{
  "data": {
    "a": {
      "slug": "bigbang-v1",
      "name": "BigBang-v1",
      "vendor": "The Endless Frontier (endless-frontier)",
      "vendorUrl": "https://huggingface.co/endless-frontier",
      "kind": "weights",
      "category": "open-weights",
      "summary": "BigBang-v1 is The Endless Frontier's general-purpose fine-tune of Qwen3.6-35B-A3B (35B mixture of experts, 3B active), post-trained on about 10,000 synthetic research and technical problems, published on Hugging Face in BF16 under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/bigbang-v1",
      "markdownUrl": "https://www.anchorterminal.com/tools/bigbang-v1.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/bigbang-v1.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/bigbang-v1.json",
      "dns": "bigbang-v1.grade.anchorterminal.com",
      "repo": "https://huggingface.co/endless-frontier/BigBang-v1",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "endless-frontier/BigBang-v1"
        }
      ],
      "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 same licence as the Qwen3.6-35B-A3B base. Running it yourself costs the hardware, 71.9 GB for the BF16 files, the only build from the publisher (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/endless-frontier/BigBang-v1",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "reasoning",
        "tool-calling",
        "derivative",
        "apache-2.0",
        "safetensors",
        "self-hosted"
      ],
      "lastRelease": "2026-08-06",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 56.3,
        "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": 1524,
        "categoryRank": 88,
        "methodology": "0.8",
        "run": "2026-10-01",
        "scores": {
          "interface": 60,
          "reach": 60,
          "risk": 55,
          "upkeep": 46
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-04"
        },
        "negative": 0,
        "verdict": "A Qwen3.6-35B-A3B fine-tuned on synthetic research problems, under plain Apache 2.0, for search, science and coding work. The publisher ships BF16 only, about 86 GB to run, and has no report, safety results or replies to questions, so smaller builds and support come from others.",
        "bestFor": "Agents with 96 GB or more that want an Apache 2.0 mixture-of-experts model tuned for research, search and coding, and can do without publisher support.",
        "strengths": [
          "Apache 2.0 like its base, not gated",
          "Same architecture, config and template as Qwen3.6-35B-A3B, so released llama.cpp, Ollama 0.40.14, vLLM, SGLang and Transformers run it",
          "Safetensors only with a SHA-256 for every weight file",
          "262,144 tokens of context and several tool calls a turn"
        ],
        "weaknesses": [
          "BF16 is the only build from the publisher, needing about 86 GB",
          "No report, safety results, agent guidance or security contact",
          "Training data described only as about 10,000 synthetic examples",
          "No reply from the publisher to any of 7 discussions, and no change to the files or card since 6 August 2026",
          "Every benchmark figure is the publisher's own, with no set-up stated"
        ],
        "agentNotes": [
          "On the reference machine use `vllm serve endless-frontier/BigBang-v1 --max-model-len 131072 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`",
          "The card says to keep at least 128K of context so its thinking isn't cut short",
          "Thinking control isn't documented, try the base template's `enable_thinking` false in chat_template_kwargs and check the output",
          "For Ollama or llama.cpp you'll need someone else's GGUF; the publisher ships BF16 safetensors only",
          "Validate JSON output yourself or use the runtime's guided decoding"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.8",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 56.3
          }
        ],
        "editorialScores": {
          "interface": 60,
          "reach": 60,
          "risk": 55,
          "upkeep": 46
        },
        "provenanceScore": 19,
        "checked": {
          "categories": {
            "interface": "2026-11-04",
            "reach": "2026-11-04",
            "risk": "2026-11-04",
            "upkeep": "2026-11-04"
          },
          "last": "2026-11-04",
          "lastMoved": "2026-11-04",
          "oldest": "2026-11-04",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "vllm serve endless-frontier/BigBang-v1 --max-model-len 262144 --reasoning-parser qwen3 \\\n  --enable-auto-tool-choice --tool-call-parser qwen3_coder\n# or, with llama.cpp and bartowski's GGUF, a third party's conversion:\nllama-server -hf bartowski/endless-frontier_BigBang-v1-GGUF:Q4_K_M --jinja",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\"model\": \"endless-frontier/BigBang-v1\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/bigbang-v1"
      },
      "weights": {
        "trainedBy": "The Endless Frontier (endless-frontier)",
        "builtOn": "Qwen/Qwen3.6-35B-A3B (Apache 2.0), declared in the card's metadata (base_model) and text. Identical config.json, parameter count and chat template, and the repository's LICENSE is Qwen's Apache 2.0 file. BigBang is also Apache 2.0",
        "params": "35B (3B active)",
        "active": "3B",
        "context": 262144,
        "goodFor": "General-purpose mixture-of-experts model tuned for scientific research, search and coding tasks with thinking on, text and images in.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "bartowski endless-frontier_BigBang-v1-GGUF (Q4_K_M)",
            "url": "https://huggingface.co/bartowski/endless-frontier_BigBang-v1-GGUF",
            "who": "bartowski",
            "precision": "q4_k_m",
            "sizeGB": 22.76,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From bartowski, a third party's conversion and not Endless Frontier's. 21.86 GB of Q4_K_M weights plus the 0.90 GB F16 projector, from the Hub's model information on 10 November 2026. Recorded after the last grading, so Reach doesn't count it"
          },
          {
            "name": "bartowski endless-frontier_BigBang-v1-GGUF (Q8_0)",
            "url": "https://huggingface.co/bartowski/endless-frontier_BigBang-v1-GGUF",
            "who": "bartowski",
            "precision": "q8_0",
            "sizeGB": 38.71,
            "memoryGB": 48,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From bartowski, a third party's conversion and not Endless Frontier's. 37.81 GB of Q8_0 weights plus the 0.90 GB F16 projector, from the Hub's model information on 10 November 2026. Recorded after the last grading, so Reach doesn't count it"
          },
          {
            "name": "BigBang-v1",
            "url": "https://huggingface.co/endless-frontier/BigBang-v1",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 71.9,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)",
              "Transformers"
            ]
          }
        ],
        "run": "vllm serve endless-frontier/BigBang-v1 --max-model-len 131072 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder",
        "runBuild": "BigBang-v1",
        "checked": "2026-11-04",
        "minMemoryGB": 32
      },
      "family": {
        "lab": "The Endless Frontier (endless-frontier)",
        "family": "BigBang",
        "url": "https://www.anchorterminal.com/open-weights/#endless-frontier",
        "olderCount": 2,
        "unrestrictedCopies": 3
      },
      "area": "models",
      "provenance": {
        "legalEntity": "",
        "domain": "",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "No legal entity, website, paper or GitHub repository is named on the card. The Hugging Face organisation endless-frontier (fullname The Endless Frontier, 17 members, three models) isn't verified.",
          "Nothing is hosted by the publisher, so the licence stands in for terms of service and no privacy policy is scored.",
          "No changelog. The commit messages are uploads and benchmark-table fixes.",
          "No security.txt, since there is no domain."
        ],
        "score": 19
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/bigbang-v1.json"
    },
    "answer": "Inkling 2 Small scores 58.8 (C) on agent readiness against BigBang-v1's 56.3 (C), and leads in 3 of 4 scored categories. BigBang-v1 leads on reach.",
    "b": {
      "slug": "inkling-2-small",
      "name": "Inkling 2 Small",
      "vendor": "Thinking Machines Lab",
      "vendorUrl": "https://thinkingmachines.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Inkling 2 Small is Thinking Machines Lab's open-weight mixture-of-experts model, 594B total and 17B active parameters, taking text and images and returning text, with adjustable thinking effort, published in NVFP4 and MXFP8 under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/inkling-2-small",
      "markdownUrl": "https://www.anchorterminal.com/tools/inkling-2-small.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/inkling-2-small.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json",
      "dns": "inkling-2-small.grade.anchorterminal.com",
      "repo": "https://huggingface.co/thinkingmachines/Inkling-2-Small",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-2-Small"
        },
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-2-Small-MXFP8"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-11-12). Thinking Machines' Model Acceptable Use Policy, linked from the card, says that downloading or using the weights binds you to it.",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0 with Thinking Machines' Model Acceptable Use Policy on top. Running it yourself costs the hardware, 393.5 GB of files for the NVFP4 checkpoint and 622.8 GB for MXFP8, which Thinking Machines puts at 500 GB and 800 GB of GPU memory. Thinking Machines' Tinker serves it as a beta serverless inference API at $0.30 per million input tokens, $0.03 cached and $1.00 output (read 2026-11-06).",
      "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 2026-11-12).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-12"
      },
      "docsUrl": "https://thinkingmachines.ai/model-card/inkling-2-small/",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "vision",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "nvfp4",
        "self-hosted",
        "new"
      ],
      "lastRelease": "2026-11-12",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 58.8,
        "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": 1524,
        "categoryRank": 78,
        "methodology": "0.8",
        "run": "2026-10-01",
        "scores": {
          "interface": 85,
          "reach": 40,
          "risk": 65,
          "upkeep": 67
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-12"
        },
        "negative": 0,
        "verdict": "Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.",
        "bestFor": "Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.",
        "strengths": [
          "Safetensors only, with a checksum on every LFS file in the publisher's own organisation",
          "Thinking effort set per request from none to xhigh, several tool calls a turn and a 1M-token context",
          "Two checkpoints from Thinking Machines, NVFP4 and MXFP8, under Apache 2.0 with no gate",
          "Thinking Machines' tml-renderers package renders prompts and parses tool calls for this model",
          "A training-content summary with sources, mix and an October 2026 collection cut-off",
          "Thinking Machines' own Tinker hosts it as beta serverless inference, and the card names seven more API providers"
        ],
        "weaknesses": [
          "The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory",
          "No released version of vLLM, SGLang, Transformers, llama.cpp or Ollama runs it on 12 November 2026",
          "Apache 2.0 comes with an acceptable use policy that binds on download and can change at any time",
          "Safety results are Thinking Machines' own, with no harness to rerun them and no prompt-injection guidance",
          "Structured output isn't documented, and the card gives no dated knowledge cut-off",
          "No independent benchmark results were read, so Capability is pending and the total is capped at 61"
        ],
        "agentNotes": [
          "No released runtime runs it yet. Serve the NVFP4 checkpoint from SGLang's dev-inkling-2-small image with the cookbook's recipe for your hardware, or from vLLM's vllm/vllm-openai:inkling-2-small image",
          "In vLLM pass `--reasoning-parser inkling --enable-auto-tool-choice --tool-call-parser inkling`. In SGLang the tool-call parser is `inkling2` and the reasoning parser `inkling`",
          "Transformers' main branch loads only thinkingmachines/Inkling-2-Small-MXFP8, the 622.8 GB checkpoint, and no release has the code yet",
          "Pass `reasoning_effort` as none, minimal, low, medium, high (the default), xhigh or max, or a number from 0 to 0.99",
          "Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens",
          "Tool call arguments must reach the template as an object, not a JSON string, or it raises an error",
          "Images should be 40 to 4096 px a side. The model takes no audio, and the template raises an error for an audio part",
          "Use guided decoding or validate JSON yourself, since structured output isn't documented",
          "Without the hardware, call it on Tinker's OpenAI-compatible endpoint with a Tinker key, at $0.30 input and $1.00 output per million tokens as read on 6 November 2026",
          "Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.8",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 58.8
          }
        ],
        "editorialScores": {
          "interface": 85,
          "reach": 40,
          "risk": 65,
          "upkeep": 67
        },
        "provenanceScore": 72,
        "checked": {
          "categories": {
            "interface": "2026-11-12",
            "reach": "2026-11-12",
            "risk": "2026-11-12",
            "upkeep": "2026-11-12"
          },
          "last": "2026-11-12",
          "lastMoved": "2026-11-12",
          "oldest": "2026-11-12",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# per SGLang's cookbook, the NVFP4 checkpoint on 4 B300 GPUs. Not in an SGLang release yet,\n# so run it inside the lmsysorg/sglang:dev-inkling-2-small image:\nSGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK=4096 sglang serve \\\n  --model-path thinkingmachines/Inkling-2-Small --tp 4 --ep 4 \\\n  --moe-a2a-backend megamoe --attention-backend fa4 --bf16-gemm-backend torch --dtype bfloat16 \\\n  --page-size 128 --grammar-backend xgrammar --enable-multimodal \\\n  --reasoning-parser inkling --tool-call-parser inkling2",
        "http": "curl http://localhost:30000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"thinkingmachines/Inkling-2-Small\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"reasoning_effort\": \"low\"\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/inkling-2-small"
      },
      "sameCompany": [
        "inkling",
        "inkling-small"
      ],
      "sameModel": [
        "tinker"
      ],
      "weights": {
        "trainedBy": "Thinking Machines Lab",
        "params": "594B",
        "active": "17B",
        "context": 1048576,
        "goodFor": "Mixture-of-experts generalist for coding, agents and tool use with images in, a 1M-token context and thinking effort set per request.",
        "runtimes": [],
        "builds": [
          {
            "name": "Inkling-2-Small",
            "url": "https://huggingface.co/thinkingmachines/Inkling-2-Small",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 393.5,
            "memoryGB": 512,
            "format": "safetensors",
            "note": "The main checkpoint, in the precision the model was trained in. Routed experts in NVFP4 for layers 0 to 39 and MXFP8 for layers 40 to 47, per SGLang's cookbook. Thinking Machines states at least 500 GB of GPU memory"
          },
          {
            "name": "Inkling-2-Small-MXFP8",
            "url": "https://huggingface.co/thinkingmachines/Inkling-2-Small-MXFP8",
            "who": "publisher",
            "precision": "mxfp8",
            "sizeGB": 622.8,
            "memoryGB": 1024,
            "format": "safetensors",
            "note": "Every routed expert in MXFP8. Thinking Machines states at least 800 GB of GPU memory and recommends the NVFP4 checkpoint. It's the only checkpoint Transformers' main branch loads"
          }
        ],
        "run": "SGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK=4096 sglang serve --model-path thinkingmachines/Inkling-2-Small --tp 4 --ep 4 --moe-a2a-backend megamoe --attention-backend fa4 --bf16-gemm-backend torch --dtype bfloat16 --page-size 128 --grammar-backend xgrammar --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling2",
        "runBuild": "Inkling-2-Small",
        "checked": "2026-11-12",
        "minMemoryGB": 512
      },
      "family": {
        "lab": "Thinking Machines Lab",
        "family": "Inkling 2",
        "url": "https://www.anchorterminal.com/open-weights/#thinking-machines"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Thinking Machines Lab, Inc. (named as provider on its model card page and in its training-content summary)",
        "domain": "thinkingmachines.ai",
        "domainRegistered": "",
        "domainNote": "Not looked up: RDAP isn't requested under the 1 November 2026 rules.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/thinkingmachines/Inkling-2-Small/commits/main",
        "securityTxt": "valid",
        "checked": "2026-11-12",
        "notes": [
          "Thinking Machines' model card page links both repositories in the thinkingmachines organisation on Hugging Face, which isn't verified by Hugging Face.",
          "Nothing is hosted for this listing, so the Apache 2.0 licence and the Model Acceptable Use Policy stand in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history, 3 commits on 12 November 2026, the upload, a library tag from a merged pull request and a card update.",
          "thinkingmachines.ai/.well-known/security.txt gives a security contact, a PGP key and an expiry in 2029, read on 12 November 2026, and the model card page links a coordinated vulnerability disclosure policy.",
          "Thinking Machines' terms bar scraping the Services. The founder decided on 6 November 2026 that reading at a person's pace is fine, so six pages were read one at a time on 12 November: the acceptable use policy, the training data page and its summary for this model, the model card page, and the tml-renderers and thinking effort guides. thinkingmachines.ai's robots.txt has no rules, and tinker-docs.thinkingmachines.ai answers 404 for robots.txt."
        ],
        "score": 72
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling-2-small.json",
      "live": {
        "slug": "inkling-2-small",
        "probe": {
          "target": "https://tinker.thinkingmachines.dev/services/tinker-prod/oai/api/v1",
          "method": "get",
          "lastAt": "2026-11-13T20:11:37.236512439Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 439,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 238,
          "p95ms24h": 467,
          "samples24h": 245,
          "samples30d": 1854,
          "days": [
            {
              "date": "2026-11-06",
              "probes": 186,
              "ok": 186
            },
            {
              "date": "2026-11-07",
              "probes": 243,
              "ok": 243
            },
            {
              "date": "2026-11-08",
              "probes": 243,
              "ok": 243
            },
            {
              "date": "2026-11-09",
              "probes": 243,
              "ok": 243
            },
            {
              "date": "2026-11-10",
              "probes": 244,
              "ok": 244
            },
            {
              "date": "2026-11-11",
              "probes": 244,
              "ok": 244
            },
            {
              "date": "2026-11-12",
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        "llmsTxt": {
          "url": "https://tinker-docs.thinkingmachines.ai/llms.txt",
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        "domain": {
          "domain": "thinkingmachines.ai",
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          "source": "https://rdap.identitydigital.services/rdap/domain/thinkingmachines.ai",
          "checkedAt": "2026-11-08T15:05:10.558189316Z"
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        "pages": [
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      {
        "by": 25,
        "category": "interface",
        "leads": "inkling-2-small",
        "name": "Agent interface",
        "reasons": {
          "a": "Chat template 20, the base's template in the repository. Tool-calling format 10 of 25, the card names the qwen3_coder parser and nothing more. Trained tool calling 20, tuned for tool use with several calls a turn. Structured output 0. Reasoning control 0, the card doesn't say how to turn thinking off or budget it. Context 10, 262,144 tokens. 20 + 10 + 20 + 0 + 0 + 10 = 60.",
          "b": "Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back for this model, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request from none to xhigh, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens. 20 + 25 + 20 + 0 + 10 + 10 = 85."
        },
        "scores": {
          "a": 60,
          "b": 85
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        "by": 21,
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        "leads": "inkling-2-small",
        "name": "Documentation and upkeep",
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          "a": "Model card 11 of 20, limitations, architecture and a cut-off are missing. Training data 5, a general description of about 10,000 synthetic examples. Last change 15, the card last changed on 6 August 2026, 90 days before this check. Responsiveness 0, no publisher reply to any of 7 questions. Version policy 5, a first release. File health 10, the files agree with the card and the base. 11 + 5 + 15 + 0 + 5 + 10 = 46.",
          "b": "Model card 17 of 20, everything but a dated knowledge cut-off. Training data 15, an EU training-content summary with sources, mix, an October 2026 collection cut-off and filtering. Last change 20, the files were uploaded on 12 November 2026. Responsiveness 0, the repository has no questions yet, which reads as none answered. Version policy 5, a first release. File health 10, the files agree and no broken-file report waits. 17 + 15 + 20 + 0 + 5 + 10 = 67."
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          "b": 67
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        "leads": "bigbang-v1",
        "name": "Reach",
        "reasons": {
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          "b": "Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line. Runtimes 0, no released version of the six runs it; vLLM and SGLang serve it from their own images and Transformers has it on its main branch only. Builds 15, two precisions from the publisher (NVFP4 and MXFP8). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Thinking Machines' own Tinker serves it as beta serverless inference, and Together is live on Hugging Face. 0 + 0 + 15 + 10 + 10 + 5 = 40."
        },
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          "b": 40
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        "category": "risk",
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        "name": "Risk",
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          "b": "File safety 25, safetensors only and no repository code to run. Provenance 15, the files are in the organisation Thinking Machines links to, with a SHA-256 on every LFS file. Safety evaluation 10, Thinking Machines' own StrongREJECT, FORTRESS, HoneyBench and DistressBench results and described outside red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 5, the card names safeguards to add but doesn't say what its refusals cover, with nothing on prompt injection. Licence risk 5, 10 off for a use policy that reaches beyond the law and that can change at any time. Security programme 5, a security.txt and a disclosure policy, with public advisories unchecked and scored as absent. 25 + 15 + 10 + 5 + 5 + 5 = 65."
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          "b": 65
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        "b": "Open-weight model",
        "name": "Kind"
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        "a": "The Endless Frontier (endless-frontier)",
        "b": "Thinking Machines Lab",
        "name": "Vendor"
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      {
        "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"
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      {
        "a": "Apache-2.0",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
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        "a": "2026-08-06",
        "b": "2026-11-12",
        "name": "Last release"
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      {
        "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": "2.3/5 (4)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Inkling 2 Small scores 58.8 (C) on agent readiness against BigBang-v1's 56.3 (C), and leads in 3 of 4 scored categories. BigBang-v1 leads on reach.",
        "question": "Which is better for AI agents, BigBang-v1 or Inkling 2 Small?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 60 against 40"
        ],
        "also": null,
        "goodFor": "Agents with 96 GB or more that want an Apache 2.0 mixture-of-experts model tuned for research, search and coding, and can do without publisher support.",
        "slug": "bigbang-v1",
        "watchFor": "BF16 is the only build from the publisher, needing about 86 GB"
      },
      {
        "aheadOn": [
          "Risk, 65 against 55",
          "Agent interface, 85 against 60",
          "Documentation and upkeep, 67 against 46"
        ],
        "also": null,
        "goodFor": "Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.",
        "slug": "inkling-2-small",
        "watchFor": "The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory"
      }
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    "history": {
      "bigbang-v1": [
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          "date": "2026-11-04",
          "delta": 1.9,
          "from": 54.4,
          "fromGrade": "C",
          "to": 56.3,
          "toGrade": "C"
        }
      ],
      "inkling-2-small": [
        {
          "causes": [
            "product"
          ],
          "date": "2026-11-12",
          "delta": 6.7,
          "from": 52.1,
          "fromGrade": "D",
          "to": 58.8,
          "toGrade": "C"
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        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-2-small.json",
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        "title": "Apertus v1.5 8B vs BigBang-v1",
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        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small.json",
        "title": "Apertus v1.5 8B vs Inkling 2 Small",
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        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-bigbang-v1.json",
        "title": "Apodex-1.1-mini vs BigBang-v1",
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        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-2-small.json",
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        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-inkling-2-small.json",
        "title": "Arete-27B vs Inkling 2 Small",
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v4-1-flash.json",
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v4-flash-0731.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v4-flash-0731"
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-devstral-small-2.json",
        "title": "BigBang-v1 vs Devstral Small 2",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-devstral-small-2"
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-diffusiongemma-26b-a4b-it.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-diffusiongemma-26b-a4b-it"
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-exaone-4-5-33b"
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-12b-it"
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-26b-a4b-it"
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-31b-it.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-31b-it"
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-e2b-it"
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-e4b-it"
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-4-5-air.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-4-5-air"
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-4-7-flash"
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        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-5-3.json",
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        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-397b-a17b.json",
        "title": "Inkling 2 Small vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-4b.json",
        "title": "Inkling 2 Small vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-9b.json",
        "title": "Inkling 2 Small vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b.json",
        "title": "Inkling 2 Small vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-35b-a3b.json",
        "title": "Inkling 2 Small vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-27b.json",
        "title": "Inkling 2 Small vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-flash-next.json",
        "title": "Inkling 2 Small vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-next.json",
        "title": "Inkling 2 Small vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-2b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-32b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-4b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-8b-instruct.json",
        "title": "Inkling 2 Small vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Inkling 2 Small vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-recursive-flint.json",
        "title": "Inkling 2 Small vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ripple-65b-preview.json",
        "title": "Inkling 2 Small vs Ripple-65B Preview",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ripple-65b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-sensenova-loop-9b-preview.json",
        "title": "Inkling 2 Small vs SenseNova-Loop-9B-Preview",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-sensenova-loop-9b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-smollm3-3b.json",
        "title": "Inkling 2 Small vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-spark-x2-6-4b.json",
        "title": "Inkling 2 Small vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-step-3-7-flash.json",
        "title": "Inkling 2 Small vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-step-3-7-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Inkling 2 Small vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Inkling 2 Small vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Inkling 2 Small vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-unlimited-ocr-2.json",
        "title": "Inkling 2 Small vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-2b.json",
        "title": "Inkling 2 Small vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-4b.json",
        "title": "Inkling 2 Small vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-wevisone-vl-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-zaya1-8b.json",
        "title": "Inkling 2 Small vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-zaya1-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-inkling-2-small.json",
        "title": "Inkling vs Inkling 2 Small",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-inkling-2-small"
      }
    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "bigbang-v1": 60,
        "by": 20,
        "edge": "bigbang-v1",
        "inkling-2-small": 40,
        "key": "reach",
        "name": "Reach",
        "weight": 25
      },
      {
        "bigbang-v1": 55,
        "by": 10,
        "edge": "inkling-2-small",
        "inkling-2-small": 65,
        "key": "risk",
        "name": "Risk",
        "weight": 20
      },
      {
        "bigbang-v1": 60,
        "by": 25,
        "edge": "inkling-2-small",
        "inkling-2-small": 85,
        "key": "interface",
        "name": "Agent interface",
        "weight": 10
      },
      {
        "bigbang-v1": 46,
        "by": 21,
        "edge": "inkling-2-small",
        "inkling-2-small": 67,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Inkling 2 Small scores 58.8 (C) on agent readiness against BigBang-v1's 56.3 (C), and leads in 3 of 4 scored categories. BigBang-v1 leads on reach. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "bigbang-v1": "A Qwen3.6-35B-A3B fine-tuned on synthetic research problems, under plain Apache 2.0, for search, science and coding work. The publisher ships BF16 only, about 86 GB to run, and has no report, safety results or replies to questions, so smaller builds and support come from others.",
      "inkling-2-small": "Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change."
    }
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    "html": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-2-small",
    "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-2-small.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-2-small.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-2-small.min.md"
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  "markdown": "Inkling 2 Small scores 58.8 (C) on agent readiness against BigBang-v1's 56.3 (C), and leads in 3 of 4 scored categories. BigBang-v1 leads on reach. Both do open-weight models you run yourself.\n\n- BigBang-v1: grade C, 56.3/100, rank #117 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/bigbang-v1.md · JSON https://www.anchorterminal.com/api/v1/tools/bigbang-v1.json\n- Inkling 2 Small: grade C, 58.8/100, rank #102 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling-2-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-2-small.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 6472 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### BigBang-v1 (C)\n\nGood for: Agents with 96 GB or more that want an Apache 2.0 mixture-of-experts model tuned for research, search and coding, and can do without publisher support.\n\nAhead on:\n- Reach, 60 against 40\n\nWatch for: BF16 is the only build from the publisher, needing about 86 GB\n\n### Inkling 2 Small (C)\n\nGood for: Teams with 512 GB or more of datacentre GPU memory who want Thinking Machines' newest open multimodal agent model and can run a runtime's pre-release image.\n\nAhead on:\n- Risk, 65 against 55\n- Agent interface, 85 against 60\n- Documentation and upkeep, 67 against 46\n\nWatch for: The smaller checkpoint needs about 472 GB, and Thinking Machines says 500 GB of GPU memory\n\n\n## Why the edge\n\n### Agent interface: Inkling 2 Small +25\n\n- BigBang-v1 (60): Chat template 20, the base's template in the repository. Tool-calling format 10 of 25, the card names the qwen3_coder parser and nothing more. Trained tool calling 20, tuned for tool use with several calls a turn. Structured output 0. Reasoning control 0, the card doesn't say how to turn thinking off or budget it. Context 10, 262,144 tokens. 20 + 10 + 20 + 0 + 0 + 10 = 60.\n- Inkling 2 Small (85): Chat template 20, a Jinja file in the repository. Tool-calling format 25, Thinking Machines' tml-renderers guide shows how tools are declared and how calls come back for this model, and its package ships the parser. Trained tool calling 20, several calls in one turn. Structured output 0, not documented. Reasoning control 10, thinking effort is set per request from none to xhigh, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens. 20 + 25 + 20 + 0 + 10 + 10 = 85.\n\n### Documentation and upkeep: Inkling 2 Small +21\n\n- BigBang-v1 (46): Model card 11 of 20, limitations, architecture and a cut-off are missing. Training data 5, a general description of about 10,000 synthetic examples. Last change 15, the card last changed on 6 August 2026, 90 days before this check. Responsiveness 0, no publisher reply to any of 7 questions. Version policy 5, a first release. File health 10, the files agree with the card and the base. 11 + 5 + 15 + 0 + 5 + 10 = 46.\n- Inkling 2 Small (67): Model card 17 of 20, everything but a dated knowledge cut-off. Training data 15, an EU training-content summary with sources, mix, an October 2026 collection cut-off and filtering. Last change 20, the files were uploaded on 12 November 2026. Responsiveness 0, the repository has no questions yet, which reads as none answered. Version policy 5, a first release. File health 10, the files agree and no broken-file report waits. 17 + 15 + 20 + 0 + 5 + 10 = 67.\n\n### Reach: BigBang-v1 +20\n\n- BigBang-v1 (60): Memory 10 of 30, the only build from the publisher is BF16 at 71.9 GB, 86.3 GB with a fifth added, which fits the reference machine but not 64 GB. Runtimes 25, it keeps the base's qwen3_5_moe architecture, which llama.cpp, vLLM, SGLang and Transformers run in released versions, and Ollama 0.40.14 runs through the llama.cpp build it pins. Builds 0, no quantised build from the publisher. Terms 15, Apache 2.0 like its base. Download 10, not gated. Hosted 0, one inference provider, Featherless AI, where the line needs two. 10 + 25 + 0 + 15 + 10 + 0 = 60.\n- Inkling 2 Small (40): Memory 0 of 30, the smallest build is Thinking Machines' NVFP4 checkpoint at 393.5 GB, about 472 GB with a fifth added, above the 256 GB line. Runtimes 0, no released version of the six runs it; vLLM and SGLang serve it from their own images and Transformers has it on its main branch only. Builds 15, two precisions from the publisher (NVFP4 and MXFP8). Terms 10, Apache 2.0 with a binding acceptable use policy on top, read as a custom licence. Download 10, no gate. Hosted 5, Thinking Machines' own Tinker serves it as beta serverless inference, and Together is live on Hugging Face. 0 + 0 + 15 + 10 + 10 + 5 = 40.\n\n### Risk: Inkling 2 Small +10\n\n- BigBang-v1 (55): File safety 25, safetensors only and nothing from the repository runs. Provenance 15, the files are in the publisher's own organisation with a SHA-256 for every weight file. Safety evaluation 0. Agent guidance 0. Licence risk 15, plain Apache 2.0 that hasn't changed. Security programme 0, no website or security contact. 25 + 15 + 0 + 0 + 15 + 0 = 55.\n- Inkling 2 Small (65): File safety 25, safetensors only and no repository code to run. Provenance 15, the files are in the organisation Thinking Machines links to, with a SHA-256 on every LFS file. Safety evaluation 10, Thinking Machines' own StrongREJECT, FORTRESS, HoneyBench and DistressBench results and described outside red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 5, the card names safeguards to add but doesn't say what its refusals cover, with nothing on prompt injection. Licence risk 5, 10 off for a use policy that reaches beyond the law and that can change at any time. Security programme 5, a security.txt and a disclosure policy, with public advisories unchecked and scored as absent. 25 + 15 + 10 + 5 + 5 + 5 = 65.\n\n## Score by category\n\n| Category | Weight | BigBang-v1 | Inkling 2 Small | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 60 | 40 | BigBang-v1 +20 |\n| Risk | 20% (20 this run) | 55 | 65 | Inkling 2 Small +10 |\n| Agent interface | 10% (10 this run) | 60 | 85 | Inkling 2 Small +25 |\n| Documentation and upkeep | 10% (10 this run) | 46 | 67 | Inkling 2 Small +21 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **56.3 · C** | **58.8 · C** | |\n\n## Facts side by side\n\n| Fact | BigBang-v1 | Inkling 2 Small |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | The Endless Frontier (endless-frontier) | Thinking Machines 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 | Apache-2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-08-06 | 2026-11-12 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Agent reviews | 2.3/5 (4) | none |\n\n## How the scores have moved\n\n### BigBang-v1\n\n- +1.9 on 4 November 2026: correction\n\n### Inkling 2 Small\n\n- +6.7 on 12 November 2026 (D to C): product\n\n## Verdicts\n\n**BigBang-v1.** A Qwen3.6-35B-A3B fine-tuned on synthetic research problems, under plain Apache 2.0, for search, science and coding work. The publisher ships BF16 only, about 86 GB to run, and has no report, safety results or replies to questions, so smaller builds and support come from others.\n\n**Inkling 2 Small.** Thinking Machines' newest open model, a 594B mixture-of-experts generalist with images in, several tool calls a turn and per-request thinking effort. The NVFP4 checkpoint needs about 472 GB, and no released runtime runs it yet, so today that means vLLM's or SGLang's own images, or Tinker and Together hosted. The use policy binds on download and can change.\n\n## Before you call either\n\n### BigBang-v1\n\n1. On the reference machine use `vllm serve endless-frontier/BigBang-v1 --max-model-len 131072 --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder`\n2. The card says to keep at least 128K of context so its thinking isn't cut short\n3. Thinking control isn't documented, try the base template's `enable_thinking` false in chat_template_kwargs and check the output\n4. For Ollama or llama.cpp you'll need someone else's GGUF; the publisher ships BF16 safetensors only\n5. Validate JSON output yourself or use the runtime's guided decoding\n\n### Inkling 2 Small\n\n1. No released runtime runs it yet. Serve the NVFP4 checkpoint from SGLang's dev-inkling-2-small image with the cookbook's recipe for your hardware, or from vLLM's vllm/vllm-openai:inkling-2-small image\n2. In vLLM pass `--reasoning-parser inkling --enable-auto-tool-choice --tool-call-parser inkling`. In SGLang the tool-call parser is `inkling2` and the reasoning parser `inkling`\n3. Transformers' main branch loads only thinkingmachines/Inkling-2-Small-MXFP8, the 622.8 GB checkpoint, and no release has the code yet\n4. Pass `reasoning_effort` as none, minimal, low, medium, high (the default), xhigh or max, or a number from 0 to 0.99\n5. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens\n6. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error\n7. Images should be 40 to 4096 px a side. The model takes no audio, and the template raises an error for an audio part\n8. Use guided decoding or validate JSON yourself, since structured output isn't documented\n9. Without the hardware, call it on Tinker's OpenAI-compatible endpoint with a Tinker key, at $0.30 input and $1.00 output per million tokens as read on 6 November 2026\n10. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal\n\n## Questions\n\n### Which is better for AI agents, BigBang-v1 or Inkling 2 Small?\n\nInkling 2 Small scores 58.8 (C) on agent readiness against BigBang-v1's 56.3 (C), and leads in 3 of 4 scored categories. BigBang-v1 leads on reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-2-small.json, and with the fewest tokens: https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-2-small.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"bigbang-v1\", \"b\": \"inkling-2-small\"}`. From a terminal: `anchor compare bigbang-v1 inkling-2-small`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/bigbang-v1.json and https://www.anchorterminal.com/api/v1/tools/inkling-2-small.json\n\n## Other comparisons with BigBang-v1 or Inkling 2 Small\n\n- [Agents-A1-4B vs BigBang-v1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-bigbang-v1.md)\n- [Agents-A1-4B vs Inkling 2 Small](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-2-small.md)\n- [Apertus v1.5 8B vs BigBang-v1](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-bigbang-v1.md)\n- [Apertus v1.5 8B vs Inkling 2 Small](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-2-small.md)\n- [Apodex-1.1-mini vs BigBang-v1](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-bigbang-v1.md)\n- [Apodex-1.1-mini vs Inkling 2 Small](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-2-small.md)\n- [Arete-27B vs BigBang-v1](https://www.anchorterminal.com/compare/arete-27b-vs-bigbang-v1.md)\n- [Arete-27B vs Inkling 2 Small](https://www.anchorterminal.com/compare/arete-27b-vs-inkling-2-small.md)\n- [BigBang-v1 vs Carbon-X](https://www.anchorterminal.com/compare/bigbang-v1-vs-carbon-x.md)\n- [BigBang-v1 vs Cola2](https://www.anchorterminal.com/compare/bigbang-v1-vs-cola2.md)\n- [BigBang-v1 vs Cosmos-Reason2-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-cosmos-reason2-2b.md)\n- [BigBang-v1 vs Darwin-36B-Opus](https://www.anchorterminal.com/compare/bigbang-v1-vs-darwin-36b-opus.md)\n- [BigBang-v1 vs DeepSeek-V3.2](https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v3-2.md)\n- [BigBang-v1 vs DeepSeek V4.1 Flash](https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v4-1-flash.md)\n- [BigBang-v1 vs DeepSeek-V4-Flash-0731](https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v4-flash-0731.md)\n- [BigBang-v1 vs Devstral Small 2](https://www.anchorterminal.com/compare/bigbang-v1-vs-devstral-small-2.md)\n- [BigBang-v1 vs DiffusionGemma 26B A4B IT](https://www.anchorterminal.com/compare/bigbang-v1-vs-diffusiongemma-26b-a4b-it.md)\n- [BigBang-v1 vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/bigbang-v1-vs-exaone-4-5-33b.md)\n- [BigBang-v1 vs Gemma 4 12B IT](https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-12b-it.md)\n- [BigBang-v1 vs Gemma 4 26B A4B IT](https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-26b-a4b-it.md)\n- [BigBang-v1 vs Gemma 4 31B IT](https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-31b-it.md)\n- [BigBang-v1 vs Gemma 4 E2B IT](https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-e2b-it.md)\n- [BigBang-v1 vs Gemma 4 E4B IT](https://www.anchorterminal.com/compare/bigbang-v1-vs-gemma-4-e4b-it.md)\n- [BigBang-v1 vs GLM-4.5-Air](https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-4-5-air.md)\n- [BigBang-v1 vs GLM-4.7-Flash](https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-4-7-flash.md)\n- [BigBang-v1 vs GLM-5.3](https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-5-3.md)\n- [BigBang-v1 vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/bigbang-v1-vs-glm-5-3-flash.md)\n- [BigBang-v1 vs gpt-oss-120b](https://www.anchorterminal.com/compare/bigbang-v1-vs-gpt-oss-120b.md)\n- [BigBang-v1 vs gpt-oss-20b](https://www.anchorterminal.com/compare/bigbang-v1-vs-gpt-oss-20b.md)\n- [BigBang-v1 vs Granite 4.2 30B](https://www.anchorterminal.com/compare/bigbang-v1-vs-granite-4-2-30b.md)\n- [BigBang-v1 vs Granite 4.2 3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-granite-4-2-3b.md)\n- [BigBang-v1 vs Granite 4.2 8B](https://www.anchorterminal.com/compare/bigbang-v1-vs-granite-4-2-8b.md)\n- [BigBang-v1 vs Hy-Memory-30B-A3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-hy-memory-30b-a3b.md)\n- [BigBang-v1 vs Hy3](https://www.anchorterminal.com/compare/bigbang-v1-vs-hy3.md)\n- [BigBang-v1 vs Inkling](https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.md)\n- [BigBang-v1 vs Inkling-Small](https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling-small.md)\n- [BigBang-v1 vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/bigbang-v1-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [BigBang-v1 vs Kimi K3](https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3.md)\n- [BigBang-v1 vs Kimi K3.1 Pro](https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3-1-pro.md)\n- [BigBang-v1 vs Kolibri-1](https://www.anchorterminal.com/compare/bigbang-v1-vs-kolibri-1.md)\n- [BigBang-v1 vs Kronos](https://www.anchorterminal.com/compare/bigbang-v1-vs-kronos.md)\n- [BigBang-v1 vs Laguna M.1](https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-m-1.md)\n- [BigBang-v1 vs Laguna S 2.1](https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-s-2-1.md)\n- [BigBang-v1 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-xs-2-1.md)\n- [BigBang-v1 vs LBS-27B](https://www.anchorterminal.com/compare/bigbang-v1-vs-lbs-27b.md)\n- [BigBang-v1 vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm2-5-2-6b.md)\n- [BigBang-v1 vs LFM3-1.7B](https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-1-7b.md)\n- [BigBang-v1 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-audio-2b.md)\n- [BigBang-v1 vs LFM3-Omni-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-omni-2b.md)\n- [BigBang-v1 vs LFM3-VL-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-vl-2b.md)\n- [BigBang-v1 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/bigbang-v1-vs-ling-3-0-tiny.md)\n- [BigBang-v1 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/bigbang-v1-vs-ling-3-1-flash-1019.md)\n- [BigBang-v1 vs LongCat-2.5](https://www.anchorterminal.com/compare/bigbang-v1-vs-longcat-2-5.md)\n- [BigBang-v1 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/bigbang-v1-vs-mimo-v2-6-distill-qwen-9b.md)\n- [BigBang-v1 vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/bigbang-v1-vs-mimo-v2-6-flash-rl.md)\n- [BigBang-v1 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-o-4-5.md)\n- [BigBang-v1 vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-v-4-7-1b.md)\n- [BigBang-v1 vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm-v-4-7-35b-a3b.md)\n- [BigBang-v1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-minicpm5-2b.md)\n- [BigBang-v1 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/bigbang-v1-vs-minimax-m2-5.md)\n- [BigBang-v1 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/bigbang-v1-vs-minimax-m2-7.md)\n- [BigBang-v1 vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/bigbang-v1-vs-minimax-m3-1-flash.md)\n- [BigBang-v1 vs Mistral Large 4](https://www.anchorterminal.com/compare/bigbang-v1-vs-mistral-large-4.md)\n- [BigBang-v1 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/bigbang-v1-vs-muse-glimmer-30b.md)\n- [BigBang-v1 vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-nanbeige-4-2-3b.md)\n- [BigBang-v1 vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/bigbang-v1-vs-nanbeige-4-3-33b.md)\n- [BigBang-v1 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [BigBang-v1 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [BigBang-v1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-nano-30b-a3b.md)\n- [BigBang-v1 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-nano-4b.md)\n- [BigBang-v1 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [BigBang-v1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-super-120b-a12b.md)\n- [BigBang-v1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/bigbang-v1-vs-nemotron-3-ultra-550b-a55b.md)\n- [BigBang-v1 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/bigbang-v1-vs-north-mini-code-1-0.md)\n- [BigBang-v1 vs occamy-1.0](https://www.anchorterminal.com/compare/bigbang-v1-vs-occamy-1-0.md)\n- [BigBang-v1 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/bigbang-v1-vs-olmo-3-7b-think.md)\n- [BigBang-v1 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/bigbang-v1-vs-ornith-1-5-122b.md)\n- [BigBang-v1 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-ornith-1-5-35b-a3b.md)\n- [BigBang-v1 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/bigbang-v1-vs-ornith-1-5-397b.md)\n- [BigBang-v1 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/bigbang-v1-vs-ornith-1-5-9b.md)\n- [BigBang-v1 vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/bigbang-v1-vs-otel-2-0-llm-31b-it.md)\n- [BigBang-v1 vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen-agentworld-35b-a3b.md)\n- [BigBang-v1 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-30b-a3b-instruct-2507.md)\n- [BigBang-v1 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-4b-instruct-2507.md)\n- [BigBang-v1 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-5-0-8b.md)\n- [BigBang-v1 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-5-122b-a10b.md)\n- [BigBang-v1 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-5-2b.md)\n- [BigBang-v1 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-5-397b-a17b.md)\n- [BigBang-v1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-5-4b.md)\n- [BigBang-v1 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-5-9b.md)\n- [BigBang-v1 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-6-27b.md)\n- [BigBang-v1 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-6-35b-a3b.md)\n- [BigBang-v1 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-8-27b.md)\n- [BigBang-v1 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-8-flash-next.md)\n- [BigBang-v1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-coder-30b-a3b-instruct.md)\n- [BigBang-v1 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-coder-next.md)\n- [BigBang-v1 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-omni-30b-a3b-instruct.md)\n- [BigBang-v1 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-vl-2b-instruct.md)\n- [BigBang-v1 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-vl-30b-a3b-instruct.md)\n- [BigBang-v1 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-vl-32b-instruct.md)\n- [BigBang-v1 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-vl-4b-instruct.md)\n- [BigBang-v1 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwen3-vl-8b-instruct.md)\n- [BigBang-v1 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/bigbang-v1-vs-qwopus3-8-27b-flash-v2.md)\n- [BigBang-v1 vs Recursive Flint](https://www.anchorterminal.com/compare/bigbang-v1-vs-recursive-flint.md)\n- [BigBang-v1 vs Ripple-65B Preview](https://www.anchorterminal.com/compare/bigbang-v1-vs-ripple-65b-preview.md)\n- [BigBang-v1 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/bigbang-v1-vs-sensenova-loop-9b-preview.md)\n- [BigBang-v1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/bigbang-v1-vs-smollm3-3b.md)\n- [BigBang-v1 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/bigbang-v1-vs-spark-x2-6-4b.md)\n- [BigBang-v1 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/bigbang-v1-vs-step-3-7-flash.md)\n- [BigBang-v1 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/bigbang-v1-vs-swift-1-5-qwen3-8-27b.md)\n- [BigBang-v1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/bigbang-v1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [BigBang-v1 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/bigbang-v1-vs-thinkingcap-qwen3-8-27b.md)\n- [BigBang-v1 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/bigbang-v1-vs-unlimited-ocr-2.md)\n- [BigBang-v1 vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-wevisone-vl-2b.md)\n- [BigBang-v1 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/bigbang-v1-vs-wevisone-vl-4b.md)\n- [BigBang-v1 vs ZAYA1-8B](https://www.anchorterminal.com/compare/bigbang-v1-vs-zaya1-8b.md)\n- [Carbon-X vs Inkling 2 Small](https://www.anchorterminal.com/compare/carbon-x-vs-inkling-2-small.md)\n- [Cola2 vs Inkling 2 Small](https://www.anchorterminal.com/compare/cola2-vs-inkling-2-small.md)\n- [Cosmos-Reason2-2B vs Inkling 2 Small](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling-2-small.md)\n- [Darwin-36B-Opus vs Inkling 2 Small](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling-2-small.md)\n- [DeepSeek-V3.2 vs Inkling 2 Small](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-2-small.md)\n- [DeepSeek V4.1 Flash vs Inkling 2 Small](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling-2-small.md)\n- [DeepSeek-V4-Flash-0731 vs Inkling 2 Small](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-2-small.md)\n- [Devstral Small 2 vs Inkling 2 Small](https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling-2-small.md)\n- [DiffusionGemma 26B A4B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling-2-small.md)\n- [EXAONE 4.5 33B vs Inkling 2 Small](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling-2-small.md)\n- [Gemma 4 12B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling-2-small.md)\n- [Gemma 4 26B A4B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling-2-small.md)\n- [Gemma 4 31B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling-2-small.md)\n- [Gemma 4 E2B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-inkling-2-small.md)\n- [Gemma 4 E4B IT vs Inkling 2 Small](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling-2-small.md)\n- [GLM-4.5-Air vs Inkling 2 Small](https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling-2-small.md)\n- [GLM-4.7-Flash vs Inkling 2 Small](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling-2-small.md)\n- [GLM-5.3-Flash vs Inkling 2 Small](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling-2-small.md)\n- [GLM-5.3 vs Inkling 2 Small](https://www.anchorterminal.com/compare/glm-5-3-vs-inkling-2-small.md)\n- [gpt-oss-120b vs Inkling 2 Small](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling-2-small.md)\n- 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