2 can update the guidelines and end access at its discretion. The security programme earns 5 for a reporting route, a security.txt now past its expiry and a channel for security concerns in the guidelines, with no public advisories. 25 + 15 + 20 + 5 + 5 + 5 = 75.",
          "b": "File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the Zyphra organisation, which the card ties to zyphra.com's blog post for the model (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 0, no way to report a flaw on the card, and www.zyphra.com has no security.txt. 25 + 15 + 0 + 0 + 15 + 0 = 55."
        },
        "scores": {
          "a": 75,
          "b": 55
        }
      },
      {
        "by": 5,
        "category": "reach",
        "leads": "zaya1-8b",
        "name": "Reach",
        "reasons": {
          "a": "Memory earns the full 30, since Ollama's 4-bit build is 4.5 GB and fits 8 GB (per the 21 October check of Ollama's library). Runtimes earn 25, with released llama.cpp (b11963), Ollama (v0.40.14, pinning b11963), vLLM, LM Studio and Transformers all running it. Builds earn nothing, because Ai2 publishes no quantised build of its own. Terms earn 10, since the card binds Apache 2.0 to Ai2's Responsible Use Guidelines, a use policy. Download earns 10, with no gate. Hosted earns nothing, as the Hub's provider mapping is empty and Ai2 has no API for it. 30 + 25 + 0 + 10 + 10 + 0 = 75.",
          "b": "Memory 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB. Runtimes 10, Released Transformers 5.22.2 has the zaya model and SGLang 0.5.23 has srt/models/zaya.py. Builds 15, Quantised builds from Zyphra at two precisions, FP8 and MXFP4 for the experts, each in its own repository. Terms 15, Apache 2.0 in the card's metadata, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API. Zyphra's site lists a cloud product for its open models, which wasn't checked for this model. 30 + 10 + 15 + 15 + 10 + 0 = 80."
        },
        "scores": {
          "a": 75,
          "b": 80
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Ai2 (Allen Institute for AI)",
        "b": "Zyphra",
        "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": "Apache-2.0, with Ai2's Responsible Use Guidelines named on the card",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-06-25",
        "b": "2026-07-02",
        "name": "Last release"
      },
      {
        "a": "2024-09-25",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "2025-02-19",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "yes",
        "b": "not read yet",
        "name": "Customer content may train models"
      },
      {
        "a": "not found in the text",
        "b": "not read yet",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not found in the text",
        "b": "not read yet",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "yes",
        "b": "not read yet",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "not read yet",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "2.8/5 (4)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "ZAYA1-8B scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on risk.",
        "question": "Which is better for AI agents, Olmo 3 7B Think or ZAYA1-8B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 75 against 55"
        ],
        "also": null,
        "goodFor": "Researchers and agents that want a small fully open reasoning model for maths and code, with its training data on hand",
        "slug": "olmo-3-7b-think",
        "watchFor": "Not trained for tool calling, and the tool format lives only in the template"
      },
      {
        "aheadOn": [
          "Reach, 80 against 75",
          "Agent interface, 60 against 35"
        ],
        "also": null,
        "goodFor": "People who want a small, fast reasoning model for maths and code and can live without tool calling",
        "slug": "zaya1-8b",
        "watchFor": "Tool calling needs a parser that only Zyphra's vLLM fork has"
      }
    ],
    "history": null,
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-olmo-3-7b-think.json",
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        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-zaya1-8b.json",
        "title": "Agents-A1-4B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-olmo-3-7b-think.json",
        "title": "Apertus v1.5 8B vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-zaya1-8b.json",
        "title": "Apertus v1.5 8B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-olmo-3-7b-think.json",
        "title": "Apodex-1.1-mini vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-zaya1-8b.json",
        "title": "Apodex-1.1-mini vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-olmo-3-7b-think.json",
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        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-olmo-3-7b-think"
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      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-zaya1-8b.json",
        "title": "Arete-27B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-olmo-3-7b-think.json",
        "title": "BigBang-v1 vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-zaya1-8b.json",
        "title": "BigBang-v1 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-zaya1-8b"
      },
      {
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        "title": "Carbon-X vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-zaya1-8b.json",
        "title": "Carbon-X vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-olmo-3-7b-think.json",
        "title": "Cola2 vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-zaya1-8b.json",
        "title": "Cola2 vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-olmo-3-7b-think.json",
        "title": "Cosmos-Reason2-2B vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-zaya1-8b.json",
        "title": "Cosmos-Reason2-2B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-olmo-3-7b-think.json",
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-olmo-3-7b-think"
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-zaya1-8b"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-zaya1-8b"
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        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-zaya1-8b.json",
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        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-olmo-3-7b-think"
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        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-zaya1-8b.json",
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-olmo-3-7b-think.json",
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        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-zaya1-8b.json",
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-zaya1-8b.json",
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        "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-zaya1-8b"
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-olmo-3-7b-think.json",
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-zaya1-8b.json",
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-olmo-3-7b-think.json",
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        "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-zaya1-8b.json",
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        "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-zaya1-8b.json",
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-olmo-3-7b-think.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-olmo-3-7b-think.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-olmo-3-7b-think.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-zaya1-8b.json",
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        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-olmo-3-7b-think.json",
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        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-zaya1-8b.json",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-olmo-3-7b-think.json",
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-zaya1-8b.json",
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        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-zaya1-8b.json",
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    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 5,
        "edge": "zaya1-8b",
        "key": "reach",
        "name": "Reach",
        "olmo-3-7b-think": 75,
        "weight": 25,
        "zaya1-8b": 80
      },
      {
        "by": 20,
        "edge": "olmo-3-7b-think",
        "key": "risk",
        "name": "Risk",
        "olmo-3-7b-think": 75,
        "weight": 20,
        "zaya1-8b": 55
      },
      {
        "by": 25,
        "edge": "zaya1-8b",
        "key": "interface",
        "name": "Agent interface",
        "olmo-3-7b-think": 35,
        "weight": 10,
        "zaya1-8b": 60
      },
      {
        "by": 2,
        "edge": "olmo-3-7b-think",
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "olmo-3-7b-think": 52,
        "weight": 10,
        "zaya1-8b": 50
      }
    ],
    "summary": "ZAYA1-8B scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on risk. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "olmo-3-7b-think": "A fully open 7B reasoning model 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.",
      "zaya1-8b": "A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety."
    }
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  "markdown": "ZAYA1-8B scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on risk. Both do open-weight models you run yourself.\n\n- Olmo 3 7B Think: grade D, 52.3/100, rank #139 of 160 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- ZAYA1-8B: grade C, 61/100, rank #85 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/zaya1-8b.md · JSON https://www.anchorterminal.com/api/v1/tools/zaya1-8b.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### 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- Risk, 75 against 55\n\nWatch for: Not trained for tool calling, and the tool format lives only in the template\n\n### ZAYA1-8B (C)\n\nGood for: People who want a small, fast reasoning model for maths and code and can live without tool calling\n\nAhead on:\n- Reach, 80 against 75\n- Agent interface, 60 against 35\n\nWatch for: Tool calling needs a parser that only Zyphra's vLLM fork has\n\n\n## Why the edge\n\n### Agent interface: ZAYA1-8B +25\n\n- Olmo 3 7B Think (35): The chat template earns 20 for chat_template.jinja in the repository. The tool-calling format earns 10, since only the template and vLLM's own parser describe it. Trained tool calling earns nothing, because Ai2's report says tool calling was trained into the Instruct model, not Think. Structured output earns nothing. Reasoning control earns nothing, since it always thinks. Context earns 5 for 65,536 tokens trained. 20 + 10 + 0 + 0 + 0 + 5 = 35.\n- ZAYA1-8B (60): Chat template 20, chat_template.jinja in the repository (10,700 characters). Tool-calling format 10, only the template and a fork say it. Trained tool calling 10, the template takes tools and renders calls, and the card recommends settings for agent use, but it doesn't say the model was trained for tool calling or for several calls in a turn, so the lower band. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, the template has an enable_thinking switch, and the card names the qwen3 reasoning parser, which returns the reasoning apart from the answer. Context 10, 131,072 positions in config.json, for an architecture Zyphra trained end to end, so the config is the model's own. 20 + 10 + 10 + 0 + 10 + 10 = 60.\n\n### Risk: Olmo 3 7B Think +20\n\n- Olmo 3 7B Think (75): File safety earns 25, safetensors only and nothing from the repository runs. Provenance earns 15, files in the allenai organisation Ai2 links to, with a checksum for every file. Safety evaluation earns 20, as Ai2 publishes its safety results and the OLMES harness to rerun them. Agent guidance earns 5 for the card's general cautions. Licence risk earns 5, losing 5 for disallowed uses beyond the law and 5 because Ai2 can update the guidelines and end access at its discretion. The security programme earns 5 for a reporting route, a security.txt now past its expiry and a channel for security concerns in the guidelines, with no public advisories. 25 + 15 + 20 + 5 + 5 + 5 = 75.\n- ZAYA1-8B (55): File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in the Zyphra organisation, which the card ties to zyphra.com's blog post for the model (10). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on prompt injection, instruction priority or what the model refuses. Licence risk 15, Apache 2.0 has no use policy, threshold or change clause. Security programme 0, no way to report a flaw on the card, and www.zyphra.com has no security.txt. 25 + 15 + 0 + 0 + 15 + 0 = 55.\n\n### Reach: ZAYA1-8B +5\n\n- Olmo 3 7B Think (75): Memory earns the full 30, since Ollama's 4-bit build is 4.5 GB and fits 8 GB (per the 21 October check of Ollama's library). Runtimes earn 25, with released llama.cpp (b11963), Ollama (v0.40.14, pinning b11963), vLLM, LM Studio and Transformers all running it. Builds earn nothing, because Ai2 publishes no quantised build of its own. Terms earn 10, since the card binds Apache 2.0 to Ai2's Responsible Use Guidelines, a use policy. Download earns 10, with no gate. Hosted earns nothing, as the Hub's provider mapping is empty and Ai2 has no API for it. 30 + 25 + 0 + 10 + 10 + 0 = 75.\n- ZAYA1-8B (80): Memory 30, the smallest build from Zyphra is the MXFP4-Experts repository, 5.85 GB, and 5.85 GB × 1.2 = 7.0 GB, within 16 GB. Runtimes 10, Released Transformers 5.22.2 has the zaya model and SGLang 0.5.23 has srt/models/zaya.py. Builds 15, Quantised builds from Zyphra at two precisions, FP8 and MXFP4 for the experts, each in its own repository. Terms 15, Apache 2.0 in the card's metadata, an OSI licence with nothing added. Download 10, the Hub API reports gated false for the model and its builds on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API. Zyphra's site lists a cloud product for its open models, which wasn't checked for this model. 30 + 10 + 15 + 15 + 10 + 0 = 80.\n\n## Score by category\n\n| Category | Weight | Olmo 3 7B Think | ZAYA1-8B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 75 | 80 | ZAYA1-8B +5 |\n| Risk | 20% (20 this run) | 75 | 55 | Olmo 3 7B Think +20 |\n| Agent interface | 10% (10 this run) | 35 | 60 | ZAYA1-8B +25 |\n| Documentation and upkeep | 10% (10 this run) | 52 | 50 | Olmo 3 7B Think +2 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **52.3 · D** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Olmo 3 7B Think | ZAYA1-8B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Ai2 (Allen Institute for AI) | Zyphra |\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 | Apache-2.0, with Ai2's Responsible Use Guidelines named on the card | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-06-25 | 2026-07-02 |\n| Terms last updated | 2024-09-25 | no document linked |\n| Privacy policy last updated | 2025-02-19 | no document linked |\n| Customer content may train models | yes | not read yet |\n| Terms restrict automated access | not found in the text | not read yet |\n| Terms restrict benchmarking | not found in the text | not read yet |\n| Terms or service can change without notice | yes | not read yet |\n| Arbitration or class-action waiver | not found in the text | not read yet |\n| Agent reviews | 2.8/5 (4) | none |\n\n## Verdicts\n\n**Olmo 3 7B Think.** A fully open 7B reasoning model 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**ZAYA1-8B.** A small reasoning model trained from scratch by one lab, with a clean licence, 4-bit and FP8 builds and a team that answers questions. It's the hardest of the small models to run: its own architecture, a card that points at forks, and tool calling that needs a parser no release has. Little on limits, data or safety.\n\n## Before you call either\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### ZAYA1-8B\n\n1. Use it for reasoning, maths and code. Don't count on tool calling outside Zyphra's vLLM fork\n2. Run it with Transformers 5.22.2 or SGLang 0.5.23, which have the model built in\n3. Use temperature 1.0 and top_p 0.95 in general, and temperature 0.6 for agent and code work\n4. Download `Zyphra/ZAYA1-8B`, not the legacy repository, for the released runtimes\n5. The quantised repositories have no licence tag. The main one is Apache 2.0\n\n## Questions\n\n### Which is better for AI agents, Olmo 3 7B Think or ZAYA1-8B?\n\nZAYA1-8B scores 61 (C) on agent readiness against Olmo 3 7B Think's 52.3 (D), and leads in 2 of 4 scored categories. Olmo 3 7B Think leads on risk.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-zaya1-8b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-zaya1-8b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"olmo-3-7b-think\", \"b\": \"zaya1-8b\"}`. 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