{ "data": { "a": { "slug": "inkling", "name": "Inkling", "vendor": "Thinking Machines Lab", "vendorUrl": "https://thinkingmachines.ai", "kind": "weights", "category": "open-weights", "summary": "Inkling is Thinking Machines Lab's large open-weight mixture-of-experts model, 975B total and 41B 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", "markdownUrl": "https://www.anchorterminal.com/tools/inkling.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/inkling.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inkling.json", "dns": "inkling.grade.anchorterminal.com", "repo": "https://huggingface.co/thinkingmachines/Inkling", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "thinkingmachines/Inkling" }, { "registry": "huggingface", "name": "thinkingmachines/Inkling-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, 1,904.8 GB for the BF16 files and 592.0 GB for the NVFP4 build. Thinking Machines' Tinker serves it as a beta serverless inference API at $1.00 per million input tokens and $4.05 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": "2026-11-02" }, "docsUrl": "https://thinkingmachines.ai/model-card/inkling/", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "multimodal", "audio", "reasoning", "tool-calling", "apache-2.0", "safetensors", "nvfp4", "self-hosted" ], "lastRelease": "2026-07-23", "graded": true, "anchor": { "graded": true, "score": 64.7, "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": 14, "methodology": "0.7", "run": "2026-10-01", "scores": { "capability": 60, "interface": 85, "reach": 50, "risk": 70, "upkeep": 87 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-11-02" }, "negative": 0, "verdict": "Thinking Machines' large multimodal generalist, stronger than Inkling-Small on factual recall by its own numbers. It needs about 710 GB of datacentre GPU memory even in NVFP4, so most agents will use a host such as Together AI or Tinker. The main risks are a use policy that binds on download and can change, and no outside safety results.", "bestFor": "Agents calling a hosted open multimodal model with audio input, or teams with a multi-GPU datacentre node who want to run it themselves.", "strengths": [ "Three inference providers and Thinking Machines' own Tinker host it today", "Safetensors only, with a checksum on every LFS file in the publisher's own organisation", "Thinking effort set per request, several tool calls a turn and a 1M-token context", "Released support in Transformers, vLLM and SGLang, with inkling tool and reasoning parsers", "Thinking Machines answered 8 of the 12 questions and reports in its discussions", "A training-content summary with sources, mix and a July 2026 collection cut-off" ], "weaknesses": [ "The smallest build Thinking Machines publishes needs about 710 GB, beyond any single workstation", "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": [ "Unless you have a multi-GPU Blackwell or H200 node, call it through Together AI, Fireworks, DeepInfra or Tinker rather than starting it", "On 8 B200 GPUs, SGLang's recipe is `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-NVFP4 --tp 8 --quantization modelopt_fp4 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`", "Use the inkling tool parser, not Hermes, and the inkling reasoning parser", "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 list xhigh", "Tool call arguments must reach the template as an object, not a JSON string, or it raises an error", "Audio should be 16 kHz WAV, ideally under 20 minutes, and images 40 to 4096 px a side, per the card", "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, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 64.7 } ], "editorialScores": { "capability": 60, "interface": 85, "reach": 50, "risk": 70, "upkeep": 87 }, "provenanceScore": 71, "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": "# per SGLang's cookbook, NVFP4 on 8 B200 GPUs:\nsglang serve --trust-remote-code --model-path thinkingmachines/Inkling-NVFP4 --tp 8 \\\n --quantization modelopt_fp4 --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-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" }, "sameCompany": [ "inkling-2-small", "inkling-small" ], "sameModel": [ "tinker" ], "weights": { "trainedBy": "Thinking Machines Lab", "params": "975B", "active": "41B", "context": 1048576, "goodFor": "Large mixture-of-experts generalist for coding, agents, factual recall and audio, with images in and thinking effort set per request.", "runtimes": [ "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Inkling-NVFP4", "url": "https://huggingface.co/thinkingmachines/Inkling-NVFP4", "who": "publisher", "precision": "nvfp4", "sizeGB": 592, "memoryGB": 1024, "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", "url": "https://huggingface.co/thinkingmachines/Inkling", "who": "publisher", "precision": "bf16", "sizeGB": 1904.8, "memoryGB": 4096, "format": "safetensors", "note": "1,904.8 GB × 1.2 = 2,285.7 GB, so the 4,096 GB band. Thinking Machines states at least 2 TB of GPU memory" } ], "run": "sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-NVFP4 --tp 8 --quantization modelopt_fp4 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling", "runBuild": "Inkling-NVFP4", "checked": "2026-10-21", "minMemoryGB": 1024 }, "family": { "lab": "Thinking Machines Lab", "family": "Inkling", "url": "https://www.anchorterminal.com/open-weights/#thinking-machines", "others": [ { "name": "Inkling-Small", "url": "https://huggingface.co/thinkingmachines/Inkling-Small", "params": "265.96B (Hub safetensors count; the name states none)", "listing": "https://www.anchorterminal.com/tools/inkling-small" } ], "unrestrictedCopies": 1 }, "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/commits/main", "securityTxt": "valid", "checked": "2026-10-21", "notes": [ "Thinking Machines' Inkling page links the thinkingmachines collection on Hugging Face, and its model card page links the repository. Hugging Face hasn't verified the organisation.", "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, 13 commits from 15 to 23 July 2026, the upload, a Transformers processor and template change on 15 July, 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": 71 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling.json", "live": { "slug": "inkling", "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/commits/main", "kind": "changelog", "status": 200, "checkedAt": "2026-11-10T16:23:50.70345348Z", "changedAt": "2026-11-10T16:23:50.70345348Z", "fingerprint": "60baeb3c18bc" } ], "updatedAt": "2026-11-10T16:23:50.70345348Z" } }, "answer": "Inkling scores 64.7 (B) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in every scored category.", "b": { "slug": "sensenova-loop-9b-preview", "name": "SenseNova-Loop-9B-Preview", "vendor": "SenseTime (SenseNova)", "vendorUrl": "https://www.sensetime.com/en", "kind": "weights", "category": "open-weights", "summary": "SenseNova-Loop-9B-Preview is SenseTime's open-weight multimodal model of about 9B parameters. It runs 24 of its 32 decoder layers twice, with text and images in, tool calling, a thinking switch and a 256K context. Apache 2.0. No released runtime loads it.", "url": "https://www.anchorterminal.com/tools/sensenova-loop-9b-preview", "markdownUrl": "https://www.anchorterminal.com/tools/sensenova-loop-9b-preview.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/sensenova-loop-9b-preview.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/sensenova-loop-9b-preview.json", "dns": "sensenova-loop-9b-preview.grade.anchorterminal.com", "repo": "https://huggingface.co/sensenova/SenseNova-Loop-9B-Preview", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "sensenova/SenseNova-Loop-9B-Preview" } ], "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 under Apache 2.0. Running it yourself costs the hardware: the files are 38.1 GB because most weights are stored in 32-bit floats, and the card's example loads them as BF16 (checked 2026-11-10).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-10" }, "docsUrl": "https://github.com/OpenSenseNova/SenseNova-Loop", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "multimodal", "vision", "looped-transformer", "tool-calling", "reasoning", "long-context", "preview", "apache-2.0", "safetensors", "custom-code", "self-hosted" ], "lastRelease": "2026-11-02", "graded": true, "anchor": { "graded": true, "score": 46.8, "grade": "D", "agentReady": false, "rank": 0, "ranked": false, "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools", "rankOf": 1518, "categoryRank": 110, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 60, "reach": 40, "risk": 50, "upkeep": 44 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "An unusual architecture under Apache 2.0, with a 256K training context, a thinking switch and tool calling in the template. It's a preview in practice too: no released runtime runs it, loading it runs the repository's code, the files are twice the size the card implies, and nobody from SenseNova has answered a question yet.", "bestFor": "Researchers who want to study or fine-tune a looped transformer, more than agents that need a model to call today", "strengths": [ "Apache 2.0, ungated", "A 256K training context, stated on the card", "Thinking can be switched per request", "The architecture and parameter counts are documented", "Changed in the last ten days" ], "weaknesses": [ "No released runtime runs it. vLLM and SGLang need unmerged pull requests", "Loading it runs Python from the repository", "The files are 38.1 GB, mostly F32, though the card says BF16", "No quantised build", "No tool-calling documentation beyond the template", "No limitations, safety results or data sources, and the technical report isn't out", "None of 5 questions answered" ], "agentNotes": [ "Read modeling_sensenova_loop.py before you load it. trust_remote_code runs it", "Pin transformers 5.18.0, the version the card checked", "Load with dtype=torch.bfloat16 as the card does, or the 38 GB of F32 weights stay at full size", "Pass enable_thinking=False to apply_chat_template for a direct answer", "Tool calls come back as tool_call blocks with function and parameter tags. Parse them yourself, since no runtime ships a parser", "Wait for the vLLM or SGLang pull request to land in a release before putting it behind an API" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 46.8 } ], "editorialScores": { "interface": 60, "reach": 40, "risk": 50, "upkeep": 44 }, "provenanceScore": 51, "checked": { "categories": { "interface": "2026-11-10", "reach": "2026-11-10", "risk": "2026-11-10", "upkeep": "2026-11-10" }, "last": "2026-11-10", "oldest": "2026-11-10", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install \"transformers==5.18.0\" accelerate safetensors\n# then AutoModelForCausalLM.from_pretrained(\"sensenova/SenseNova-Loop-9B-Preview\", trust_remote_code=True, dtype=torch.bfloat16)\n# trust_remote_code runs modeling_sensenova_loop.py from the repository. Read it first", "http": "# No released server runs it. The card's vLLM and SGLang commands build from open pull requests,\n# and its LightLLM example serves an OpenAI-compatible API at http://localhost:8000/v1 on four GPUs" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/sensenova-loop-9b-preview" }, "weights": { "trainedBy": "SenseTime (SenseNova)", "params": "9B", "context": 262144, "goodFor": "Trying a looped transformer for long-context, tool-using work, if you can run the repository's own code on a large GPU.", "runtimes": [], "builds": [ { "name": "SenseNova-Loop-9B-Preview (safetensors, mostly F32)", "url": "https://huggingface.co/sensenova/SenseNova-Loop-9B-Preview/tree/main", "who": "publisher", "precision": "f32", "sizeGB": 38.14, "memoryGB": 48, "format": "safetensors", "note": "Eight shards and the MTP head. Stored mostly as 32-bit floats; the card's example loads it as BF16, about half the size in memory" } ], "run": "python -c \"from transformers import AutoModelForCausalLM; AutoModelForCausalLM.from_pretrained('sensenova/SenseNova-Loop-9B-Preview', trust_remote_code=True)\"", "runBuild": "SenseNova-Loop-9B-Preview (safetensors, mostly F32)", "checked": "2026-11-10", "minMemoryGB": 48 }, "family": { "lab": "SenseTime (SenseNova)", "family": "SenseNova-Loop", "url": "https://www.anchorterminal.com/open-weights/#sensenova" }, "area": "models", "provenance": { "legalEntity": "SenseTime, listed on the Stock Exchange of Hong Kong (00020) per its investor page. SenseNova is its foundation model series, per its site", "domain": "sensetime.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "https://github.com/OpenSenseNova/SenseNova-Loop/blob/main/LICENSE", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/sensenova/SenseNova-Loop-9B-Preview/commits/main", "securityTxt": "none", "checked": "2026-11-10", "notes": [ "The card names SenseNova only. SenseTime's site presents SenseNova as its foundation model series, and that is the tie between the two; the site wasn't read for a link to this repository.", "The domain's registration date wasn't looked up.", "Nothing is hosted under this listing, so Apache 2.0 stands in for terms of service and no privacy policy is scored.", "www.sensetime.com has no security.txt (404 on 10 November 2026). Its about page gives a security contact.", "The changelog is the commit history, 39 commits from 28 October to 2 November 2026." ], "score": 51 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/sensenova-loop-9b-preview.json" }, "edges": [ { "by": 43, "category": "upkeep", "leads": "inkling", "name": "Documentation and upkeep", "reasons": { "a": "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 weights files last changed on 23 July 2026, and Thinking Machines' Inkling renderer in tinker-cookbook changed on 30 October 2026, 3 days ago. Responsiveness 20, Thinking Machines answered 8 of the 12 questions and reports in its discussions. Version policy 5, a first release. File health 10, the files agree and the reports were answered.", "b": "Model card 14, Intended use, the architecture, the parameter counts, the training context and the languages (in the metadata) are on the card. Training data 5, one general sentence on the recipes, with no sources, sizes or cut-off. Last change 20, the last commit, on 2 November 2026, reworked the speculative decoding section of the card, 8 days before this check. Responsiveness 0, none of the 5 discussions that aren't pull requests (30 October to 9 November 2026) has a reply from a sensenova member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, A first release, labelled a preview, with dated news on the card. File health 0, the files contradict the card on precision. 14 + 5 + 20 + 0 + 5 + 0 = 44." }, "scores": { "a": 87, "b": 44 } }, { "by": 25, "category": "interface", "leads": "inkling", "name": "Agent interface", "reasons": { "a": "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, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens.", "b": "Chat template 20, chat_template.jinja in the repository (7,756 characters). Tool-calling format 10, only the template says it: a tools block, and calls written as tool_call blocks with function and parameter tags. Trained tool calling 10, the card says the training recipes include tool trajectories and that the model is for agentic workflows. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, the card documents enable_thinking in the chat template call, on or off per request, and the template puts the reasoning in think tags ahead of the answer. Context 10, 262,144 tokens in training, per the card's specification table, and config.json gives the language model 262,144 positions. 20 + 10 + 10 + 0 + 10 + 10 = 60." }, "scores": { "a": 85, "b": 60 } }, { "by": 20, "category": "risk", "leads": "inkling", "name": "Risk", "reasons": { "a": "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 commissioned external testers who published nothing. 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.", "b": "File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the sensenova organisation, which the GitHub repository for the model links to (10), and the Hub gives a SHA-256 for the large files (5). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on instructions inside tool results or images. Licence risk 15, Apache 2.0 with no use policy, no threshold and no right to change the terms. Security programme 5, SenseTime's about page gives a security contact (5). 15 + 15 + 0 + 0 + 15 + 5 = 50." }, "scores": { "a": 70, "b": 50 } }, { "by": 10, "category": "reach", "leads": "inkling", "name": "Reach", "reasons": { "a": "Memory 0 of 30, the smallest 4-bit build is Thinking Machines' NVFP4 at 592.0 GB, about 710 GB with a fifth added, far above 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, Together AI, Fireworks and DeepInfra are live on Hugging Face, and Thinking Machines' Tinker serves it too.", "b": "Memory 15, the only build is the safetensors set, 38.14 GB with its MTP head, since the Hub counts 9.41B of its parameters in F32. Runtimes 0, none of the six runs it in a released version. Builds 0, SenseNova publishes one set of weights and no quantised build. Terms 15, Apache 2.0 in the card's metadata and on the card, which links the LICENSE in the GitHub repository, and nothing added. Download 10, the Hub API reports gated false on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API that serves it. 15 + 0 + 0 + 15 + 10 + 0 = 40." }, "scores": { "a": 50, "b": 40 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Thinking Machines Lab", "b": "SenseTime (SenseNova)", "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": "2026-07-23", "b": "2026-11-02", "name": "Last release" }, { "a": "no document linked", "b": "not read yet", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "3/5 (4)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Inkling scores 64.7 (B) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in every scored category.", "question": "Which is better for AI agents, Inkling or SenseNova-Loop-9B-Preview?" } ], "goodFor": [ { "aheadOn": [ "Reach, 50 against 40", "Risk, 70 against 50", "Agent interface, 85 against 60", "Documentation and upkeep, 87 against 44" ], "also": null, "goodFor": "Agents calling a hosted open multimodal model with audio input, or teams with a multi-GPU datacentre node who want to run it themselves.", "slug": "inkling", "watchFor": "The smallest build Thinking Machines publishes needs about 710 GB, beyond any single workstation" }, { "aheadOn": null, "also": null, "goodFor": "Researchers who want to study or fine-tune a looped transformer, more than agents that need a model to call today", "slug": "sensenova-loop-9b-preview", "watchFor": "No released runtime runs it. vLLM and SGLang need unmerged pull requests" } ], "history": { "inkling": [ { "causes": [ "product" ], "date": "2026-11-02", "delta": 0.5, "from": 64.2, "fromGrade": "B", "to": 64.7, "toGrade": "B" } ], "sensenova-loop-9b-preview": null }, "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling.json", "title": "Agents-A1-4B vs Inkling", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-sensenova-loop-9b-preview.json", "title": "Agents-A1-4B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling.json", "title": "Apertus v1.5 8B vs Inkling", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-sensenova-loop-9b-preview.json", "title": "Apertus v1.5 8B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling.json", "title": "Apodex-1.1-mini vs Inkling", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-sensenova-loop-9b-preview.json", "title": "Apodex-1.1-mini vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-sensenova-loop-9b-preview" }, { "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-sensenova-loop-9b-preview.json", "title": "Arete-27B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/arete-27b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.json", "title": "BigBang-v1 vs Inkling", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-sensenova-loop-9b-preview.json", "title": "BigBang-v1 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling.json", "title": "Carbon-X vs Inkling", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/carbon-x-vs-sensenova-loop-9b-preview.json", "title": "Carbon-X vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/carbon-x-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/cola2-vs-inkling.json", "title": "Cola2 vs Inkling", "url": "https://www.anchorterminal.com/compare/cola2-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/cola2-vs-sensenova-loop-9b-preview.json", "title": "Cola2 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/cola2-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling.json", "title": "Cosmos-Reason2-2B vs Inkling", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-sensenova-loop-9b-preview.json", "title": "Cosmos-Reason2-2B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling.json", "title": "Darwin-36B-Opus vs Inkling", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-sensenova-loop-9b-preview.json", "title": "Darwin-36B-Opus vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling.json", "title": "DeepSeek-V3.2 vs Inkling", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-sensenova-loop-9b-preview.json", "title": "DeepSeek-V3.2 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling.json", "title": "DeepSeek V4.1 Flash vs Inkling", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-sensenova-loop-9b-preview.json", "title": "DeepSeek V4.1 Flash vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling.json", "title": "DeepSeek-V4-Flash-0731 vs Inkling", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-sensenova-loop-9b-preview.json", "title": "DeepSeek-V4-Flash-0731 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling.json", "title": "Devstral Small 2 vs Inkling", "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/devstral-small-2-vs-sensenova-loop-9b-preview.json", "title": "Devstral Small 2 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/devstral-small-2-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling.json", "title": "DiffusionGemma 26B A4B IT vs Inkling", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-sensenova-loop-9b-preview.json", "title": "DiffusionGemma 26B A4B IT vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling.json", "title": "EXAONE 4.5 33B vs Inkling", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-sensenova-loop-9b-preview.json", "title": "EXAONE 4.5 33B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling.json", "title": "Gemma 4 12B IT vs Inkling", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-sensenova-loop-9b-preview.json", "title": "Gemma 4 12B IT vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling.json", "title": "Gemma 4 26B A4B IT vs Inkling", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-sensenova-loop-9b-preview.json", "title": "Gemma 4 26B A4B IT vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling.json", "title": "Gemma 4 31B IT vs Inkling", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-sensenova-loop-9b-preview.json", "title": "Gemma 4 31B IT vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-inkling.json", "title": "Gemma 4 E2B IT vs Inkling", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-sensenova-loop-9b-preview.json", "title": "Gemma 4 E2B IT vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling.json", "title": "Gemma 4 E4B IT vs Inkling", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-sensenova-loop-9b-preview.json", "title": "Gemma 4 E4B IT vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling.json", "title": "GLM-4.5-Air vs Inkling", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-sensenova-loop-9b-preview.json", "title": "GLM-4.5-Air vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling.json", "title": "GLM-4.7-Flash vs Inkling", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-sensenova-loop-9b-preview.json", "title": "GLM-4.7-Flash vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling.json", "title": "GLM-5.3-Flash vs Inkling", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-sensenova-loop-9b-preview.json", "title": "GLM-5.3-Flash vs SenseNova-Loop-9B-Preview", "url": 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"https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling.json", "title": "gpt-oss-20b vs Inkling", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-sensenova-loop-9b-preview.json", "title": "gpt-oss-20b vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-inkling.json", "title": "Granite 4.2 30B vs Inkling", "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-sensenova-loop-9b-preview.json", "title": "Granite 4.2 30B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/granite-4-2-30b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-inkling.json", "title": "Granite 4.2 3B vs Inkling", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-sensenova-loop-9b-preview.json", "title": "Granite 4.2 3B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-inkling.json", "title": "Granite 4.2 8B vs Inkling", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-sensenova-loop-9b-preview.json", "title": "Granite 4.2 8B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/granite-4-2-8b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-inkling.json", "title": "Hy-Memory-30B-A3B vs Inkling", "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-sensenova-loop-9b-preview.json", "title": "Hy-Memory-30B-A3B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-inkling.json", "title": "Hy3 vs Inkling", "url": "https://www.anchorterminal.com/compare/hy3-vs-inkling" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-sensenova-loop-9b-preview.json", "title": "Hy3 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/hy3-vs-sensenova-loop-9b-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-vs-inkling-small.json", "title": "Inkling vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/inkling-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-internvl3-5-gpt-oss-20b-a4b-preview.json", "title": "Inkling vs InternVL3.5-GPT-OSS-20B-A4B-Preview", "url": "https://www.anchorterminal.com/compare/inkling-vs-internvl3-5-gpt-oss-20b-a4b-preview" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-kimi-k3.json", "title": "Inkling vs Kimi K3", "url": "https://www.anchorterminal.com/compare/inkling-vs-kimi-k3" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-kimi-k3-1-pro.json", "title": "Inkling vs Kimi K3.1 Pro", "url": "https://www.anchorterminal.com/compare/inkling-vs-kimi-k3-1-pro" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-kolibri-1.json", "title": "Inkling vs Kolibri-1", "url": "https://www.anchorterminal.com/compare/inkling-vs-kolibri-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-kronos.json", "title": "Inkling vs Kronos", "url": "https://www.anchorterminal.com/compare/inkling-vs-kronos" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-laguna-m-1.json", "title": "Inkling vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/inkling-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1.json", "title": "Inkling vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-laguna-xs-2-1.json", "title": "Inkling vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/inkling-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-lbs-27b.json", "title": "Inkling vs LBS-27B", "url": "https://www.anchorterminal.com/compare/inkling-vs-lbs-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-lfm2-5-2-6b.json", "title": "Inkling vs LFM2.5-2.6B", "url": "https://www.anchorterminal.com/compare/inkling-vs-lfm2-5-2-6b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-1-7b.json", "title": "Inkling vs LFM3-1.7B", "url": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-1-7b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-audio-2b.json", "title": "Inkling vs LFM3-Audio-2B", "url": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-audio-2b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-omni-2b.json", "title": "Inkling vs LFM3-Omni-2B", "url": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-omni-2b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-vl-2b.json", "title": "Inkling vs LFM3-VL-2B", "url": "https://www.anchorterminal.com/compare/inkling-vs-lfm3-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-ling-3-0-tiny.json", "title": "Inkling vs Ling-3.0-tiny", "url": 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"title": "Inkling vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-1b.json", "title": "Inkling vs MiniCPM-V 4.7 1B", "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-1b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-35b-a3b.json", "title": "Inkling vs MiniCPM-V 4.7 35B-A3B", "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b.json", "title": "Inkling vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-5.json", "title": "Inkling vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-7.json", "title": "Inkling vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m3-1-flash.json", "title": "Inkling vs MiniMax-M3.1-Flash", "url": "https://www.anchorterminal.com/compare/inkling-vs-minimax-m3-1-flash" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-mistral-large-4.json", "title": "Inkling vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/inkling-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-muse-glimmer-30b.json", "title": "Inkling vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/inkling-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-nanbeige-4-2-3b.json", "title": "Inkling vs Nanbeige4.2-3B", "url": "https://www.anchorterminal.com/compare/inkling-vs-nanbeige-4-2-3b" }, { "json": 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}, { "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-4b.json", "title": "Inkling vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-9b.json", "title": "Inkling vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-6-27b.json", "title": "Inkling vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-6-35b-a3b.json", "title": "Inkling vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-8-27b.json", "title": "Inkling vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-8-27b" }, { "json": 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Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Inkling vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-32b-instruct.json", "title": "Inkling vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-4b-instruct.json", "title": "Inkling vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-8b-instruct.json", "title": "Inkling vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-vl-8b-instruct" }, { "json": 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}, { "json": "https://www.anchorterminal.com/compare/inkling-vs-step-3-7-flash.json", "title": "Inkling vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/inkling-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-27b.json", "title": "Inkling vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-flash-next.json", "title": "Inkling vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/inkling-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-thinkingcap-qwen3-8-27b.json", "title": "Inkling vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/inkling-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-unlimited-ocr-2.json", "title": "Inkling vs Baidu 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"https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-sensenova-loop-9b-preview.json", "title": "LFM3-VL-2B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/lfm3-vl-2b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-sensenova-loop-9b-preview.json", "title": "Ling-3.0-tiny vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-sensenova-loop-9b-preview.json", "title": "Ling-3.1-flash-1019 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/ling-3-1-flash-1019-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/longcat-2-5-vs-sensenova-loop-9b-preview.json", "title": "LongCat-2.5 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/longcat-2-5-vs-sensenova-loop-9b-preview" }, { "json": 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SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-sensenova-loop-9b-preview.json", "title": "MiniMax-M3.1-Flash vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/mistral-large-4-vs-sensenova-loop-9b-preview.json", "title": "Mistral Large 4 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/mistral-large-4-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-sensenova-loop-9b-preview.json", "title": "Muse Glimmer 30B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-sensenova-loop-9b-preview.json", "title": "Nanbeige4.2-3B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/nanbeige-4-2-3b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-sensenova-loop-9b-preview.json", "title": "Nanbeige4.3-33B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/nanbeige-4-3-33b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-sensenova-loop-9b-preview.json", "title": "NVIDIA Nemotron 3.5 Bolt E4B 4GB vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-bolt-e4b-4gb-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-sensenova-loop-9b-preview.json", "title": "Nemotron 3.5 Lightning 30B A3B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-sensenova-loop-9b-preview.json", "title": "Nemotron 3 Nano 30B A3B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-sensenova-loop-9b-preview.json", "title": "Nemotron 3 Nano 4B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-sensenova-loop-9b-preview.json", "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-sensenova-loop-9b-preview.json", "title": "Nemotron 3 Super 120B A12B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-sensenova-loop-9b-preview.json", "title": "Nemotron 3 Ultra 550B A55B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-sensenova-loop-9b-preview.json", "title": "North Mini Code 1.0 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/north-mini-code-1-0-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-sensenova-loop-9b-preview.json", "title": "occamy-1.0 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-sensenova-loop-9b-preview" }, { "json": 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"title": "Qwen3-30B-A3B-Instruct-2507 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-sensenova-loop-9b-preview.json", "title": "Qwen3-4B-Instruct-2507 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-sensenova-loop-9b-preview.json", "title": "Qwen3.5-0.8B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-sensenova-loop-9b-preview.json", "title": "Qwen3.5-122B-A10B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-5-122b-a10b-vs-sensenova-loop-9b-preview" }, { "json": 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"https://www.anchorterminal.com/compare/qwen3-6-27b-vs-sensenova-loop-9b-preview.json", "title": "Qwen3.6-27B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-6-27b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-sensenova-loop-9b-preview.json", "title": "Qwen3.6-35B-A3B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-6-35b-a3b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-sensenova-loop-9b-preview.json", "title": "Qwen3.8-27B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-8-27b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-sensenova-loop-9b-preview.json", "title": "Qwen3.8-Flash-Next vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-8-flash-next-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-sensenova-loop-9b-preview.json", "title": "Qwen3-Coder-30B-A3B-Instruct vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-coder-30b-a3b-instruct-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-sensenova-loop-9b-preview.json", "title": "Qwen3-Coder-Next vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-coder-next-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-sensenova-loop-9b-preview.json", "title": "Qwen3-Omni-30B-A3B-Instruct vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-omni-30b-a3b-instruct-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-sensenova-loop-9b-preview.json", "title": "Qwen3-VL-2B-Instruct vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-vl-2b-instruct-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-sensenova-loop-9b-preview.json", "title": "Qwen3-VL-30B-A3B-Instruct vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-vl-30b-a3b-instruct-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-sensenova-loop-9b-preview.json", "title": "Qwen3-VL-32B-Instruct vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-vl-32b-instruct-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-sensenova-loop-9b-preview.json", "title": "Qwen3-VL-4B-Instruct vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-vl-4b-instruct-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-sensenova-loop-9b-preview.json", "title": "Qwen3-VL-8B-Instruct vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwen3-vl-8b-instruct-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-sensenova-loop-9b-preview.json", "title": "Qwopus3.8-27B-Flash-V2 vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/qwopus3-8-27b-flash-v2-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/recursive-flint-vs-sensenova-loop-9b-preview.json", "title": "Recursive Flint vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/recursive-flint-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/ripple-65b-preview-vs-sensenova-loop-9b-preview.json", "title": "Ripple-65B Preview vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/ripple-65b-preview-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-smollm3-3b.json", "title": "SenseNova-Loop-9B-Preview vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-spark-x2-6-4b.json", "title": "SenseNova-Loop-9B-Preview vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-step-3-7-flash.json", "title": "SenseNova-Loop-9B-Preview vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-swift-1-5-qwen3-8-27b.json", "title": "SenseNova-Loop-9B-Preview vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-swift-1-5-qwen3-8-flash-next.json", "title": "SenseNova-Loop-9B-Preview vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-thinkingcap-qwen3-8-27b.json", "title": "SenseNova-Loop-9B-Preview vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-unlimited-ocr-2.json", "title": "SenseNova-Loop-9B-Preview vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-wevisone-vl-2b.json", "title": "SenseNova-Loop-9B-Preview vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-wevisone-vl-4b.json", "title": "SenseNova-Loop-9B-Preview vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-zaya1-8b.json", "title": "SenseNova-Loop-9B-Preview vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-zaya1-8b" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 10, "edge": "inkling", "inkling": 50, "key": "reach", "name": "Reach", "sensenova-loop-9b-preview": 40, "weight": 25 }, { "by": 20, "edge": "inkling", "inkling": 70, "key": "risk", "name": "Risk", "sensenova-loop-9b-preview": 50, "weight": 20 }, { "by": 25, "edge": "inkling", "inkling": 85, "key": "interface", "name": "Agent interface", "sensenova-loop-9b-preview": 60, "weight": 10 }, { "by": 43, "edge": "inkling", "inkling": 87, "key": "upkeep", "name": "Documentation and upkeep", "sensenova-loop-9b-preview": 44, "weight": 10 } ], "summary": "Inkling scores 64.7 (B) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in every scored category. Both do open-weight models you run yourself.", "tasks": null, "tutorials": [], "verdicts": { "inkling": "Thinking Machines' large multimodal generalist, stronger than Inkling-Small on factual recall by its own numbers. It needs about 710 GB of datacentre GPU memory even in NVFP4, so most agents will use a host such as Together AI or Tinker. The main risks are a use policy that binds on download and can change, and no outside safety results.", "sensenova-loop-9b-preview": "An unusual architecture under Apache 2.0, with a 256K training context, a thinking switch and tool calling in the template. It's a preview in practice too: no released runtime runs it, loading it runs the repository's code, the files are twice the size the card implies, and nobody from SenseNova has answered a question yet." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/inkling-vs-sensenova-loop-9b-preview", "json": "https://www.anchorterminal.com/compare/inkling-vs-sensenova-loop-9b-preview.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/inkling-vs-sensenova-loop-9b-preview.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/inkling-vs-sensenova-loop-9b-preview.min.md" }, "markdown": "Inkling scores 64.7 (B) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in every scored category. Both do open-weight models you run yourself.\n\n- Inkling: grade B, 64.7/100, rank #19 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling.json\n- SenseNova-Loop-9B-Preview: grade D, 46.8/100, rank #155 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/sensenova-loop-9b-preview.md · JSON https://www.anchorterminal.com/api/v1/tools/sensenova-loop-9b-preview.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### Inkling (B)\n\nGood for: Agents calling a hosted open multimodal model with audio input, or teams with a multi-GPU datacentre node who want to run it themselves.\n\nAhead on:\n- Reach, 50 against 40\n- Risk, 70 against 50\n- Agent interface, 85 against 60\n- Documentation and upkeep, 87 against 44\n\nWatch for: The smallest build Thinking Machines publishes needs about 710 GB, beyond any single workstation\n\n### SenseNova-Loop-9B-Preview (D)\n\nGood for: Researchers who want to study or fine-tune a looped transformer, more than agents that need a model to call today\n\nWatch for: No released runtime runs it. vLLM and SGLang need unmerged pull requests\n\n\n## Why the edge\n\n### Documentation and upkeep: Inkling +43\n\n- Inkling (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 weights files last changed on 23 July 2026, and Thinking Machines' Inkling renderer in tinker-cookbook changed on 30 October 2026, 3 days ago. Responsiveness 20, Thinking Machines answered 8 of the 12 questions and reports in its discussions. Version policy 5, a first release. File health 10, the files agree and the reports were answered.\n- SenseNova-Loop-9B-Preview (44): Model card 14, Intended use, the architecture, the parameter counts, the training context and the languages (in the metadata) are on the card. Training data 5, one general sentence on the recipes, with no sources, sizes or cut-off. Last change 20, the last commit, on 2 November 2026, reworked the speculative decoding section of the card, 8 days before this check. Responsiveness 0, none of the 5 discussions that aren't pull requests (30 October to 9 November 2026) has a reply from a sensenova member, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, A first release, labelled a preview, with dated news on the card. File health 0, the files contradict the card on precision. 14 + 5 + 20 + 0 + 5 + 0 = 44.\n\n### Agent interface: Inkling +25\n\n- Inkling (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, and the reasoning comes back in reasoning_content. Context 10, up to 1M tokens.\n- SenseNova-Loop-9B-Preview (60): Chat template 20, chat_template.jinja in the repository (7,756 characters). Tool-calling format 10, only the template says it: a tools block, and calls written as tool_call blocks with function and parameter tags. Trained tool calling 10, the card says the training recipes include tool trajectories and that the model is for agentic workflows. Structured output 0, Nothing on the card about JSON or schema-constrained output. Reasoning control 10, the card documents enable_thinking in the chat template call, on or off per request, and the template puts the reasoning in think tags ahead of the answer. Context 10, 262,144 tokens in training, per the card's specification table, and config.json gives the language model 262,144 positions. 20 + 10 + 10 + 0 + 10 + 10 = 60.\n\n### Risk: Inkling +20\n\n- Inkling (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 commissioned external testers who published nothing. 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- SenseNova-Loop-9B-Preview (50): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the sensenova organisation, which the GitHub repository for the model links to (10), and the Hub gives a SHA-256 for the large files (5). Safety evaluation 0, no safety results on the card. Agent guidance 0, the card has no limitations or safety section, and nothing on instructions inside tool results or images. Licence risk 15, Apache 2.0 with no use policy, no threshold and no right to change the terms. Security programme 5, SenseTime's about page gives a security contact (5). 15 + 15 + 0 + 0 + 15 + 5 = 50.\n\n### Reach: Inkling +10\n\n- Inkling (50): Memory 0 of 30, the smallest 4-bit build is Thinking Machines' NVFP4 at 592.0 GB, about 710 GB with a fifth added, far above 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, Together AI, Fireworks and DeepInfra are live on Hugging Face, and Thinking Machines' Tinker serves it too.\n- SenseNova-Loop-9B-Preview (40): Memory 15, the only build is the safetensors set, 38.14 GB with its MTP head, since the Hub counts 9.41B of its parameters in F32. Runtimes 0, none of the six runs it in a released version. Builds 0, SenseNova publishes one set of weights and no quantised build. Terms 15, Apache 2.0 in the card's metadata and on the card, which links the LICENSE in the GitHub repository, and nothing added. Download 10, the Hub API reports gated false on 10 November 2026, so the files download with no account and nothing to accept. Hosted 0, Hugging Face maps no inference provider to it, and the card names no API that serves it. 15 + 0 + 0 + 15 + 10 + 0 = 40.\n\n## Score by category\n\n| Category | Weight | Inkling | SenseNova-Loop-9B-Preview | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 50 | 40 | Inkling +10 |\n| Risk | 20% (20 this run) | 70 | 50 | Inkling +20 |\n| Agent interface | 10% (10 this run) | 85 | 60 | Inkling +25 |\n| Documentation and upkeep | 10% (10 this run) | 87 | 44 | Inkling +43 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **64.7 · B** | **46.8 · D** | |\n\n## Facts side by side\n\n| Fact | Inkling | SenseNova-Loop-9B-Preview |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Thinking Machines Lab | SenseTime (SenseNova) |\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 | 2026-07-23 | 2026-11-02 |\n| Terms last updated | no document linked | not read yet |\n| Privacy policy last updated | no document linked | no document linked |\n| Agent reviews | 3/5 (4) | none |\n\n## How the scores have moved\n\n### Inkling\n\n- +0.5 on 2 November 2026: product\n\n### SenseNova-Loop-9B-Preview\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Inkling.** Thinking Machines' large multimodal generalist, stronger than Inkling-Small on factual recall by its own numbers. It needs about 710 GB of datacentre GPU memory even in NVFP4, so most agents will use a host such as Together AI or Tinker. The main risks are a use policy that binds on download and can change, and no outside safety results.\n\n**SenseNova-Loop-9B-Preview.** An unusual architecture under Apache 2.0, with a 256K training context, a thinking switch and tool calling in the template. It's a preview in practice too: no released runtime runs it, loading it runs the repository's code, the files are twice the size the card implies, and nobody from SenseNova has answered a question yet.\n\n## Before you call either\n\n### Inkling\n\n1. Unless you have a multi-GPU Blackwell or H200 node, call it through Together AI, Fireworks, DeepInfra or Tinker rather than starting it\n2. On 8 B200 GPUs, SGLang's recipe is `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-NVFP4 --tp 8 --quantization modelopt_fp4 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`\n3. Use the inkling tool parser, not Hermes, and the inkling reasoning parser\n4. 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 list xhigh\n5. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error\n6. Audio should be 16 kHz WAV, ideally under 20 minutes, and images 40 to 4096 px a side, per the card\n7. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal\n\n### SenseNova-Loop-9B-Preview\n\n1. Read modeling_sensenova_loop.py before you load it. trust_remote_code runs it\n2. Pin transformers 5.18.0, the version the card checked\n3. Load with dtype=torch.bfloat16 as the card does, or the 38 GB of F32 weights stay at full size\n4. Pass enable_thinking=False to apply_chat_template for a direct answer\n5. Tool calls come back as tool_call blocks with function and parameter tags. Parse them yourself, since no runtime ships a parser\n6. Wait for the vLLM or SGLang pull request to land in a release before putting it behind an API\n\n## Questions\n\n### Which is better for AI agents, Inkling or SenseNova-Loop-9B-Preview?\n\nInkling scores 64.7 (B) on agent readiness against SenseNova-Loop-9B-Preview's 46.8 (D), and leads in every scored category.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/inkling-vs-sensenova-loop-9b-preview.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-vs-sensenova-loop-9b-preview.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"inkling\", \"b\": \"sensenova-loop-9b-preview\"}`. From a terminal: `anchor compare inkling sensenova-loop-9b-preview`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling.json and https://www.anchorterminal.com/api/v1/tools/sensenova-loop-9b-preview.json\n\n## Other comparisons with Inkling or SenseNova-Loop-9B-Preview\n\n- [Agents-A1-4B vs Inkling](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling.md)\n- [Agents-A1-4B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/agents-a1-4b-vs-sensenova-loop-9b-preview.md)\n- [Apertus v1.5 8B vs Inkling](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling.md)\n- [Apertus v1.5 8B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-sensenova-loop-9b-preview.md)\n- [Apodex-1.1-mini vs Inkling](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling.md)\n- [Apodex-1.1-mini vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-sensenova-loop-9b-preview.md)\n- [Arete-27B vs Inkling](https://www.anchorterminal.com/compare/arete-27b-vs-inkling.md)\n- [Arete-27B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/arete-27b-vs-sensenova-loop-9b-preview.md)\n- [BigBang-v1 vs Inkling](https://www.anchorterminal.com/compare/bigbang-v1-vs-inkling.md)\n- [BigBang-v1 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/bigbang-v1-vs-sensenova-loop-9b-preview.md)\n- [Carbon-X vs Inkling](https://www.anchorterminal.com/compare/carbon-x-vs-inkling.md)\n- [Carbon-X vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/carbon-x-vs-sensenova-loop-9b-preview.md)\n- [Cola2 vs Inkling](https://www.anchorterminal.com/compare/cola2-vs-inkling.md)\n- [Cola2 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/cola2-vs-sensenova-loop-9b-preview.md)\n- [Cosmos-Reason2-2B vs Inkling](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-inkling.md)\n- [Cosmos-Reason2-2B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-sensenova-loop-9b-preview.md)\n- [Darwin-36B-Opus vs Inkling](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-inkling.md)\n- [Darwin-36B-Opus vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-sensenova-loop-9b-preview.md)\n- [DeepSeek-V3.2 vs Inkling](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling.md)\n- [DeepSeek-V3.2 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-sensenova-loop-9b-preview.md)\n- [DeepSeek V4.1 Flash vs Inkling](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-inkling.md)\n- [DeepSeek V4.1 Flash vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-sensenova-loop-9b-preview.md)\n- [DeepSeek-V4-Flash-0731 vs Inkling](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-inkling.md)\n- [DeepSeek-V4-Flash-0731 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-sensenova-loop-9b-preview.md)\n- [Devstral Small 2 vs Inkling](https://www.anchorterminal.com/compare/devstral-small-2-vs-inkling.md)\n- [Devstral Small 2 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/devstral-small-2-vs-sensenova-loop-9b-preview.md)\n- [DiffusionGemma 26B A4B IT vs Inkling](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-inkling.md)\n- [DiffusionGemma 26B A4B IT vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-sensenova-loop-9b-preview.md)\n- [EXAONE 4.5 33B vs Inkling](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-inkling.md)\n- [EXAONE 4.5 33B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-sensenova-loop-9b-preview.md)\n- [Gemma 4 12B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-inkling.md)\n- [Gemma 4 12B IT vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-sensenova-loop-9b-preview.md)\n- [Gemma 4 26B A4B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-inkling.md)\n- [Gemma 4 26B A4B IT vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-sensenova-loop-9b-preview.md)\n- [Gemma 4 31B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-inkling.md)\n- [Gemma 4 31B IT vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-sensenova-loop-9b-preview.md)\n- [Gemma 4 E2B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-inkling.md)\n- [Gemma 4 E2B IT vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-sensenova-loop-9b-preview.md)\n- [Gemma 4 E4B IT vs Inkling](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-inkling.md)\n- [Gemma 4 E4B IT vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-sensenova-loop-9b-preview.md)\n- [GLM-4.5-Air vs Inkling](https://www.anchorterminal.com/compare/glm-4-5-air-vs-inkling.md)\n- [GLM-4.5-Air vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/glm-4-5-air-vs-sensenova-loop-9b-preview.md)\n- [GLM-4.7-Flash vs Inkling](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-inkling.md)\n- [GLM-4.7-Flash vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-sensenova-loop-9b-preview.md)\n- [GLM-5.3-Flash vs Inkling](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-inkling.md)\n- [GLM-5.3-Flash vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-sensenova-loop-9b-preview.md)\n- [GLM-5.3 vs Inkling](https://www.anchorterminal.com/compare/glm-5-3-vs-inkling.md)\n- [GLM-5.3 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/glm-5-3-vs-sensenova-loop-9b-preview.md)\n- [gpt-oss-120b vs Inkling](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-inkling.md)\n- [gpt-oss-120b vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-sensenova-loop-9b-preview.md)\n- [gpt-oss-20b vs Inkling](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-inkling.md)\n- [gpt-oss-20b vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-sensenova-loop-9b-preview.md)\n- [Granite 4.2 30B vs Inkling](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-inkling.md)\n- [Granite 4.2 30B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-sensenova-loop-9b-preview.md)\n- [Granite 4.2 3B vs Inkling](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-inkling.md)\n- [Granite 4.2 3B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-sensenova-loop-9b-preview.md)\n- [Granite 4.2 8B vs Inkling](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-inkling.md)\n- [Granite 4.2 8B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-sensenova-loop-9b-preview.md)\n- [Hy-Memory-30B-A3B vs Inkling](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-inkling.md)\n- [Hy-Memory-30B-A3B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-sensenova-loop-9b-preview.md)\n- [Hy3 vs Inkling](https://www.anchorterminal.com/compare/hy3-vs-inkling.md)\n- [Hy3 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/hy3-vs-sensenova-loop-9b-preview.md)\n- [Inkling-Small vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/inkling-small-vs-sensenova-loop-9b-preview.md)\n- [Inkling vs 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vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/inkling-vs-minicpm-o-4-5.md)\n- [Inkling vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-1b.md)\n- [Inkling vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/inkling-vs-minicpm-v-4-7-35b-a3b.md)\n- [Inkling vs MiniCPM5-2B](https://www.anchorterminal.com/compare/inkling-vs-minicpm5-2b.md)\n- [Inkling vs MiniMax-M2.5](https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-5.md)\n- [Inkling vs MiniMax-M2.7](https://www.anchorterminal.com/compare/inkling-vs-minimax-m2-7.md)\n- [Inkling vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/inkling-vs-minimax-m3-1-flash.md)\n- [Inkling vs Mistral Large 4](https://www.anchorterminal.com/compare/inkling-vs-mistral-large-4.md)\n- [Inkling vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/inkling-vs-muse-glimmer-30b.md)\n- [Inkling vs 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SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-sensenova-loop-9b-preview.md)\n- [OTel-2.0-LLM-31B-IT vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/otel-2-0-llm-31b-it-vs-sensenova-loop-9b-preview.md)\n- [Qwen-AgentWorld-35B-A3B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen-agentworld-35b-a3b-vs-sensenova-loop-9b-preview.md)\n- [Qwen3-30B-A3B-Instruct-2507 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-sensenova-loop-9b-preview.md)\n- [Qwen3-4B-Instruct-2507 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-sensenova-loop-9b-preview.md)\n- [Qwen3.5-0.8B vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/qwen3-5-0-8b-vs-sensenova-loop-9b-preview.md)\n- [Qwen3.5-122B-A10B vs 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[SenseNova-Loop-9B-Preview vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-unlimited-ocr-2.md)\n- [SenseNova-Loop-9B-Preview vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-wevisone-vl-2b.md)\n- [SenseNova-Loop-9B-Preview vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-wevisone-vl-4b.md)\n- [SenseNova-Loop-9B-Preview vs ZAYA1-8B](https://www.anchorterminal.com/compare/sensenova-loop-9b-preview-vs-zaya1-8b.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-11", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": 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