{ "data": { "a": { "slug": "arete-27b", "name": "Arete-27B", "vendor": "Nous Research", "vendorUrl": "https://nousresearch.com", "kind": "weights", "category": "open-weights", "summary": "Arete-27B is Nous Research's fine-tune of Qwen3.8-27B, trained on 28,886 published examples so that its answers on politically sensitive topics stop following the Chinese state's account, with the base's tools, images and 262K context, under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/arete-27b", "markdownUrl": "https://www.anchorterminal.com/tools/arete-27b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/arete-27b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/arete-27b.json", "dns": "arete-27b.grade.anchorterminal.com", "repo": "https://huggingface.co/NousResearch/Arete-27B", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "NousResearch/Arete-27B" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-11-10).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0, in the card's metadata and as a LICENSE file in the repository. Running it yourself costs the hardware, 54.7 GB for the BF16 files, or 18.1 GB for bartowski's Q4_K_M GGUF with its projector (checked 2026-11-10).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-10" }, "docsUrl": "https://huggingface.co/NousResearch/Arete-27B", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "fine-tune", "qwen", "multimodal", "vision", "reasoning", "tool-calling", "apache-2.0", "safetensors", "self-hosted" ], "lastRelease": "2026-11-06", "graded": true, "anchor": { "graded": true, "score": 55.1, "grade": "C", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1518, "categoryRank": 92, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 60, "reach": 50, "risk": 55, "upkeep": 63 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "Qwen3.8-27B with its answers on politically sensitive topics retrained, four days old when read. The training data is published, which is rare. Nous Research ships BF16 only, so a small machine runs it from bartowski's GGUF, and the card documents none of the tool or thinking controls it inherits.", "bestFor": "Agents that want Qwen3.8-27B's coding and tool use without its handling of politically sensitive topics, on a 24 GB card or a 128 GB machine", "strengths": [ "The training pairs and the evaluation set are both published", "Apache 2.0, ungated, safetensors only, no remote code", "The base's architecture, so vLLM, SGLang and Transformers run it from their releases", "Fits a 128 GB machine in BF16, and 24 GB from bartowski's 4-bit GGUF", "Nous Research reports no meaningful loss against the base on its agent benchmarks" ], "weaknesses": [ "No quantised build from Nous Research, so the GGUF route depends on a third party", "The card doesn't document tool calling, structured output or how to switch thinking", "No limitations section, safety results or security contact", "None of the 13 discussions has a reply from Nous Research", "The results are Nous Research's own evaluation and nobody else has rerun it yet" ], "agentNotes": [ "Start it with `llama-server -hf bartowski/NousResearch_Arete-27B-GGUF:Q4_K_M --jinja`, a third party's conversion, or serve the BF16 files with vLLM", "Use the base's parsers in vLLM, `--reasoning-parser qwen3 --tool-call-parser qwen3_coder`, and check tool calls first, since the template differs slightly from Qwen3.8-27B's", "Thinking switches with `enable_thinking` in the template. The card's own evaluation ran with it off", "Expect answers on politically sensitive topics to differ from Qwen3.8-27B's. That is what the fine-tune is for", "Validate JSON output yourself, since structured output isn't documented" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 55.1 } ], "editorialScores": { "interface": 60, "reach": 50, "risk": 55, "upkeep": 63 }, "provenanceScore": 61, "checked": { "categories": { "interface": "2026-11-10", "reach": "2026-11-10", "risk": "2026-11-10", "upkeep": "2026-11-10" }, "last": "2026-11-10", "oldest": "2026-11-10", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "vllm serve NousResearch/Arete-27B --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/NousResearch_Arete-27B-GGUF:Q4_K_M --jinja", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"NousResearch/Arete-27B\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/arete-27b" }, "sameCompany": [ "hermes-agent" ], "weights": { "trainedBy": "Nous Research", "builtOn": "Qwen3.8-27B, declared as base_model in the card's metadata. Supervised fine-tuning with Inkling as the teacher", "params": "27.4B", "context": 262144, "goodFor": "Qwen3.8-27B for coding and agent work, text, images and video in, with its answers on politically sensitive topics retrained away from the Chinese state's account.", "runtimes": [ "vLLM", "SGLang", "Transformers", "llama.cpp" ], "builds": [ { "name": "bartowski NousResearch_Arete-27B-GGUF (Q4_K_M)", "url": "https://huggingface.co/bartowski/NousResearch_Arete-27B-GGUF", "who": "bartowski", "precision": "q4_k_m", "sizeGB": 18.13, "memoryGB": 24, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "From bartowski, a third party's conversion and not Nous Research's. 17.20 GB of Q4_K_M weights plus the 0.93 GB F16 projector, from the Hub's model information on 10 November 2026. Reach doesn't count it" }, { "name": "bartowski NousResearch_Arete-27B-GGUF (Q8_0)", "url": "https://huggingface.co/bartowski/NousResearch_Arete-27B-GGUF", "who": "bartowski", "precision": "q8_0", "sizeGB": 29.6, "memoryGB": 48, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "From bartowski, a third party's conversion and not Nous Research's. 28.67 GB of Q8_0 weights plus the 0.93 GB F16 projector, from the Hub's model information on 10 November 2026. Reach doesn't count it" }, { "name": "Arete-27B", "url": "https://huggingface.co/NousResearch/Arete-27B", "who": "publisher", "precision": "bf16", "sizeGB": 54.7, "memoryGB": 96, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)", "Transformers" ], "note": "The only build Nous Research publishes" } ], "run": "llama-server -hf bartowski/NousResearch_Arete-27B-GGUF:Q4_K_M --jinja", "runBuild": "bartowski NousResearch_Arete-27B-GGUF (Q4_K_M)", "checked": "2026-11-10", "minMemoryGB": 24 }, "family": { "lab": "Nous Research (NousResearch)", "family": "Arete", "url": "https://www.anchorterminal.com/open-weights/#nous-research" }, "area": "models", "provenance": { "legalEntity": "Nous Research, Inc. (named in the footer of nousresearch.com)", "domain": "nousresearch.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/NousResearch/Arete-27B/commits/main", "securityTxt": "none", "checked": "2026-11-10", "notes": [ "Nous Research, Inc. is the name in the site's footer, as the Hermes Agent listing records.", "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.", "The changelog is the repository's commit history, eight commits on 6 November 2026, the upload and updates to the card.", "The Hermes Agent listing found no security.txt on nousresearch.com. unchecked on 10 November.", "unchecked: the domain's registration date." ], "score": 61 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/arete-27b.json" }, "answer": "Inkling-Small scores 67 (B) on agent readiness against Arete-27B's 55.1 (C), and leads in every scored category.", "b": { "slug": "inkling-small", "name": "Inkling-Small", "vendor": "Thinking Machines Lab", "vendorUrl": "https://thinkingmachines.ai", "kind": "weights", "category": "open-weights", "summary": "Inkling-Small is Thinking Machines Lab's open-weight mixture-of-experts model, 276B total and 12B active parameters, taking text, images and audio and returning text, with adjustable thinking effort, published in BF16 and NVFP4 under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/inkling-small", "markdownUrl": "https://www.anchorterminal.com/tools/inkling-small.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/inkling-small.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inkling-small.json", "dns": "inkling-small.grade.anchorterminal.com", "repo": "https://huggingface.co/thinkingmachines/Inkling-Small", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "thinkingmachines/Inkling-Small" }, { "registry": "huggingface", "name": "thinkingmachines/Inkling-Small-NVFP4" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-10-21). 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, 531.9 GB for the BF16 files and 170.8 GB for the NVFP4 build. Thinking Machines' Tinker serves it as a beta serverless inference API at $0.30 per million input tokens and $1.20 per million output tokens (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": "2026-11-01" }, "docsUrl": "https://thinkingmachines.ai/model-card/inkling-small/", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "audio", "reasoning", "tool-calling", "apache-2.0", "safetensors", "nvfp4", "self-hosted" ], "lastRelease": "2026-07-31", "graded": true, "anchor": { "graded": true, "score": 67, "grade": "B", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1518, "categoryRank": 10, "methodology": "0.7", "run": "2026-10-01", "scores": { "capability": 63, "interface": 85, "reach": 55, "risk": 70, "upkeep": 87 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-11-01" }, "negative": 0, "verdict": "A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.", "bestFor": "Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.", "strengths": [ "Thinking Machines answered 8 of the 9 questions in its discussions", "Safetensors only, with a checksum on every LFS file in the publisher's own organisation", "Thinking effort set per request from none to the maximum, several tool calls a turn and a 1M-token context", "Released support in Transformers, vLLM and SGLang, with inkling tool and reasoning parsers", "A training-content summary with sources, mix and a July 2026 collection cut-off", "Thinking Machines' own Tinker hosts it as beta serverless inference", "Thinking Machines updated its Inkling renderer in tinker-cookbook on 30 October 2026" ], "weaknesses": [ "The smallest build Thinking Machines publishes needs about 205 GB", "Apache 2.0 comes with an acceptable use policy that binds on download and can change at any time", "No release of ggml-org's llama.cpp, Ollama or LM Studio runs it", "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" ], "agentNotes": [ "Start the NVFP4 build with SGLang's recipe, `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`, on Blackwell for W4A4", "Use the inkling tool and reasoning parsers in vLLM or SGLang, or Thinking Machines' tml-renderers package to render prompts and parse calls yourself", "Pass `reasoning_effort` as none, minimal, low, medium, high (the default) or max, or a number from 0 to 0.99. The repository's template has no xhigh preset and raises an error for it, though Thinking Machines' docs and SGLang's cookbook list xhigh", "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 and audio 16 kHz WAV under two minutes, per the card", "Use guided decoding or validate JSON yourself, since structured output isn't documented", "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": 4, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 67 } ], "editorialScores": { "capability": 63, "interface": 85, "reach": 55, "risk": 70, "upkeep": 87 }, "provenanceScore": 72, "checked": { "categories": { "capability": "2026-11-01", "interface": "2026-11-01", "reach": "2026-11-01", "risk": "2026-11-01", "upkeep": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# per SGLang's cookbook, NVFP4 on 8 Blackwell GPUs:\nsglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 \\\n --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling", "http": "curl http://localhost:30000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"model\": \"thinkingmachines/Inkling-Small-NVFP4\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n \"reasoning_effort\": \"low\"\n }'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/inkling-small" }, "sameCompany": [ "inkling-2-small", "inkling" ], "sameModel": [ "tinker" ], "weights": { "trainedBy": "Thinking Machines Lab", "params": "276B", "active": "12B", "context": 1048576, "goodFor": "Mixture-of-experts generalist for coding, agents and tool use with images and audio in, and thinking effort set per request.", "runtimes": [ "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Inkling-Small-NVFP4", "url": "https://huggingface.co/thinkingmachines/Inkling-Small-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 170.8, "memoryGB": 256, "format": "safetensors", "note": "NVFP4 experts with FP8 and BF16 parts. Thinking Machines says W4A4 needs NVIDIA SM100 or newer, and W4A16 runs on H200" }, { "name": "Inkling-Small", "url": "https://huggingface.co/thinkingmachines/Inkling-Small", "who": "publisher", "precision": "bf16", "sizeGB": 531.9, "memoryGB": 1024, "format": "safetensors" } ], "run": "sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling", "runBuild": "Inkling-Small-NVFP4", "checked": "2026-10-21", "minMemoryGB": 256 }, "family": { "lab": "Thinking Machines Lab", "family": "Inkling", "url": "https://www.anchorterminal.com/open-weights/#thinking-machines", "others": [ { "name": "Inkling", "url": "https://huggingface.co/thinkingmachines/Inkling", "params": "952.38B (Hub safetensors count; the name states none)", "listing": "https://www.anchorterminal.com/tools/inkling" } ], "unrestrictedCopies": 3 }, "area": "models", "provenance": { "legalEntity": "Thinking Machines Lab, Inc. (named on its model card page and in its training-content summary)", "domain": "thinkingmachines.ai", "domainRegistered": "", "domainNote": "thinkingmachines.ai's registration date wasn't read on 21 October 2026.", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/thinkingmachines/Inkling-Small/commits/main", "securityTxt": "valid", "checked": "2026-10-21", "notes": [ "Thinking Machines' model card page and launch post link 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, 12 commits from 27 to 31 July 2026, an upload, card updates and community evaluation results.", "thinkingmachines.ai/.well-known/security.txt gives a security contact, a PGP key and an expiry in 2029, and the site publishes a coordinated vulnerability disclosure policy that leaves model safety to a separate incident contact." ], "score": 72 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling-small.json", "live": { "slug": "inkling-small", "securityTxt": { "url": "https://thinkingmachines.ai/.well-known/security.txt", "state": "valid", "expires": "2029-07-13T07:00:00.000Z", "checkedAt": "2026-11-10T16:08:06.712462129Z" }, "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-Small/commits/main", "kind": "changelog", "status": 200, "checkedAt": "2026-11-10T16:23:48.468026384Z", "changedAt": "2026-11-10T16:23:48.468026384Z", "fingerprint": "286c2793f3d5" } ], "updatedAt": "2026-11-10T16:23:48.468026384Z" } }, "edges": [ { "by": 25, "category": "interface", "leads": "inkling-small", "name": "Agent interface", "reasons": { "a": "Chat template 20, a Jinja file in the repository. Tool-calling format 10, only the template says it. Trained tool calling 20, several calls a turn and agentic work as an intended use. Structured output 0 and reasoning control 0, neither is documented on the card. Context 10, 262,144 tokens native. 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, 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 the maximum, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens." }, "scores": { "a": 60, "b": 85 } }, { "by": 24, "category": "upkeep", "leads": "inkling-small", "name": "Documentation and upkeep", "reasons": { "a": "Model card 8, no limitations, context length, languages or cut-off. Training data 20, the training pairs and the evaluation set are published with their counts. Last change 20, a commit on 6 November 2026. Responsiveness 0, none of 13 discussions has a reply from Nous Research. Version policy 5, a first release. File health 10, the files agree. 8 + 20 + 20 + 0 + 5 + 10 = 63.", "b": "Model card 17 of 20, everything but a dated knowledge cut-off, counting Thinking Machines' own model card page. Training data 15, an EU training-content summary with sources, mix, a July 2026 collection cut-off and filtering. Last change 20, the files last changed on 31 July 2026, but Thinking Machines' Inkling renderer in tinker-cookbook changed in its 30 October 2026 release. Responsiveness 20, Thinking Machines answered 8 of the 9 questions in its discussions. Version policy 5, a first release. File health 10, the files agree and no broken-file report waits. 17+15+20+20+5+10 = 87." }, "scores": { "a": 63, "b": 87 } }, { "by": 15, "category": "risk", "leads": "inkling-small", "name": "Risk", "reasons": { "a": "File safety 25, safetensors only and no remote code. Provenance 15, Nous Research's own organisation, linked from its blog, with a hash on every file. Safety evaluation 0 and agent guidance 0, nothing published on either. Licence risk 15, plain Apache 2.0. Security programme 0, no way to report a flaw found. 25 + 15 + 0 + 0 + 15 + 0 = 55.", "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 and FORTRESS results and described external red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 10, the card says what its refusals miss and which safeguards to add, 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." }, "scores": { "a": 55, "b": 70 } }, { "by": 5, "category": "reach", "leads": "inkling-small", "name": "Reach", "reasons": { "a": "Memory 10, the only build from Nous Research is the 54.7 GB BF16 release, which needs about 66 GB and fits the reference machine. Runtimes 15, vLLM, SGLang and Transformers run the base's architecture from those files, and llama.cpp isn't credited because Nous Research publishes no GGUF. Builds 0, no quantised build of its own. Terms 15, Apache 2.0. Download 10, not gated. Hosted 0, no provider. 10 + 15 + 0 + 15 + 10 + 0 = 50.", "b": "Memory 5 of 30, the smallest 4-bit build is Thinking Machines' NVFP4 at 170.8 GB, about 205 GB with a fifth added, so it needs 256 GB. Runtimes 15, released Transformers, vLLM and SGLang run it, llama.cpp, Ollama and LM Studio don't. Builds 10, one quantised build (NVFP4). 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 DeepInfra is live on Hugging Face." }, "scores": { "a": 50, "b": 55 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Nous Research", "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": "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" }, { "a": "2026-11-06", "b": "2026-07-31", "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": "none", "b": "3.5/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Inkling-Small scores 67 (B) on agent readiness against Arete-27B's 55.1 (C), and leads in every scored category.", "question": "Which is better for AI agents, Arete-27B or Inkling-Small?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Agents that want Qwen3.8-27B's coding and tool use without its handling of politically sensitive topics, on a 24 GB card or a 128 GB machine", "slug": "arete-27b", "watchFor": "No quantised build from Nous Research, so the GGUF route depends on a third party" }, { "aheadOn": [ "Reach, 55 against 50", "Risk, 70 against 55", "Agent interface, 85 against 60", "Documentation and upkeep, 87 against 63" ], "also": null, "goodFor": "Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.", "slug": "inkling-small", "watchFor": "The smallest build Thinking Machines publishes needs about 205 GB" } ], "history": { "arete-27b": null, "inkling-small": [ { "causes": [ "product" ], "date": "2026-11-01", "delta": 0.5, "from": 66.5, "fromGrade": "B", "to": 67, "toGrade": "B" } ] }, "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-arete-27b.json", "title": "Agents-A1-4B vs Arete-27B", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-arete-27b" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-small.json", "title": "Agents-A1-4B vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-arete-27b.json", "title": "Apertus v1.5 8B vs Arete-27B", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-arete-27b" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-small.json", "title": "Apertus v1.5 8B vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-arete-27b.json", "title": "Apodex-1.1-mini vs Arete-27B", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-arete-27b" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-small.json", "title": "Apodex-1.1-mini vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-bigbang-v1.json", "title": "Arete-27B vs BigBang-v1", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-bigbang-v1" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-carbon-x.json", "title": "Arete-27B vs Carbon-X", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-carbon-x" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-cola2.json", "title": "Arete-27B vs Cola2", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-cola2" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-cosmos-reason2-2b.json", "title": "Arete-27B vs Cosmos-Reason2-2B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-cosmos-reason2-2b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-darwin-36b-opus.json", "title": "Arete-27B vs Darwin-36B-Opus", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-darwin-36b-opus" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-deepseek-v3-2.json", "title": "Arete-27B vs DeepSeek-V3.2", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-deepseek-v3-2" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-deepseek-v4-1-flash.json", "title": "Arete-27B vs DeepSeek V4.1 Flash", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-deepseek-v4-1-flash" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-deepseek-v4-flash-0731.json", "title": "Arete-27B vs DeepSeek-V4-Flash-0731", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-deepseek-v4-flash-0731" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-devstral-small-2.json", "title": "Arete-27B vs Devstral Small 2", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-devstral-small-2" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-diffusiongemma-26b-a4b-it.json", "title": "Arete-27B vs DiffusionGemma 26B A4B IT", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-diffusiongemma-26b-a4b-it" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-exaone-4-5-33b.json", "title": "Arete-27B vs EXAONE 4.5 33B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-exaone-4-5-33b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-gemma-4-12b-it.json", "title": "Arete-27B vs Gemma 4 12B IT", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-gemma-4-12b-it" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-gemma-4-26b-a4b-it.json", "title": "Arete-27B vs Gemma 4 26B A4B IT", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-gemma-4-26b-a4b-it" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-gemma-4-31b-it.json", "title": "Arete-27B vs Gemma 4 31B IT", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-gemma-4-31b-it" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-gemma-4-e2b-it.json", "title": "Arete-27B vs Gemma 4 E2B IT", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-gemma-4-e2b-it" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-gemma-4-e4b-it.json", "title": "Arete-27B vs Gemma 4 E4B IT", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-gemma-4-e4b-it" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-glm-4-5-air.json", "title": "Arete-27B vs GLM-4.5-Air", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-glm-4-5-air" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-glm-4-7-flash.json", "title": "Arete-27B vs GLM-4.7-Flash", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-glm-4-7-flash" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-glm-5-3.json", "title": "Arete-27B vs GLM-5.3", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-glm-5-3" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-glm-5-3-flash.json", "title": "Arete-27B vs GLM-5.3-Flash", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-glm-5-3-flash" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-gpt-oss-120b.json", "title": "Arete-27B vs gpt-oss-120b", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-gpt-oss-120b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-gpt-oss-20b.json", "title": "Arete-27B vs gpt-oss-20b", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-gpt-oss-20b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-granite-4-2-30b.json", "title": "Arete-27B vs Granite 4.2 30B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-granite-4-2-30b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-granite-4-2-3b.json", "title": "Arete-27B vs Granite 4.2 3B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-granite-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-granite-4-2-8b.json", "title": "Arete-27B vs Granite 4.2 8B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-granite-4-2-8b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-hy-memory-30b-a3b.json", "title": "Arete-27B vs Hy-Memory-30B-A3B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-hy-memory-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-hy3.json", "title": "Arete-27B vs Hy3", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-inkling.json", "title": "Arete-27B vs Inkling", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-internvl3-5-gpt-oss-20b-a4b-preview.json", "title": "Arete-27B vs InternVL3.5-GPT-OSS-20B-A4B-Preview", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-internvl3-5-gpt-oss-20b-a4b-preview" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-kimi-k3.json", "title": "Arete-27B vs Kimi K3", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-kimi-k3" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-kimi-k3-1-pro.json", "title": "Arete-27B vs Kimi K3.1 Pro", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-kimi-k3-1-pro" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-kolibri-1.json", "title": "Arete-27B vs Kolibri-1", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-kolibri-1" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-kronos.json", "title": "Arete-27B vs Kronos", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-kronos" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-m-1.json", "title": "Arete-27B vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-s-2-1.json", "title": "Arete-27B vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-xs-2-1.json", "title": "Arete-27B vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-lbs-27b.json", "title": "Arete-27B vs LBS-27B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-lbs-27b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm2-5-2-6b.json", "title": "Arete-27B vs LFM2.5-2.6B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm2-5-2-6b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-1-7b.json", "title": "Arete-27B vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-audio-2b.json", "title": "Arete-27B vs LFM3-Audio-2B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-audio-2b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-omni-2b.json", "title": "Arete-27B vs LFM3-Omni-2B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-omni-2b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-vl-2b.json", "title": "Arete-27B vs LFM3-VL-2B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-ling-3-0-tiny.json", "title": "Arete-27B vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-ling-3-0-tiny" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-ling-3-1-flash-1019.json", "title": "Arete-27B vs Ling-3.1-flash-1019", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-ling-3-1-flash-1019" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-longcat-2-5.json", "title": "Arete-27B vs LongCat-2.5", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-longcat-2-5" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Arete-27B vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-mimo-v2-6-flash-rl.json", "title": "Arete-27B vs MiMo-V2.6-Flash-RL", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-mimo-v2-6-flash-rl" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm-o-4-5.json", "title": "Arete-27B vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm-v-4-7-1b.json", "title": "Arete-27B vs MiniCPM-V 4.7 1B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm-v-4-7-1b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm-v-4-7-35b-a3b.json", "title": "Arete-27B vs MiniCPM-V 4.7 35B-A3B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm-v-4-7-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm5-2b.json", "title": "Arete-27B vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-minimax-m2-5.json", "title": "Arete-27B vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-minimax-m2-7.json", "title": "Arete-27B vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-minimax-m3-1-flash.json", "title": "Arete-27B vs MiniMax-M3.1-Flash", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-minimax-m3-1-flash" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-mistral-large-4.json", "title": "Arete-27B vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-muse-glimmer-30b.json", "title": "Arete-27B vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-nanbeige-4-2-3b.json", "title": "Arete-27B vs Nanbeige4.2-3B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-nanbeige-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-nanbeige-4-3-33b.json", "title": "Arete-27B vs Nanbeige4.3-33B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-nanbeige-4-3-33b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-5-bolt-e4b-4gb.json", "title": "Arete-27B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-5-bolt-e4b-4gb" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "Arete-27B vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-nano-30b-a3b.json", "title": "Arete-27B vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-nano-4b.json", "title": "Arete-27B vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "Arete-27B vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-super-120b-a12b.json", "title": "Arete-27B vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-ultra-550b-a55b.json", "title": "Arete-27B vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-north-mini-code-1-0.json", "title": "Arete-27B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-occamy-1-0.json", "title": "Arete-27B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/arete-27b-vs-olmo-3-7b-think.json", "title": "Arete-27B vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-olmo-3-7b-think" }, { "json": 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"title": "Inkling-Small vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-v-4-7-1b.json", "title": "Inkling-Small vs MiniCPM-V 4.7 1B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-v-4-7-1b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-v-4-7-35b-a3b.json", "title": "Inkling-Small vs MiniCPM-V 4.7 35B-A3B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm-v-4-7-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b.json", "title": "Inkling-Small vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-5.json", "title": "Inkling-Small vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-7.json", "title": "Inkling-Small vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m3-1-flash.json", "title": "Inkling-Small vs MiniMax-M3.1-Flash", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-minimax-m3-1-flash" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-mistral-large-4.json", "title": "Inkling-Small vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-muse-glimmer-30b.json", "title": "Inkling-Small vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nanbeige-4-2-3b.json", "title": "Inkling-Small vs Nanbeige4.2-3B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nanbeige-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nanbeige-4-3-33b.json", "title": "Inkling-Small vs Nanbeige4.3-33B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nanbeige-4-3-33b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-5-bolt-e4b-4gb.json", "title": "Inkling-Small vs NVIDIA Nemotron 3.5 Bolt E4B 4GB", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-5-bolt-e4b-4gb" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "Inkling-Small vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-30b-a3b.json", "title": "Inkling-Small vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-4b.json", "title": "Inkling-Small vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "Inkling-Small vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-super-120b-a12b.json", "title": "Inkling-Small vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-ultra-550b-a55b.json", "title": "Inkling-Small vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-north-mini-code-1-0.json", "title": "Inkling-Small vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-occamy-1-0.json", "title": "Inkling-Small vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-olmo-3-7b-think.json", "title": "Inkling-Small vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-122b.json", "title": "Inkling-Small vs Ornith-1.5-122B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-122b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-35b-a3b.json", "title": "Inkling-Small vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-397b.json", "title": "Inkling-Small vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-9b.json", "title": "Inkling-Small vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-otel-2-0-llm-31b-it.json", "title": "Inkling-Small vs OTel-2.0-LLM-31B-IT", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-otel-2-0-llm-31b-it" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen-agentworld-35b-a3b.json", "title": "Inkling-Small vs Qwen-AgentWorld-35B-A3B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen-agentworld-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Inkling-Small vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-4b-instruct-2507.json", "title": "Inkling-Small vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-0-8b.json", "title": "Inkling-Small vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-122b-a10b.json", "title": "Inkling-Small vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-2b.json", "title": "Inkling-Small vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-397b-a17b.json", "title": "Inkling-Small vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-4b.json", "title": "Inkling-Small vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-9b.json", "title": "Inkling-Small vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-6-27b.json", "title": "Inkling-Small vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-6-35b-a3b.json", "title": "Inkling-Small vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-27b.json", "title": "Inkling-Small vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-flash-next.json", "title": "Inkling-Small vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Inkling-Small vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-next.json", "title": "Inkling-Small vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Inkling-Small vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-2b-instruct.json", "title": "Inkling-Small vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Inkling-Small vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-32b-instruct.json", "title": "Inkling-Small vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-4b-instruct.json", "title": "Inkling-Small vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-8b-instruct.json", "title": "Inkling-Small vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwopus3-8-27b-flash-v2.json", "title": "Inkling-Small vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-recursive-flint.json", "title": "Inkling-Small vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-ripple-65b-preview.json", "title": "Inkling-Small vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-sensenova-loop-9b-preview.json", "title": "Inkling-Small vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-smollm3-3b.json", "title": "Inkling-Small vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-spark-x2-6-4b.json", "title": "Inkling-Small vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-step-3-7-flash.json", "title": "Inkling-Small vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-27b.json", "title": "Inkling-Small vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Inkling-Small vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-thinkingcap-qwen3-8-27b.json", "title": "Inkling-Small vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-unlimited-ocr-2.json", "title": "Inkling-Small vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-wevisone-vl-2b.json", "title": "Inkling-Small vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-wevisone-vl-4b.json", "title": "Inkling-Small vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-zaya1-8b.json", "title": "Inkling-Small vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-zaya1-8b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-inkling-small.json", "title": "Inkling vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/inkling-vs-inkling-small" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "arete-27b": 50, "by": 5, "edge": "inkling-small", "inkling-small": 55, "key": "reach", "name": "Reach", "weight": 25 }, { "arete-27b": 55, "by": 15, "edge": "inkling-small", "inkling-small": 70, "key": "risk", "name": "Risk", "weight": 20 }, { "arete-27b": 60, "by": 25, "edge": "inkling-small", "inkling-small": 85, "key": "interface", "name": "Agent interface", "weight": 10 }, { "arete-27b": 63, "by": 24, "edge": "inkling-small", "inkling-small": 87, "key": "upkeep", "name": "Documentation and upkeep", "weight": 10 } ], "summary": "Inkling-Small scores 67 (B) on agent readiness against Arete-27B's 55.1 (C), and leads in every scored category. Both do open-weight models you run yourself.", "tasks": null, "tutorials": [], "verdicts": { "arete-27b": "Qwen3.8-27B with its answers on politically sensitive topics retrained, four days old when read. The training data is published, which is rare. Nous Research ships BF16 only, so a small machine runs it from bartowski's GGUF, and the card documents none of the tool or thinking controls it inherits.", "inkling-small": "A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/arete-27b-vs-inkling-small", "json": "https://www.anchorterminal.com/compare/arete-27b-vs-inkling-small.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/arete-27b-vs-inkling-small.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/arete-27b-vs-inkling-small.min.md" }, "markdown": "Inkling-Small scores 67 (B) on agent readiness against Arete-27B's 55.1 (C), and leads in every scored category. Both do open-weight models you run yourself.\n\n- Arete-27B: grade C, 55.1/100, rank #123 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/arete-27b.md · JSON https://www.anchorterminal.com/api/v1/tools/arete-27b.json\n- Inkling-Small: grade B, 67/100, rank #13 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-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 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Arete-27B (C)\n\nGood for: Agents that want Qwen3.8-27B's coding and tool use without its handling of politically sensitive topics, on a 24 GB card or a 128 GB machine\n\nWatch for: No quantised build from Nous Research, so the GGUF route depends on a third party\n\n### Inkling-Small (B)\n\nGood for: Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.\n\nAhead on:\n- Reach, 55 against 50\n- Risk, 70 against 55\n- Agent interface, 85 against 60\n- Documentation and upkeep, 87 against 63\n\nWatch for: The smallest build Thinking Machines publishes needs about 205 GB\n\n\n## Why the edge\n\n### Agent interface: Inkling-Small +25\n\n- Arete-27B (60): Chat template 20, a Jinja file in the repository. Tool-calling format 10, only the template says it. Trained tool calling 20, several calls a turn and agentic work as an intended use. Structured output 0 and reasoning control 0, neither is documented on the card. Context 10, 262,144 tokens native. 20 + 10 + 20 + 0 + 0 + 10 = 60.\n- Inkling-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, 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 the maximum, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens.\n\n### Documentation and upkeep: Inkling-Small +24\n\n- Arete-27B (63): Model card 8, no limitations, context length, languages or cut-off. Training data 20, the training pairs and the evaluation set are published with their counts. Last change 20, a commit on 6 November 2026. Responsiveness 0, none of 13 discussions has a reply from Nous Research. Version policy 5, a first release. File health 10, the files agree. 8 + 20 + 20 + 0 + 5 + 10 = 63.\n- Inkling-Small (87): Model card 17 of 20, everything but a dated knowledge cut-off, counting Thinking Machines' own model card page. Training data 15, an EU training-content summary with sources, mix, a July 2026 collection cut-off and filtering. Last change 20, the files last changed on 31 July 2026, but Thinking Machines' Inkling renderer in tinker-cookbook changed in its 30 October 2026 release. Responsiveness 20, Thinking Machines answered 8 of the 9 questions in its discussions. Version policy 5, a first release. File health 10, the files agree and no broken-file report waits. 17+15+20+20+5+10 = 87.\n\n### Risk: Inkling-Small +15\n\n- Arete-27B (55): File safety 25, safetensors only and no remote code. Provenance 15, Nous Research's own organisation, linked from its blog, with a hash on every file. Safety evaluation 0 and agent guidance 0, nothing published on either. Licence risk 15, plain Apache 2.0. Security programme 0, no way to report a flaw found. 25 + 15 + 0 + 0 + 15 + 0 = 55.\n- Inkling-Small (70): 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 and FORTRESS results and described external red-teaming, but nothing an outside party published or a harness to rerun. Agent guidance 10, the card says what its refusals miss and which safeguards to add, 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.\n\n### Reach: Inkling-Small +5\n\n- Arete-27B (50): Memory 10, the only build from Nous Research is the 54.7 GB BF16 release, which needs about 66 GB and fits the reference machine. Runtimes 15, vLLM, SGLang and Transformers run the base's architecture from those files, and llama.cpp isn't credited because Nous Research publishes no GGUF. Builds 0, no quantised build of its own. Terms 15, Apache 2.0. Download 10, not gated. Hosted 0, no provider. 10 + 15 + 0 + 15 + 10 + 0 = 50.\n- Inkling-Small (55): Memory 5 of 30, the smallest 4-bit build is Thinking Machines' NVFP4 at 170.8 GB, about 205 GB with a fifth added, so it needs 256 GB. Runtimes 15, released Transformers, vLLM and SGLang run it, llama.cpp, Ollama and LM Studio don't. Builds 10, one quantised build (NVFP4). 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 DeepInfra is live on Hugging Face.\n\n## Score by category\n\n| Category | Weight | Arete-27B | Inkling-Small | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 50 | 55 | Inkling-Small +5 |\n| Risk | 20% (20 this run) | 55 | 70 | Inkling-Small +15 |\n| Agent interface | 10% (10 this run) | 60 | 85 | Inkling-Small +25 |\n| Documentation and upkeep | 10% (10 this run) | 63 | 87 | Inkling-Small +24 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **55.1 · C** | **67 · B** | |\n\n## Facts side by side\n\n| Fact | Arete-27B | Inkling-Small |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Nous Research | 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 | 2026-11-06 | 2026-07-31 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Agent reviews | none | 3.5/5 (4) |\n\n## How the scores have moved\n\n### Arete-27B\n\nNo score change since it was listed.\n\n### Inkling-Small\n\n- +0.5 on 1 November 2026: product\n\n## Verdicts\n\n**Arete-27B.** Qwen3.8-27B with its answers on politically sensitive topics retrained, four days old when read. The training data is published, which is rare. Nous Research ships BF16 only, so a small machine runs it from bartowski's GGUF, and the card documents none of the tool or thinking controls it inherits.\n\n**Inkling-Small.** A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.\n\n## Before you call either\n\n### Arete-27B\n\n1. Start it with `llama-server -hf bartowski/NousResearch_Arete-27B-GGUF:Q4_K_M --jinja`, a third party's conversion, or serve the BF16 files with vLLM\n2. Use the base's parsers in vLLM, `--reasoning-parser qwen3 --tool-call-parser qwen3_coder`, and check tool calls first, since the template differs slightly from Qwen3.8-27B's\n3. Thinking switches with `enable_thinking` in the template. The card's own evaluation ran with it off\n4. Expect answers on politically sensitive topics to differ from Qwen3.8-27B's. That is what the fine-tune is for\n5. Validate JSON output yourself, since structured output isn't documented\n\n### Inkling-Small\n\n1. Start the NVFP4 build with SGLang's recipe, `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`, on Blackwell for W4A4\n2. Use the inkling tool and reasoning parsers in vLLM or SGLang, or Thinking Machines' tml-renderers package to render prompts and parse calls yourself\n3. Pass `reasoning_effort` as none, minimal, low, medium, high (the default) or max, or a number from 0 to 0.99. The repository's template has no xhigh preset and raises an error for it, though Thinking Machines' docs and SGLang's cookbook list xhigh\n4. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens\n5. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error\n6. Images should be 40 to 4096 px a side and audio 16 kHz WAV under two minutes, per the card\n7. Use guided decoding or validate JSON yourself, since structured output isn't documented\n8. 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, Arete-27B or Inkling-Small?\n\nInkling-Small scores 67 (B) on agent readiness against Arete-27B's 55.1 (C), and leads in every scored category.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/arete-27b-vs-inkling-small.json, and with the fewest tokens: https://www.anchorterminal.com/compare/arete-27b-vs-inkling-small.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"arete-27b\", \"b\": \"inkling-small\"}`. From a terminal: `anchor compare arete-27b inkling-small`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/arete-27b.json and https://www.anchorterminal.com/api/v1/tools/inkling-small.json\n\n## Other comparisons with Arete-27B or Inkling-Small\n\n- [Agents-A1-4B vs Arete-27B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-arete-27b.md)\n- [Agents-A1-4B vs Inkling-Small](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-small.md)\n- [Apertus v1.5 8B vs Arete-27B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-arete-27b.md)\n- [Apertus v1.5 8B vs Inkling-Small](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-small.md)\n- [Apodex-1.1-mini vs Arete-27B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-arete-27b.md)\n- [Apodex-1.1-mini vs Inkling-Small](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-small.md)\n- [Arete-27B vs 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