{ "data": { "a": { "slug": "deepseek-v4-flash-0731", "name": "DeepSeek-V4-Flash-0731", "vendor": "DeepSeek", "vendorUrl": "https://www.deepseek.com", "kind": "weights", "category": "open-weights", "summary": "DeepSeek-V4-Flash-0731 is the 31 July 2026 release of DeepSeek's V4 Flash, a mixture-of-experts text model with 284B parameters, 13B active and a 1M-token context, under MIT. DeepSeek's API retired V4 Flash on 10 September 2026.", "url": "https://www.anchorterminal.com/tools/deepseek-v4-flash-0731", "markdownUrl": "https://www.anchorterminal.com/tools/deepseek-v4-flash-0731.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/deepseek-v4-flash-0731.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/deepseek-v4-flash-0731.json", "dns": "deepseek-v4-flash-0731.grade.anchorterminal.com", "repo": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731", "license": "MIT", "transports": [], "packages": [ { "registry": "huggingface", "name": "deepseek-ai/DeepSeek-V4-Flash-0731" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository isn't gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under the MIT licence. DeepSeek's API retired V4 Flash on 10 September 2026 and routes its old names to V4.1 Flash, so no hosted DeepSeek endpoint serves these weights. Running them yourself costs the hardware, 166.9 GB of files (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-02" }, "docsUrl": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "reasoning", "tool-calling", "long-context", "mit", "safetensors", "fp8", "fp4", "self-hosted", "new" ], "lastRelease": "2026-07-31", "graded": true, "anchor": { "graded": true, "score": 61.9, "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": 24, "methodology": "0.8", "run": "2026-10-01", "scores": { "capability": 66, "interface": 75, "reach": 70, "risk": 50, "upkeep": 38 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-11-02" }, "negative": 0, "verdict": "A long-context agent cousin under MIT with documented tool calls, three reasoning effort levels and support in every major runtime but Ollama. It needs about 190 to 200 GB of memory, though five inference providers serve it. The main risks are prompts built from DeepSeek's Python, no published safety results and no answers in its repository.", "bestFor": "Agents or teams with a multi-GPU server, or a provider account, who want DeepSeek's V4 agent model under MIT with a 1M context", "strengths": [ "MIT licence with nothing added, downloadable with no account", "1M tokens of context trained in", "Runs in vLLM, SGLang, llama.cpp, Transformers and LM Studio from released versions", "Parallel tool calls in a documented DSML format, with reasoning off or at three effort levels", "Five live inference providers on Hugging Face for agents without the hardware", "Safetensors only, with a SHA-256 on every shard" ], "weaknesses": [ "The smallest 4-bit build is 156.4 GB, so it needs about 188 GB and doesn't fit a 128 GB machine", "No Jinja template, so prompts come from running DeepSeek's encoding code or a runtime's own encoder", "No safety evaluation or agent-use guidance published, and only a company-wide security address", "DeepSeek hasn't replied to any of the 61 discussions, including reports of tool-call errors", "The card lacks intended use, limitations, languages and a knowledge cut-off" ], "agentNotes": [ "vllm serve deepseek-ai/DeepSeek-V4-Flash-0731 --trust-remote-code --kv-cache-dtype fp8 --block-size 256 --data-parallel-size 4 --enable-expert-parallel --moe-backend deep_gemm_mega_moe --attention-config '{\"use_fp4_indexer_cache\": true}' --speculative-config '{\"method\":\"dspark\",\"num_speculative_tokens\":7,\"draft_sample_method\":\"greedy\"}' --tokenizer-mode deepseek_v4 --tool-call-parser deepseek_v4 --enable-auto-tool-choice --reasoning-parser deepseek_v4 (the card's 4x GB300 example plus the parser flags from vLLM's recipe)", "Build prompts with encoding_dsv4.py, deepseek-recipe's V4 encoder or vLLM's --tokenizer-mode deepseek_v4, since the repository has no Jinja template", "Tool calls come back in a DSML tool_calls block with invoke elements, string parameters carry string=\"true\" and JSON values string=\"false\"", "Set temperature 1.0 and top_p 0.95 for agent work, and allow up to 384K output tokens at reasoning effort high or max", "Without the hardware, call it through a Hugging Face inference provider (DeepInfra, Novita, Baseten, Scaleway, Featherless), not DeepSeek's API, where deepseek-v4-flash now means V4.1 Flash", "LM Studio's library build is a 156.4 GB MXFP4 GGUF and LM Studio states 156 GB minimum system memory" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "C", "methodology": "0.8", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61.9 } ], "editorialScores": { "capability": 66, "interface": 75, "reach": 70, "risk": 50, "upkeep": 38 }, "provenanceScore": 75, "checked": { "categories": { "capability": "2026-11-02", "interface": "2026-11-02", "reach": "2026-11-02", "risk": "2026-11-02", "upkeep": "2026-11-02" }, "last": "2026-11-02", "lastMoved": "2026-11-02", "oldest": "2026-11-02", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# From DeepSeek's card (one 4x GB300 node). Add vLLM's --tokenizer-mode deepseek_v4 --tool-call-parser deepseek_v4 --enable-auto-tool-choice --reasoning-parser deepseek_v4 for tool calls\nvllm serve deepseek-ai/DeepSeek-V4-Flash-0731 \\\n --trust-remote-code --kv-cache-dtype fp8 --block-size 256 \\\n --data-parallel-size 4 --enable-expert-parallel \\\n --moe-backend deep_gemm_mega_moe \\\n --attention-config '{\"use_fp4_indexer_cache\": true}' \\\n --speculative-config '{\"method\":\"dspark\",\"num_speculative_tokens\":7,\"draft_sample_method\":\"greedy\"}'\n# or, with llama.cpp and llama.cpp's own GGUF:\nllama-server -hf ggml-org/DeepSeek-V4-Flash-0731-GGUF:MXFP4 --jinja" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/deepseek-v4-flash-0731" }, "sameCompany": [ "deepseek-api", "deepseek-search-api", "deepseek-ocr-2", "deepseek-harness", "deepseek-superagent", "deepseek-v4-1-flash", "deepseek-v3-2" ], "weights": { "trainedBy": "DeepSeek", "params": "284B", "active": "13B", "context": 1048576, "goodFor": "Text model for agents and long documents, with thinking or chat mode, reasoning effort and tool calls in DSML tags.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "LM Studio", "Transformers" ], "builds": [ { "name": "ggml-org DeepSeek-V4-Flash-0731-GGUF (MXFP4)", "url": "https://huggingface.co/ggml-org/DeepSeek-V4-Flash-0731-GGUF", "who": "llama.cpp", "precision": "mxfp4", "sizeGB": 154.99, "memoryGB": 192, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "From ggml-org, the llama.cpp project's organisation. 154.99 GB of MXFP4 weights, from the Hub's model information on 10 November 2026. The 2-bit files (Q2_K 117.3 GB, Q2_K_S 98.6 GB) are below the 4-bit line and aren't listed. Recorded after the last grading, so Reach doesn't count it yet" }, { "name": "DeepSeek-V4-Flash-0731", "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731", "who": "publisher", "precision": "fp8+fp4", "sizeGB": 166.9, "memoryGB": 256, "format": "safetensors", "note": "MoE experts in FP4, most other weights FP8; the only build DeepSeek publishes" } ], "run": "vllm serve deepseek-ai/DeepSeek-V4-Flash-0731 --trust-remote-code --kv-cache-dtype fp8 --block-size 256 --data-parallel-size 4 --enable-expert-parallel --moe-backend deep_gemm_mega_moe --attention-config '{\"use_fp4_indexer_cache\": true}' --speculative-config '{\"method\":\"dspark\",\"num_speculative_tokens\":7,\"draft_sample_method\":\"greedy\"}' --tokenizer-mode deepseek_v4 --tool-call-parser deepseek_v4 --enable-auto-tool-choice --reasoning-parser deepseek_v4", "runBuild": "DeepSeek-V4-Flash-0731", "checked": "2026-10-21", "minMemoryGB": 192 }, "family": { "lab": "DeepSeek", "family": "DeepSeek V4", "url": "https://www.anchorterminal.com/open-weights/#deepseek", "others": [ { "name": "DeepSeek-V4-Flash-Base", "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-Base", "params": "284B total, 13B activated" }, { "name": "DeepSeek-V4-Flash", "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash", "params": "284B total, 13B activated" }, { "name": "DeepSeek-V4-Flash-DSpark", "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-DSpark", "params": "284B total, 13B activated" }, { "name": "DeepSeek-V4-Flash-Vision-Exp", "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-Vision-Exp", "params": "not stated on card" }, { "name": "DeepSeek-V4-Pro-Base", "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-Base", "params": "1.6T total, 49B activated" }, { "name": "DeepSeek-V4-Pro", "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro", "params": "1.6T total, 49B activated" }, { "name": "DeepSeek-V4-Pro-DSpark", "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-DSpark", "params": "1.6T total, 49B activated" }, { "name": "DeepSeek-V4-Pro-0813", "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro-0813", "params": "1.6T total, 49B activated (V4-Pro figures; the 0813 card does not restate them)" }, { "name": "DeepSeek-V4.1-Flash", "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash", "params": "552B backbone, 8B activated in prefill / 16B in decode", "listing": "https://www.anchorterminal.com/tools/deepseek-v4-1-flash" }, { "name": "DeepSeek-V4.1-Flash-1017", "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017", "params": "552B backbone, 8B / 16B activated (V4.1-Flash figures; not restated)", "listing": "https://www.anchorterminal.com/tools/deepseek-v4-1-flash" } ], "olderCount": 72, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "DeepSeek (the MIT licence names DeepSeek, and DeepSeek's platform terms name Hangzhou DeepSeek Artificial Intelligence Co., Ltd.)", "domain": "deepseek.com", "domainRegistered": "2000-08-13", "domainNote": "deepseek.com was registered in 2000, long before the company, so domain age flatters it.", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731/commits/main", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The legal entity is the one DeepSeek's platform terms name, read for the deepseek-api listing. The weights' licence names only DeepSeek.", "Nothing is hosted, so the MIT licence stands in for terms of service and no privacy policy is scored.", "The changelog is the repository's commit history, four commits from 31 July to 1 August 2026 (the release and a card edit adding the SGLang cookbook).", "deepseek.com/.well-known/security.txt and www.deepseek.com/.well-known/security.txt answered 404 on 21 October 2026.", "DeepSeek's site footer has a Report Security Issue link to security@deepseek.com, a company-wide address, read from https://www.deepseek.com/en/transparency/ on 21 October 2026." ], "score": 75 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/deepseek-v4-flash-0731.json", "live": { "slug": "deepseek-v4-flash-0731", "securityTxt": { "url": "https://deepseek.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-14T16:18:39.710139082Z" }, "domain": { "domain": "deepseek.com", "registered": "2000-08-13", "source": "https://rdap.verisign.com/com/v1/domain/deepseek.com", "checkedAt": "2026-11-08T14:52:49.217816183Z" }, "pages": [ { "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash-0731/commits/main", "kind": "changelog", "status": 200, "checkedAt": "2026-11-14T19:05:25.885966043Z", "changedAt": "2026-11-14T19:05:25.885966043Z", "fingerprint": "0fff1174148a" } ], "updatedAt": "2026-11-14T19:05:25.885966043Z" } }, "answer": "DeepSeek-V4-Flash-0731 scores 61.9 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 1 of 4 scored categories. Inkling 2 Small leads on risk, agent interface and documentation and upkeep.", "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", "probes": 245, "ok": 245 }, { "date": "2026-11-13", "probes": 206, "ok": 206 } ], "since": "2026-11-06T00:00:00Z" }, "securityTxt": { "url": "https://thinkingmachines.ai/.well-known/security.txt", "state": "valid", "expires": "2029-07-13T07:00:00.000Z", "checkedAt": "2026-11-14T16:19:22.779006645Z" }, "llmsTxt": { "url": "https://tinker-docs.thinkingmachines.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-13T15:54:36.79283015Z" }, "domain": { "domain": "thinkingmachines.ai", "registered": "2024-07-09", "source": "https://rdap.identitydigital.services/rdap/domain/thinkingmachines.ai", "checkedAt": "2026-11-08T15:05:10.558189316Z" }, "pages": [ { "url": "https://huggingface.co/thinkingmachines/Inkling-2-Small/commits/main", "kind": "changelog", "status": 200, "checkedAt": "2026-11-14T19:07:35.812797752Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "39971da7a686" }, { "url": "https://tinker-docs.thinkingmachines.ai/changelog/", "kind": "changelog", "status": 200, "checkedAt": "2026-11-13T18:32:58.088087394Z", "changedAt": "2026-11-13T18:32:58.088087394Z", "fingerprint": "c56006412e95" }, { "url": "https://thinkingmachines.ai/legal/privacy/", "kind": "privacy", "status": 200, "checkedAt": "2026-11-13T18:32:53.884197991Z", "changedAt": "2026-11-06T13:43:40.660240815Z", "fingerprint": "3c33a4a74c61" }, { "url": "https://thinkingmachines.ai/legal/terms/", "kind": "terms", "status": 200, "checkedAt": "2026-11-13T18:32:56.034092745Z", "changedAt": "2026-11-06T13:43:42.918165055Z", "fingerprint": "08c6ceca5dbb" } ], "updatedAt": "2026-11-14T19:07:35.812797752Z" }, "streak": { "days": 9, "from": "2026-11-06", "sinceWatching": true, "best": 9 } }, "edges": [ { "by": 30, "category": "reach", "leads": "deepseek-v4-flash-0731", "name": "Reach", "reasons": { "a": "Memory 5, because the smallest build of 4-bit or better from a runtime's own library is LM Studio's MXFP4 GGUF at 156.4 GB, which with a fifth added needs 187.7 GB, more than our 107.4 GB machine and within 256 GB. DeepSeek's own release, 166.9 GB, sits in the same band. Runtimes 25, the cap, from vLLM v0.32.0, SGLang v0.5.22, llama.cpp release b11771, Transformers 5.20.0 and LM Studio's library, with Ollama not counted since its library entry is retired with no models pushed. Builds 10, DeepSeek ships one build, the FP8 and FP4 release itself. Terms 15, MIT with nothing added. Download 10, not gated. Hosted 5, DeepSeek's API moved to V4.1 Flash, but five inference providers on Hugging Face serve this repository live (Together's mapping has gone since 21 October).", "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." }, "scores": { "a": 70, "b": 40 } }, { "by": 29, "category": "upkeep", "leads": "inkling-2-small", "name": "Documentation and upkeep", "reasons": { "a": "Model card 8, the card and the DSpark card it names give architecture, parameters and context, with intended use, limitations, languages and cut-off missing. Training data 5, a general description in the report with no cut-off. Last change 10, a card edit on 1 August 2026, 93 days before 2 November, so past 90 and within 180; deepseek-recipe 0.2.0 (20 October) stays read as a library-wide release, not a change to this model's files. Responsiveness 0, DeepSeek answered none of the 61 discussions, the newest opened on 17 October. Version policy 10, the preview and DSpark copies keep their own repositories and the dated 0731 release says what it supersedes. File health 5, the files agree with each other, but reports of tool-call errors and looping and a pull request for a missing chat template wait without a reply from DeepSeek.", "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." }, "scores": { "a": 38, "b": 67 } }, { "by": 15, "category": "risk", "leads": "inkling-2-small", "name": "Risk", "reasons": { "a": "File safety 15, safetensors only, less 10 because prompts are built by running DeepSeek's encoding_dsv4.py from the repository and the card's serving commands pass --trust-remote-code. Provenance 15, the deepseek-ai organisation and a SHA-256 on every shard. Safety evaluation 0, none published. Agent guidance 0, the encoding README's notes about the parser and the reserved developer role are usage notes, read alike for all three DeepSeek listings. Licence risk 15, MIT with no deductions. Security programme 5, for the security@deepseek.com reporting address in DeepSeek's site footer, read as for DeepSeek-V3.2, with no security.txt and no public advisories.", "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." }, "scores": { "a": 50, "b": 65 } }, { "by": 10, "category": "interface", "leads": "inkling-2-small", "name": "Agent interface", "reasons": { "a": "Chat template 10, there is no Jinja template and the format is given as Python to run. Tool-calling format 10, DeepSeek documents how tools are declared and returned and ships its own parser, but only vLLM's recipe names a runtime parser, so the 25 line isn't met. Trained tool calling 20, several invoke elements in one call block. Structured output 15, DeepSeek's deepseek-recipe library documents JSON Schema response formats for V4 prompts. Reasoning control 10, chat mode with no thinking and three effort levels in thinking mode, with reasoning returned as reasoning_content. Context 10, 1M tokens trained.", "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": 75, "b": 85 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "DeepSeek", "b": "Thinking Machines Lab", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "", "b": "", "name": "Transports" }, { "a": "None", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "MIT", "b": "Apache-2.0", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-07-31", "b": "2026-11-12", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "2.5/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "DeepSeek-V4-Flash-0731 scores 61.9 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 1 of 4 scored categories. Inkling 2 Small leads on risk, agent interface and documentation and upkeep.", "question": "Which is better for AI agents, DeepSeek-V4-Flash-0731 or Inkling 2 Small?" } ], "goodFor": [ { "aheadOn": [ "Reach, 70 against 40" ], "also": null, "goodFor": "Agents or teams with a multi-GPU server, or a provider account, who want DeepSeek's V4 agent model under MIT with a 1M context", "slug": "deepseek-v4-flash-0731", "watchFor": "The smallest 4-bit build is 156.4 GB, so it needs about 188 GB and doesn't fit a 128 GB machine" }, { "aheadOn": [ "Risk, 65 against 50", "Agent interface, 85 against 75", "Documentation and upkeep, 67 against 38" ], "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" } ], "history": { "deepseek-v4-flash-0731": [ { "causes": [ "time" ], "date": "2026-11-02", "delta": -0.5, "from": 62.4, "fromGrade": "B", "to": 61.9, "toGrade": "C" } ], "inkling-2-small": [ { "causes": [ "product" ], "date": "2026-11-12", "delta": 6.7, "from": 52.1, "fromGrade": "D", "to": 58.8, "toGrade": "C" } ] }, "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-deepseek-v4-flash-0731.json", "title": "Agents-A1-4B vs DeepSeek-V4-Flash-0731", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-deepseek-v4-flash-0731" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-2-small.json", "title": "Agents-A1-4B vs Inkling 2 Small", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-2-small" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-deepseek-v4-flash-0731.json", "title": "Apertus v1.5 8B vs 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"https://www.anchorterminal.com/compare/inkling-2-small-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-occamy-1-0.json", "title": "Inkling 2 Small vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-olmo-3-7b-think.json", "title": "Inkling 2 Small vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-122b.json", "title": "Inkling 2 Small vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-35b-a3b.json", "title": "Inkling 2 Small vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-ornith-1-5-35b-a3b" }, { "json": 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"https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Inkling 2 Small vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-4b-instruct-2507.json", "title": "Inkling 2 Small vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-0-8b.json", "title": "Inkling 2 Small vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-122b-a10b.json", "title": "Inkling 2 Small vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-2b.json", "title": "Inkling 2 Small vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/inkling-2-small-vs-qwen3-5-2b" }, { "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 }, { "by": 30, "deepseek-v4-flash-0731": 70, "edge": "deepseek-v4-flash-0731", "inkling-2-small": 40, "key": "reach", "name": "Reach", "weight": 25 }, { "by": 15, "deepseek-v4-flash-0731": 50, "edge": "inkling-2-small", "inkling-2-small": 65, "key": "risk", "name": "Risk", "weight": 20 }, { "by": 10, "deepseek-v4-flash-0731": 75, "edge": "inkling-2-small", "inkling-2-small": 85, "key": "interface", "name": "Agent interface", "weight": 10 }, { "by": 29, "deepseek-v4-flash-0731": 38, "edge": "inkling-2-small", "inkling-2-small": 67, "key": "upkeep", "name": "Documentation and upkeep", "weight": 10 } ], "summary": "DeepSeek-V4-Flash-0731 scores 61.9 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 1 of 4 scored categories. Inkling 2 Small leads on risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.", "tasks": null, "tutorials": [], "verdicts": { "deepseek-v4-flash-0731": "A long-context agent cousin under MIT with documented tool calls, three reasoning effort levels and support in every major runtime but Ollama. It needs about 190 to 200 GB of memory, though five inference providers serve it. The main risks are prompts built from DeepSeek's Python, no published safety results and no answers in its repository.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-2-small", "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-2-small.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-2-small.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-2-small.min.md" }, "markdown": "DeepSeek-V4-Flash-0731 scores 61.9 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 1 of 4 scored categories. Inkling 2 Small leads on risk, agent interface and documentation and upkeep. Both do open-weight models you run yourself.\n\n- DeepSeek-V4-Flash-0731: grade C, 61.9/100, rank #33 of 161 open-weight models. Markdown https://www.anchorterminal.com/tools/deepseek-v4-flash-0731.md · JSON https://www.anchorterminal.com/api/v1/tools/deepseek-v4-flash-0731.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### DeepSeek-V4-Flash-0731 (C)\n\nGood for: Agents or teams with a multi-GPU server, or a provider account, who want DeepSeek's V4 agent model under MIT with a 1M context\n\nAhead on:\n- Reach, 70 against 40\n\nWatch for: The smallest 4-bit build is 156.4 GB, so it needs about 188 GB and doesn't fit a 128 GB machine\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 50\n- Agent interface, 85 against 75\n- Documentation and upkeep, 67 against 38\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### Reach: DeepSeek-V4-Flash-0731 +30\n\n- DeepSeek-V4-Flash-0731 (70): Memory 5, because the smallest build of 4-bit or better from a runtime's own library is LM Studio's MXFP4 GGUF at 156.4 GB, which with a fifth added needs 187.7 GB, more than our 107.4 GB machine and within 256 GB. DeepSeek's own release, 166.9 GB, sits in the same band. Runtimes 25, the cap, from vLLM v0.32.0, SGLang v0.5.22, llama.cpp release b11771, Transformers 5.20.0 and LM Studio's library, with Ollama not counted since its library entry is retired with no models pushed. Builds 10, DeepSeek ships one build, the FP8 and FP4 release itself. Terms 15, MIT with nothing added. Download 10, not gated. Hosted 5, DeepSeek's API moved to V4.1 Flash, but five inference providers on Hugging Face serve this repository live (Together's mapping has gone since 21 October).\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### Documentation and upkeep: Inkling 2 Small +29\n\n- DeepSeek-V4-Flash-0731 (38): Model card 8, the card and the DSpark card it names give architecture, parameters and context, with intended use, limitations, languages and cut-off missing. Training data 5, a general description in the report with no cut-off. Last change 10, a card edit on 1 August 2026, 93 days before 2 November, so past 90 and within 180; deepseek-recipe 0.2.0 (20 October) stays read as a library-wide release, not a change to this model's files. Responsiveness 0, DeepSeek answered none of the 61 discussions, the newest opened on 17 October. Version policy 10, the preview and DSpark copies keep their own repositories and the dated 0731 release says what it supersedes. File health 5, the files agree with each other, but reports of tool-call errors and looping and a pull request for a missing chat template wait without a reply from DeepSeek.\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### Risk: Inkling 2 Small +15\n\n- DeepSeek-V4-Flash-0731 (50): File safety 15, safetensors only, less 10 because prompts are built by running DeepSeek's encoding_dsv4.py from the repository and the card's serving commands pass --trust-remote-code. Provenance 15, the deepseek-ai organisation and a SHA-256 on every shard. Safety evaluation 0, none published. Agent guidance 0, the encoding README's notes about the parser and the reserved developer role are usage notes, read alike for all three DeepSeek listings. Licence risk 15, MIT with no deductions. Security programme 5, for the security@deepseek.com reporting address in DeepSeek's site footer, read as for DeepSeek-V3.2, with no security.txt and no public advisories.\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### Agent interface: Inkling 2 Small +10\n\n- DeepSeek-V4-Flash-0731 (75): Chat template 10, there is no Jinja template and the format is given as Python to run. Tool-calling format 10, DeepSeek documents how tools are declared and returned and ships its own parser, but only vLLM's recipe names a runtime parser, so the 25 line isn't met. Trained tool calling 20, several invoke elements in one call block. Structured output 15, DeepSeek's deepseek-recipe library documents JSON Schema response formats for V4 prompts. Reasoning control 10, chat mode with no thinking and three effort levels in thinking mode, with reasoning returned as reasoning_content. Context 10, 1M tokens trained.\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## Score by category\n\n| Category | Weight | DeepSeek-V4-Flash-0731 | Inkling 2 Small | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 70 | 40 | DeepSeek-V4-Flash-0731 +30 |\n| Risk | 20% (20 this run) | 50 | 65 | Inkling 2 Small +15 |\n| Agent interface | 10% (10 this run) | 75 | 85 | Inkling 2 Small +10 |\n| Documentation and upkeep | 10% (10 this run) | 38 | 67 | Inkling 2 Small +29 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61.9 · C** | **58.8 · C** | |\n\n## Facts side by side\n\n| Fact | DeepSeek-V4-Flash-0731 | Inkling 2 Small |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | DeepSeek | 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 | MIT | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-31 | 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 | 2.5/5 (4) | none |\n\n## How the scores have moved\n\n### DeepSeek-V4-Flash-0731\n\n- -0.5 on 2 November 2026 (B to C): time\n\n### Inkling 2 Small\n\n- +6.7 on 12 November 2026 (D to C): product\n\n## Verdicts\n\n**DeepSeek-V4-Flash-0731.** A long-context agent cousin under MIT with documented tool calls, three reasoning effort levels and support in every major runtime but Ollama. It needs about 190 to 200 GB of memory, though five inference providers serve it. The main risks are prompts built from DeepSeek's Python, no published safety results and no answers in its repository.\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### DeepSeek-V4-Flash-0731\n\n1. vllm serve deepseek-ai/DeepSeek-V4-Flash-0731 --trust-remote-code --kv-cache-dtype fp8 --block-size 256 --data-parallel-size 4 --enable-expert-parallel --moe-backend deep_gemm_mega_moe --attention-config '{\"use_fp4_indexer_cache\": true}' --speculative-config '{\"method\":\"dspark\",\"num_speculative_tokens\":7,\"draft_sample_method\":\"greedy\"}' --tokenizer-mode deepseek_v4 --tool-call-parser deepseek_v4 --enable-auto-tool-choice --reasoning-parser deepseek_v4 (the card's 4x GB300 example plus the parser flags from vLLM's recipe)\n2. Build prompts with encoding_dsv4.py, deepseek-recipe's V4 encoder or vLLM's --tokenizer-mode deepseek_v4, since the repository has no Jinja template\n3. Tool calls come back in a DSML tool_calls block with invoke elements, string parameters carry string=\"true\" and JSON values string=\"false\"\n4. Set temperature 1.0 and top_p 0.95 for agent work, and allow up to 384K output tokens at reasoning effort high or max\n5. Without the hardware, call it through a Hugging Face inference provider (DeepInfra, Novita, Baseten, Scaleway, Featherless), not DeepSeek's API, where deepseek-v4-flash now means V4.1 Flash\n6. LM Studio's library build is a 156.4 GB MXFP4 GGUF and LM Studio states 156 GB minimum system memory\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, DeepSeek-V4-Flash-0731 or Inkling 2 Small?\n\nDeepSeek-V4-Flash-0731 scores 61.9 (C) on agent readiness against Inkling 2 Small's 58.8 (C), and leads in 1 of 4 scored categories. Inkling 2 Small leads on risk, agent interface and documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-2-small.json, and with the fewest tokens: https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling-2-small.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"deepseek-v4-flash-0731\", \"b\": \"inkling-2-small\"}`. 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