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    "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)",
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    "generatedAt": "2026-10-21",
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    "slug": "gemma-4-12b-it",
    "name": "Gemma 4 12B IT",
    "vendor": "Google DeepMind",
    "vendorUrl": "https://gemma.ai",
    "kind": "weights",
    "category": "open-weights",
    "summary": "Gemma 4 12B IT is Google DeepMind's open-weight instruction-tuned dense model, 11.95B parameters in an encoder-free design, taking text, images, video frames and audio with a 262,144-token context, published on Hugging Face under Apache 2.0.",
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    "repo": "https://huggingface.co/google/gemma-4-12B-it",
    "license": "Apache-2.0",
    "transports": [],
    "packages": [
      {
        "registry": "huggingface",
        "name": "google/gemma-4-12B-it"
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      {
        "registry": "huggingface",
        "name": "google/gemma-4-12B-it-qat-q4_0-gguf"
      },
      {
        "registry": "huggingface",
        "name": "google/gemma-4-12B-it-qat-w4a16-ct"
      },
      {
        "registry": "ollama",
        "name": "gemma4:12b"
      }
    ],
    "auth": "none",
    "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository and Google's QAT repositories are not gated (checked 2026-10-21).",
    "pricing": "free",
    "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. No hosted version, since the Gemini API serves only the 26B A4B and 31B sizes and Hugging Face lists no inference provider for it. Running it yourself costs the hardware, 26.7 GB at BF16, 13.4 GB at SFP8 and 6.7 GB at Q4_0 to load the weights per Google (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://gemma.ai/models/gemma-4/",
    "llmsTxt": "https://gemma.ai/llms.txt",
    "capabilities": [
      "model.open-weights"
    ],
    "tags": [
      "open-weights",
      "model",
      "dense",
      "multimodal",
      "audio",
      "reasoning",
      "tool-calling",
      "apache-2.0",
      "safetensors",
      "gguf",
      "qat",
      "self-hosted"
    ],
    "lastRelease": "2026-07-20",
    "graded": true,
    "anchor": {
      "graded": true,
      "score": 71.3,
      "grade": "BB",
      "agentReady": true,
      "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": 3,
      "methodology": "0.6",
      "run": "2026-10-01",
      "scores": {
        "capability": 50,
        "interface": 85,
        "reach": 95,
        "risk": 70,
        "upkeep": 75
      },
      "pending": [
        "performance",
        "tasks"
      ],
      "breakdown": [
        {
          "key": "capability",
          "name": "Capability",
          "weight": 35,
          "effectiveWeight": 35,
          "score": 50,
          "points": 17.5,
          "reason": "From 8 independent benchmark results in 4 areas, each scored as its share of the way from the benchmark's floor to the best result any model has on the same leaderboard. By area, Instruction following 89, Long context 72, Reasoning and knowledge 40, Tool calling and agent tasks 32. Publisher-submitted results count at half weight, and numbers that appear only on the publisher's card don't count.",
          "checked": "2026-10-21"
        },
        {
          "key": "reach",
          "name": "Reach",
          "weight": 25,
          "effectiveWeight": 25,
          "score": 95,
          "points": 23.75,
          "reason": "Memory 30, Google's own 4-bit QAT GGUF with its projector is 7.15 GB, which with a fifth on top is 8.6 GB and fits in 16 GB or less. Runtimes 25, released support in Transformers, vLLM, SGLang, llama.cpp, Ollama and LM Studio, six of six, all for the separate gemma4_unified architecture. Builds 15, Google publishes a Q4_0 GGUF and a w4a16 build, read as two kinds as for the 31B. Terms 15, plain Apache 2.0 with nothing added. Download 10, no account or gate. Hosted 0, the Gemini API serves only the two largest sizes and no inference provider lists this one.",
          "checked": "2026-10-21"
        },
        {
          "key": "risk",
          "name": "Risk",
          "weight": 20,
          "effectiveWeight": 20,
          "score": 70,
          "points": 14,
          "reason": "File safety 25, safetensors and GGUF only, with nothing from the repository run on load. Provenance 15, the files sit in Google's own organisation and every file has a checksum. Safety evaluation 0, the card says testing showed minimal policy violations but gives no figures. Agent guidance 10, the card names the harm categories its safety training covers and asks for content-safety safeguards, and the tool guide says to validate calls, with no prompt-injection guidance. Licence risk 15, Apache 2.0 with no added policy, no threshold and a working link. Security programme 5, Google's security.txt and reward programme give a route to report a flaw, but no public Gemma advisories were found.",
          "checked": "2026-10-21"
        },
        {
          "key": "interface",
          "name": "Agent interface",
          "weight": 10,
          "effectiveWeight": 10,
          "score": 85,
          "points": 8.5,
          "reason": "Chat template 20, a Jinja file in the repository. Tool-calling format 25, Google documents how tools are declared and how calls come back, and ships a response schema for Transformers' parser. Trained tool calling 20, several calls in one turn. Structured output 0, nothing documents how to ask the weights for JSON or a schema. Reasoning control 10, thinking is off by default, turned on per request, and returned in a thought channel. Context 10, 262,144 tokens native.",
          "checked": "2026-10-21"
        },
        {
          "key": "upkeep",
          "name": "Documentation and upkeep",
          "weight": 10,
          "effectiveWeight": 10,
          "score": 75,
          "points": 7.5,
          "reason": "Model card 20, all seven items are there. Training data 10, a general description by type with a January 2025 cut-off and the filtering, but no sources, mix or sizes. Last change 10, the files last changed on 20 July 2026, 93 days ago, and Google's JAX library has no 12B code to count. Responsiveness 20, Google replied to 18 of 34 questions and reports, the last on 2026-07-31. Version policy 10, earlier Gemma generations keep their own repositories and gemma.ai has a dated releases page. File health 5, the files agree with the card but a report about them waits without a reply.",
          "checked": "2026-10-21"
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      ],
      "assessment": {
        "date": "2026-10-21",
        "basis": "public evidence",
        "confidence": "high",
        "notes": {
          "capability": "From 8 independent benchmark results in 4 areas, each scored as its share of the way from the benchmark's floor to the best result any model has on the same leaderboard. By area, Instruction following 89, Long context 72, Reasoning and knowledge 40, Tool calling and agent tasks 32. Publisher-submitted results count at half weight, and numbers that appear only on the publisher's card don't count.",
          "interface": "Chat template 20, a Jinja file in the repository. Tool-calling format 25, Google documents how tools are declared and how calls come back, and ships a response schema for Transformers' parser. Trained tool calling 20, several calls in one turn. Structured output 0, nothing documents how to ask the weights for JSON or a schema. Reasoning control 10, thinking is off by default, turned on per request, and returned in a thought channel. Context 10, 262,144 tokens native.",
          "reach": "Memory 30, Google's own 4-bit QAT GGUF with its projector is 7.15 GB, which with a fifth on top is 8.6 GB and fits in 16 GB or less. Runtimes 25, released support in Transformers, vLLM, SGLang, llama.cpp, Ollama and LM Studio, six of six, all for the separate gemma4_unified architecture. Builds 15, Google publishes a Q4_0 GGUF and a w4a16 build, read as two kinds as for the 31B. Terms 15, plain Apache 2.0 with nothing added. Download 10, no account or gate. Hosted 0, the Gemini API serves only the two largest sizes and no inference provider lists this one.",
          "risk": "File safety 25, safetensors and GGUF only, with nothing from the repository run on load. Provenance 15, the files sit in Google's own organisation and every file has a checksum. Safety evaluation 0, the card says testing showed minimal policy violations but gives no figures. Agent guidance 10, the card names the harm categories its safety training covers and asks for content-safety safeguards, and the tool guide says to validate calls, with no prompt-injection guidance. Licence risk 15, Apache 2.0 with no added policy, no threshold and a working link. Security programme 5, Google's security.txt and reward programme give a route to report a flaw, but no public Gemma advisories were found.",
          "upkeep": "Model card 20, all seven items are there. Training data 10, a general description by type with a January 2025 cut-off and the filtering, but no sources, mix or sizes. Last change 10, the files last changed on 20 July 2026, 93 days ago, and Google's JAX library has no 12B code to count. Responsiveness 20, Google replied to 18 of 34 questions and reports, the last on 2026-07-31. Version policy 10, earlier Gemma generations keep their own repositories and gemma.ai has a dated releases page. File health 5, the files agree with the card but a report about them waits without a reply."
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        "sources": [
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            "what": "model card",
            "url": "https://huggingface.co/google/gemma-4-12B-it",
            "seen": "2026-10-21"
          },
          {
            "what": "repository files and checksums",
            "url": "https://huggingface.co/api/models/google/gemma-4-12B-it?blobs=true",
            "seen": "2026-10-21"
          },
          {
            "what": "inference providers (none), gating, downloads and last modified",
            "url": "https://huggingface.co/api/models/google/gemma-4-12B-it?expand[]=inferenceProviderMapping",
            "seen": "2026-10-21"
          },
          {
            "what": "commit history",
            "url": "https://huggingface.co/api/models/google/gemma-4-12B-it/commits/main",
            "seen": "2026-10-21"
          },
          {
            "what": "Google's Gemma 4 repositories",
            "url": "https://huggingface.co/api/models?author=google\u0026search=gemma-4-",
            "seen": "2026-10-21"
          },
          {
            "what": "Google's Q4_0 QAT GGUF build and its file sizes",
            "url": "https://huggingface.co/api/models/google/gemma-4-12B-it-qat-q4_0-gguf/tree/main?recursive=true",
            "seen": "2026-10-21"
          },
          {
            "what": "chat template",
            "url": "https://huggingface.co/google/gemma-4-12B-it/raw/main/chat_template.jinja",
            "seen": "2026-10-21"
          },
          {
            "what": "config with context length",
            "url": "https://huggingface.co/google/gemma-4-12B-it/raw/main/config.json",
            "seen": "2026-10-21"
          },
          {
            "what": "discussions, replies counted by author and org flag only",
            "url": "https://huggingface.co/google/gemma-4-12B-it/discussions",
            "seen": "2026-10-21"
          },
          {
            "what": "Apache 2.0 page the card's licence link redirects to",
            "url": "https://ai.google.dev/gemma/apache_2",
            "seen": "2026-10-21"
          },
          {
            "what": "Gemma 4 overview with memory needs and QAT routing",
            "url": "https://gemma.ai/models/gemma-4/",
            "seen": "2026-10-21"
          },
          {
            "what": "QAT builds and availability by size",
            "url": "https://gemma.ai/get-started/qat/",
            "seen": "2026-10-21"
          },
          {
            "what": "tool-calling guide",
            "url": "https://gemma.ai/get-started/capabilities/function-calling/",
            "seen": "2026-10-21"
          },
          {
            "what": "thinking guide",
            "url": "https://gemma.ai/get-started/capabilities/thinking/",
            "seen": "2026-10-21"
          },
          {
            "what": "Gemini API hosting only the 26B A4B and 31B",
            "url": "https://gemma.ai/deployment/gemini-api/",
            "seen": "2026-10-21"
          },
          {
            "what": "dated releases page",
            "url": "https://gemma.ai/models/releases/",
            "seen": "2026-10-21"
          },
          {
            "what": "OpenRouter model list, no entry for this size",
            "url": "https://openrouter.ai/api/v1/models",
            "seen": "2026-10-21"
          },
          {
            "what": "Ollama library entry",
            "url": "https://ollama.com/library/gemma4:12b",
            "seen": "2026-10-21"
          },
          {
            "what": "LM Studio catalogue entry",
            "url": "https://lmstudio.ai/models/google/gemma-4-12b",
            "seen": "2026-10-21"
          },
          {
            "what": "vLLM 0.32.0 model registry",
            "url": "https://raw.githubusercontent.com/vllm-project/vllm/v0.32.0/vllm/model_executor/models/registry.py",
            "seen": "2026-10-21"
          },
          {
            "what": "SGLang 0.5.22 model code",
            "url": "https://raw.githubusercontent.com/sgl-project/sglang/v0.5.22/python/sglang/srt/models/gemma4_unified.py",
            "seen": "2026-10-21"
          },
          {
            "what": "llama.cpp multimodal projectors",
            "url": "https://raw.githubusercontent.com/ggml-org/llama.cpp/v0.7.0/tools/mtmd/clip.cpp",
            "seen": "2026-10-21"
          },
          {
            "what": "Transformers model code",
            "url": "https://raw.githubusercontent.com/huggingface/transformers/v5.10.0/src/transformers/models/gemma4_unified/modeling_gemma4_unified.py",
            "seen": "2026-10-21"
          },
          {
            "what": "Google's JAX library history (git clone without blobs)",
            "url": "https://github.com/google-deepmind/gemma",
            "seen": "2026-10-21"
          },
          {
            "what": "Google's security.txt",
            "url": "https://www.google.com/.well-known/security.txt",
            "seen": "2026-10-21"
          },
          {
            "what": "Independent benchmark result used for Capability",
            "url": "https://artificialanalysis.ai/models/gemma-4-12b",
            "seen": "2026-10-21"
          }
        ],
        "openQuestions": [
          "Couldn't check whether Google's AI vulnerability reward programme covers Gemma open weights, or whether Google handles Gemma advisories in public; scored as absent",
          "Hosted is scored 0 from Hugging Face's provider list, OpenRouter's model list and Google's Gemini API page. Other providers' own lists weren't searched, so a provider serving it elsewhere would lift the line to 5 if there are two",
          "builds read as two kinds because the checklist lists GGUF apart from 4-bit, as for gemma-4-31b-it, though both of Google's main builds are 4-bit. A stricter reading gives 10",
          "The Gemma Prohibited Use Policy is listed in gemma.ai's navigation but not applied by the card or licence page; if it were applied, terms would fall to 10 and licence risk to 10",
          "Responsiveness is 18 of 34, just over half, and none of the three discussions opened since 31 July has a Google reply; a stricter reading of most gives 10 and Documentation and upkeep 65"
        ]
      },
      "negative": 0,
      "verdict": "A mid-size cousin for agent work with tools, optional thinking and image and audio input, under Apache 2.0. Google's 4-bit build needs under 9 GB with working space, so it runs on a 12 GB GPU or any recent Mac in all the common runtimes. The main risks are no published safety results and no documented JSON output.",
      "bestFor": "Agents on a 12 GB or larger GPU or Mac that want a permissively licensed tool-calling model with images, audio and long context",
      "strengths": [
        "Plain Apache 2.0, no account or gate, safetensors and GGUF only with a checksum on every file",
        "Google's own 4-bit QAT GGUF needs about 8.6 GB with working space",
        "Released support in vLLM, SGLang, llama.cpp, Ollama, LM Studio and Transformers",
        "Tool declaration and call format documented by Google, with parallel calls and a shipped response parser",
        "262,144 tokens of native context and thinking that turns on or off per request",
        "Takes audio as well as images and video frames"
      ],
      "weaknesses": [
        "No safety evaluation figures published",
        "No documented way to ask for JSON or schema output",
        "No hosted version, since the Gemini API serves only the two largest sizes",
        "Training data described only by type and cut-off",
        "Files unchanged since 20 July 2026, and a startup crash report waits without a reply",
        "A newer, separate architecture (gemma4_unified) that needs Transformers 5.10.0 or later"
      ],
      "agentNotes": [
        "On the reference machine run `llama-server -hf google/gemma-4-12B-it-qat-q4_0-gguf --hf-file gemma-4-12b-it-qat-q4_0.gguf --jinja -c 131072`, and add `--mmproj` with mmproj-gemma-4-12b-it-qat-q4_0.gguf for images and audio",
        "With Ollama run `ollama run gemma4:12b` and raise num_ctx or OLLAMA_CONTEXT_LENGTH, since the default context is small and agents want at least 64K",
        "In vLLM or SGLang pass `--tool-call-parser gemma4 --reasoning-parser gemma4` (vLLM also `--enable-auto-tool-choice`), or tool calls come back as text; Google's w4a16 build is the 4-bit route there",
        "Thinking is off by default; pass enable_thinking=True or start the system prompt with \u003c|think|\u003e, and drop earlier turns' thinking from history except on tool-call turns",
        "Put images before the text and audio after it, keep audio to 30 seconds and video to 60 frames, and validate tool names and arguments before running them",
        "Transformers needs 5.10.0 or later for gemma4_unified, and mlx-lm has no gemma4_unified code, so on a Mac use mlx-vlm, LM Studio or Ollama"
      ],
      "metrics": {
        "kind": "local",
        "measured": false
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      "reviewCount": 4,
      "avgRating": 3.8,
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          "basis": "public evidence",
          "confidence": "high",
          "grade": "BB",
          "methodology": "0.6",
          "pending": [
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            "tasks"
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          "run": "2026-10-01",
          "runLabel": "October 2026 research run",
          "score": 71.3
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      "editorialScores": {
        "capability": 50,
        "interface": 85,
        "reach": 95,
        "risk": 70,
        "upkeep": 75
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      "provenanceScore": 68,
      "checked": {
        "categories": {
          "capability": "2026-10-21",
          "interface": "2026-10-21",
          "reach": "2026-10-21",
          "risk": "2026-10-21",
          "upkeep": "2026-10-21"
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        "last": "2026-10-21",
        "oldest": "2026-10-21",
        "stale": false,
        "staleAfterDays": 90
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      "scoreHistory": [
        {
          "date": "2026-10-21",
          "grade": "BB",
          "kind": "listed",
          "method": "0.6",
          "score": 71.3
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    },
    "connect": {
      "install": "ollama run gemma4:12b\n# or, with llama.cpp and Google's QAT build:\nllama-server -hf google/gemma-4-12B-it-qat-q4_0-gguf --hf-file gemma-4-12b-it-qat-q4_0.gguf --jinja -c 131072",
      "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"gemma4:12b\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"options\": {\"num_ctx\": 65536}}'"
    },
    "letme": {
      "capability": "https://letme.dev/model.open-weights",
      "tool": "https://letme.dev/gemma-4-12b-it"
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        "themes": {
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          "requests": [
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        "task": "desk review: operations",
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        "observed": null,
        "date": "2026-10-21",
        "basis": "desk",
        "basisNote": "Desk review, written from public documentation, pricing, terms, source and status history on 21 October 2026. No calls made.",
        "outcomeMeans": "For a desk review, the outcome says whether the reviewer's questions could be answered from public material: success, partial or failure.",
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                "Files unchanged since 20 July"
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            "Ollama"
          ],
          "note": "Q4_K_M weights (7.4 GB) with a BF16 projector (175 MB) and a Q8_0 draft model (465 MB) (digest 6114515d63c1), the llama.cpp variant. gemma4:12b-it-qat (7.2 GB) is Ollama's copy of Google's Q4_0 QAT build"
        },
        {
          "name": "lmstudio google/gemma-4-12b",
          "url": "https://lmstudio.ai/models/google/gemma-4-12b",
          "who": "lmstudio",
          "precision": "q4_k_m",
          "sizeGB": 7.4,
          "memoryGB": 12,
          "format": "gguf",
          "runsOn": [
            "LM Studio"
          ],
          "note": "LM Studio's catalogue build, from lmstudio-community/gemma-4-12B-it-GGUF, with MLX builds at 4 to 8 bits beside it. Size as the catalogue shows it, and Q4_K_M is inferred from that repository's files rather than stated by LM Studio"
        },
        {
          "name": "gemma-4-12B-it-qat-w4a16-ct",
          "url": "https://huggingface.co/google/gemma-4-12B-it-qat-w4a16-ct",
          "who": "publisher",
          "precision": "w4a16",
          "sizeGB": 10.3,
          "memoryGB": 16,
          "format": "safetensors",
          "note": "Quantisation-aware trained, 4-bit weights with 16-bit activations in compressed-tensors format, which Google routes to vLLM and SGLang"
        },
        {
          "name": "gemma-4-12B-it",
          "url": "https://huggingface.co/google/gemma-4-12B-it",
          "who": "publisher",
          "precision": "bf16",
          "sizeGB": 23.95,
          "memoryGB": 32,
          "format": "safetensors",
          "runsOn": [
            "vLLM (ROCm)",
            "SGLang (ROCm)"
          ]
        }
      ],
      "run": "llama-server -hf google/gemma-4-12B-it-qat-q4_0-gguf --hf-file gemma-4-12b-it-qat-q4_0.gguf --jinja -c 131072",
      "runBuild": "gemma-4-12b-it-qat-q4_0",
      "checked": "2026-10-21",
      "minMemoryGB": 12
    },
    "family": {
      "lab": "Google (Gemma)",
      "family": "Gemma 4",
      "url": "https://www.anchorterminal.com/open-weights/#google",
      "others": [
        {
          "name": "gemma-4-26B-A4B",
          "url": "https://huggingface.co/google/gemma-4-26B-A4B",
          "params": "25.2B total, 3.8B active"
        },
        {
          "name": "gemma-4-26B-A4B-it",
          "url": "https://huggingface.co/google/gemma-4-26B-A4B-it",
          "params": "25.2B total, 3.8B active",
          "listing": "https://www.anchorterminal.com/tools/gemma-4-26b-a4b-it"
        },
        {
          "name": "gemma-4-31B",
          "url": "https://huggingface.co/google/gemma-4-31B",
          "params": "30.7B"
        },
        {
          "name": "gemma-4-31B-it",
          "url": "https://huggingface.co/google/gemma-4-31B-it",
          "params": "30.7B",
          "listing": "https://www.anchorterminal.com/tools/gemma-4-31b-it"
        },
        {
          "name": "gemma-4-E2B",
          "url": "https://huggingface.co/google/gemma-4-E2B",
          "params": "2.3B effective (5.1B with embeddings)"
        },
        {
          "name": "gemma-4-E2B-it",
          "url": "https://huggingface.co/google/gemma-4-E2B-it",
          "params": "2.3B effective (5.1B with embeddings)",
          "listing": "https://www.anchorterminal.com/tools/gemma-4-e2b-it"
        },
        {
          "name": "gemma-4-E4B",
          "url": "https://huggingface.co/google/gemma-4-E4B",
          "params": "4.5B effective (8B with embeddings)"
        },
        {
          "name": "gemma-4-E4B-it",
          "url": "https://huggingface.co/google/gemma-4-E4B-it",
          "params": "4.5B effective (8B with embeddings)",
          "listing": "https://www.anchorterminal.com/tools/gemma-4-e4b-it"
        },
        {
          "name": "gemma-4-26B-A4B-it-assistant",
          "url": "https://huggingface.co/google/gemma-4-26B-A4B-it-assistant",
          "params": "420M (file metadata on Hugging Face; drafter)"
        },
        {
          "name": "gemma-4-31B-it-assistant",
          "url": "https://huggingface.co/google/gemma-4-31B-it-assistant",
          "params": "470M (file metadata on Hugging Face; drafter)"
        },
        {
          "name": "gemma-4-E2B-it-assistant",
          "url": "https://huggingface.co/google/gemma-4-E2B-it-assistant",
          "params": "78M (file metadata on Hugging Face; drafter)"
        },
        {
          "name": "gemma-4-E4B-it-assistant",
          "url": "https://huggingface.co/google/gemma-4-E4B-it-assistant",
          "params": "79M (file metadata on Hugging Face; drafter)"
        },
        {
          "name": "gemma-4-12B",
          "url": "https://huggingface.co/google/gemma-4-12B",
          "params": "11.95B"
        },
        {
          "name": "gemma-4-12B-it-assistant",
          "url": "https://huggingface.co/google/gemma-4-12B-it-assistant",
          "params": "423M (file metadata on Hugging Face; drafter)"
        },
        {
          "name": "diffusiongemma-26B-A4B-it",
          "url": "https://huggingface.co/google/diffusiongemma-26B-A4B-it",
          "params": "25.2B total, 3.8B active",
          "listing": "https://www.anchorterminal.com/tools/diffusiongemma-26b-a4b-it"
        },
        {
          "name": "embeddinggemma-2",
          "url": "https://huggingface.co/google/embeddinggemma-2",
          "params": "740M"
        }
      ],
      "olderCount": 171,
      "unrestrictedCopies": 5
    },
    "notable": [
      "1,692,786 downloads in the last 30 days and 12,808,433 in all on Hugging Face, with 1,675 likes, on 21 October 2026. Google's Q4_0 QAT GGUF repository had 848,943 and its w4a16 build 858,418 in 30 days (https://huggingface.co/api/models/google/gemma-4-12B-it)",
      "Ollama's library has it as gemma4:12b, and the gemma4 family page showed 27.4M downloads on 21 October 2026 (https://ollama.com/library/gemma4)",
      "The card's table gives 77.2% on MMLU Pro, 72.0% on LiveCodeBench v6, 69.0% on Tau2 (average over 3), 43.4% on MRCR v2 8-needle at 128K, 78.8% on GPQA Diamond. These are Google's numbers, not our measurement (https://huggingface.co/google/gemma-4-12B-it)",
      "Google publishes a draft model for speculative decoding, google/gemma-4-12B-it-assistant, and Ollama's gemma4:12b bundles one (https://gemma.ai/models/gemma-4/)",
      "Google's Gemini API hosts only the 26B A4B and 31B sizes; its page says the smaller sizes are not hosted (https://gemma.ai/deployment/gemini-api/)"
    ],
    "area": "models",
    "details": [
      {
        "label": "Surface graded",
        "value": "The open weights at huggingface.co/google/gemma-4-12B-it and Google's QAT builds, read from the model card, the files and their metadata, the chat template and tokenizer config, Google's Gemma documentation at gemma.ai and the runtimes' own code on 21 October 2026. Nothing was downloaded or run. There's no hosted version to grade"
      },
      {
        "label": "Model",
        "value": "A dense decoder of 11.95B parameters, 48 layers, sliding-window attention of 1,024 tokens interleaved with global layers 5 to 1. Google calls it Unified because it has no vision or audio encoder, and image patches and raw audio go through light linear projections into the decoder (Gemma4UnifiedForConditionalGeneration, model type gemma4_unified). Text, images, video as frames and audio up to 30 seconds in, text out. 11,959,730,224 parameters in the files per Hugging Face's metadata"
      },
      {
        "label": "Files",
        "value": "One safetensors file in BF16 (23.95 GB with the tokenizer) with chat_template.jinja, tokenizer_config.json carrying a response schema and template for parsing, and generation_config.json. No pickle files. Hugging Face lists a SHA-256 for both LFS files and a git hash for every file. Google's QAT builds sit in their own repositories (Q4_0 GGUF, w4a16 compressed tensors, and an unquantised QAT checkpoint for conversion)"
      },
      {
        "label": "Licence",
        "value": "Apache 2.0, named in the card's metadata and linked to Google's Gemma 4 licence page, which redirects to Google's Apache 2.0 page (last updated 1 April 2026). The repository has no LICENSE file. gemma.ai still lists the Gemma Prohibited Use Policy under Legal, which neither the card nor the licence page applies to Gemma 4"
      },
      {
        "label": "Runtimes",
        "value": "Model code in Transformers (gemma4_unified, from 5.10.0), vLLM 0.32.0 (gemma4_unified, with the gemma4 tool and reasoning parsers), SGLang 0.5.22 (gemma4_unified), mlx-vlm (gemma4_unified), llama.cpp (the gemma4 architecture with the encoder-free GEMMA4UV and GEMMA4UA projectors in its multimodal code), gemma4:12b in Ollama's library and google/gemma-4-12b in LM Studio's catalogue. Google's JAX library has no 12B class"
      },
      {
        "label": "Context",
        "value": "262,144 tokens native (max_position_embeddings in config.json, 256K on the card, corrected from a smaller value on 4 June 2026). Ollama's default context is smaller, so raise num_ctx"
      },
      {
        "label": "Tools and reasoning",
        "value": "Tools are declared in `\u003c|tool\u003edeclaration:...\u003ctool|\u003e` blocks and calls come back as `\u003c|tool_call\u003ecall:name{...}\u003ctool_call|\u003e`, documented on gemma.ai with a full call-and-response example that uses gemma-4-E2B-it. Transformers parses them with `processor.parse_response` and the response schema in tokenizer_config.json, and vLLM and SGLang ship a gemma4 tool parser. Thinking is off by default, `enable_thinking=True` or `\u003c|think|\u003e` at the start of the system prompt turns it on, and reasoning comes back in `\u003c|channel\u003ethought ... \u003cchannel|\u003e`. The template adds an empty thought block when thinking is off, to stop ghost thought channels. No thinking budget is documented"
      },
      {
        "label": "Hardware",
        "value": "Google states 26.7 GB at BF16, 13.4 GB at SFP8 and 6.7 GB at Q4_0 to load the weights, with 20% overhead and the KV cache on top"
      },
      {
        "label": "Training data",
        "value": "A general description on the card, web documents in over 140 languages, code, mathematics, images and audio, with a January 2025 cut-off and CSAM, sensitive-data and quality filtering. No mix, sizes or dataset list"
      }
    ],
    "provenance": {
      "legalEntity": "Google LLC (RDAP registrant of gemma.ai as recorded for the first batch's Gemma 4 listings; the card names Google DeepMind as author)",
      "domain": "gemma.ai",
      "domainRegistered": "2017-12-16",
      "endpointOnVendorDomain": null,
      "terms": "",
      "privacy": "",
      "statusPage": "",
      "changelog": "https://gemma.ai/models/releases/",
      "securityTxt": "none",
      "checked": "2026-10-21",
      "notes": [
        "The registrant and registration date are carried from the gemma-4-26b-a4b-it and gemma-4-31b-it facts read earlier on 21 October 2026, since rdap.org rate-limited our request this time and wasn't retried.",
        "Nothing is hosted under this listing, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
        "gemma.ai keeps a dated releases page for the Gemma family (this size on 3 June 2026). The Hugging Face commit history says what each change fixed.",
        "gemma.ai/.well-known/security.txt answers 404. Google's company-wide security.txt at google.com points to its vulnerability reward programme."
      ],
      "score": 68,
      "checks": [
        {
          "check": "Legal entity named",
          "value": "Google LLC (RDAP registrant of gemma.ai as recorded for the first batch's Gemma 4 listings; the card names Google DeepMind as author)",
          "points": 20,
          "max": 20,
          "state": "ok"
        },
        {
          "check": "Domain age",
          "value": "gemma.ai, registered 2017-12-16 (8 years)",
          "points": 11,
          "max": 15,
          "state": "part"
        },
        {
          "check": "Endpoint on the vendor's domain",
          "value": "no hosted endpoint",
          "points": 0,
          "max": 0,
          "state": "na"
        },
        {
          "check": "Terms of service",
          "value": "nothing hosted, so the Apache-2.0 licence stands in",
          "points": 10,
          "max": 10,
          "state": "ok"
        },
        {
          "check": "Privacy policy",
          "value": "nothing hosted, not scored",
          "points": 0,
          "max": 0,
          "state": "na"
        },
        {
          "check": "Status page",
          "value": "not found",
          "points": 0,
          "max": 10,
          "state": "no"
        },
        {
          "check": "Changelog",
          "value": "published",
          "points": 10,
          "max": 10,
          "state": "ok"
        },
        {
          "check": "security.txt",
          "value": "not found",
          "points": 0,
          "max": 10,
          "state": "no"
        }
      ]
    },
    "pageJsonUrl": "https://www.anchorterminal.com/tools/gemma-4-12b-it.json"
  }
}
