{ "data": { "a": { "slug": "cola2", "name": "Cola2", "vendor": "ByteDance (Seed)", "vendorUrl": "https://github.com/ByteDance-Seed", "kind": "weights", "category": "open-weights", "summary": "Cola2 is a research checkpoint from ByteDance Seed, a base language model of 8.8B parameters that generates text through continuous latents with a diffusion transformer and a token decoder. Not a chat model, and the weights carry no stated licence.", "url": "https://www.anchorterminal.com/tools/cola2", "markdownUrl": "https://www.anchorterminal.com/tools/cola2.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/cola2.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/cola2.json", "dns": "cola2.grade.anchorterminal.com", "repo": "https://huggingface.co/ByteDance-Seed/Cola2", "license": "None stated for the weights (the code is Apache 2.0)", "transports": [], "packages": [ { "registry": "huggingface", "name": "ByteDance-Seed/Cola2" } ], "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, but nothing says what you may do with the weights. The card says the code is Apache 2.0 and that the weights remain subject to their respective terms, without naming them. Running it yourself costs the hardware: 35.1 GB of F32 files, loaded as BF16 in the card's example (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/ByteDance-Seed/Cola2", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "base-model", "research", "diffusion", "continuous-latent", "no-licence", "safetensors", "custom-code", "self-hosted" ], "lastRelease": "2026-11-06", "graded": true, "anchor": { "graded": true, "score": 33.9, "grade": "F", "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": 113, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 20, "reach": 25, "risk": 40, "upkeep": 58 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-10" }, "negative": 0, "verdict": "A research release, and an honest one: ByteDance Seed says it's a base model with an unconverged latent stage, scoring below Llama-3-8B on its own table. It's here for people studying continuous-latent generation. Agents can't use it as a model: 32-token completions, no chat or tools, the repository's own code to load it, and no licence on the weights.", "bestFor": "Researchers working on latent or diffusion language models who want a checkpoint to study", "strengths": [ "A documented new architecture with a paper and a reproduction protocol", "Evaluation data and checksums ship with the weights", "A security policy that points to ByteDance's security centre", "The model card says plainly what it isn't for" ], "weaknesses": [ "No licence stated for the weights", "A base model: no chat, no tools, 32 new tokens by default", "Loads only with the repository's own Python, on Transformers 4.x", "35 GB of F32 files and no quantised build", "Below Llama-3-8B on the card's own eight-task table", "No stated context length or cut-off" ], "agentNotes": [ "Don't plan to use this as your model. It completes short prompts and wasn't tuned to follow instructions", "Don't use it commercially on the strength of this listing. The weights have no stated licence", "If you study it, read modeling_cola2.py first: trust_remote_code runs it", "Pin Transformers below 5, as the card requires", "Pass a seeded torch.Generator to generate(). Output varies between runs even with greedy decoding", "Check the download with `sha256sum -c SHA256SUMS`" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "F", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 33.9 } ], "editorialScores": { "interface": 20, "reach": 25, "risk": 40, "upkeep": 58 }, "provenanceScore": 58, "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 \"torch\u003e=2.2\" \"transformers\u003e=4.51,\u003c5\" \"safetensors\u003e=0.4\" accelerate\n# then AutoModel.from_pretrained(\"ByteDance-Seed/Cola2\", trust_remote_code=True, torch_dtype=torch.bfloat16)\n# trust_remote_code runs the three Python files in the repository. Read them first", "http": "# No server. The model runs in process through Transformers, and the GitHub repository has a\n# command-line chat script (scripts/run_chat.sh) and a benchmark runner" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/cola2" }, "weights": { "trainedBy": "ByteDance Seed", "builtOn": "The decoder and encoder embedding are initialised from Qwen3-4B-Base, per the GitHub model card", "params": "8.8B", "goodFor": "Research on continuous-latent text generation: short completions, cloze and multiple-choice experiments, and reproducing the paper's numbers.", "runtimes": [], "builds": [ { "name": "Cola2 (F32 safetensors)", "url": "https://huggingface.co/ByteDance-Seed/Cola2/tree/main", "who": "publisher", "precision": "f32", "sizeGB": 35.07, "memoryGB": 48, "format": "safetensors", "note": "Eight shards in 32-bit floats. The card's example loads them as BF16" } ], "run": "python -c \"from transformers import AutoModel; AutoModel.from_pretrained('ByteDance-Seed/Cola2', trust_remote_code=True)\"", "runBuild": "Cola2 (F32 safetensors)", "checked": "2026-11-10", "minMemoryGB": 48 }, "family": { "lab": "ByteDance (Seed)", "family": "Cola", "url": "https://www.anchorterminal.com/open-weights/#bytedance-seed", "others": [ { "name": "Cola-DLM", "url": "https://huggingface.co/ByteDance-Seed/Cola-DLM" } ] }, "area": "models", "provenance": { "legalEntity": "ByteDance, named in the GitHub repository's security policy. The legal entity wasn't looked up", "domain": "bytedance.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://huggingface.co/ByteDance-Seed/Cola2/commits/main", "securityTxt": "unknown", "checked": "2026-11-10", "notes": [ "The files are in the ByteDance-Seed organisation on Hugging Face and the code is in the ByteDance-Seed organisation on GitHub; each links the other.", "No licence is stated for the weights, so there are no terms to read.", "The domain's registration date and security.txt weren't looked up. The GitHub repository's SECURITY.md points to ByteDance's security centre.", "The changelog is the commit history, six commits on 6 November 2026." ], "score": 58 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/cola2.json" }, "answer": "MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep.", "b": { "slug": "mimo-v2-6-distill-qwen-9b", "name": "MiMo-V2.6 Distill Qwen 9B", "vendor": "Xiaomi (MiMo team)", "vendorUrl": "https://mimo.xiaomi.com", "kind": "weights", "category": "open-weights", "summary": "MiMo-V2.6 Distill Qwen 9B is Xiaomi's open-weight 9B agentic model, Qwen3.5-9B fine-tuned on data generated by MiMo-V2.6 for coding, agent, visual coding and cybersecurity tasks, released in BF16 under MIT as a starting point for RL research.", "url": "https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b", "markdownUrl": "https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-distill-qwen-9b.json", "dns": "mimo-v2-6-distill-qwen-9b.grade.anchorterminal.com", "repo": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B", "license": "MIT (metadata only, no LICENSE file); built on Qwen3.5-9B under Apache 2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under MIT on the card and Apache 2.0 for the Qwen3.5-9B base. Xiaomi's MiMo API serves the larger MiMo-V2.6 models, not this one. Running it yourself costs the hardware, 18.8 GB for the BF16 files (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-03" }, "docsUrl": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "dense", "multimodal", "reasoning", "tool-calling", "derivative", "distillation", "mit", "safetensors", "self-hosted" ], "lastRelease": "2026-09-21", "graded": true, "anchor": { "graded": true, "score": 61, "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": 37, "methodology": "0.7", "run": "2026-10-01", "scores": { "interface": 70, "reach": 80, "risk": 65, "upkeep": 40 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-03" }, "negative": 0, "verdict": "A 9B cousin tuned on MiMo-V2.6's agent work for coding, terminal tasks and visual coding, released as a base for RL research. Ollama's library build needs about 8 GB at 4-bit, while Xiaomi ships only BF16. The main risks are no safety results while a seventh of its tuning is offensive security, and nobody at Xiaomi answering reports.", "bestFor": "Researchers and agents that want a small coding and terminal-agent model to fine-tune further on a 24 GB GPU, or to run at 4-bit through Ollama in about 8 GB.", "strengths": [ "Runs on Qwen3.5-9B's architecture, so released vLLM, SGLang, Transformers and llama.cpp load it, and Ollama's library carries it at 4-bit and 8-bit", "MIT over an Apache 2.0 base, no gate, no account and no use policy", "Safetensors only in Xiaomi's own organisation, with a checksum on every file", "The fine-tuning mix is published by domain with token counts, and a technical report covers it", "Several tool calls a turn, thinking switched per request and 262,144 tokens of context from the base" ], "weaknesses": [ "Only BF16 from Xiaomi, about 23 GB to run; the smaller builds are Ollama's", "No safety results or agent guidance beyond general cautions, with 11.0B tokens of offensive-security tuning", "No reply from Xiaomi to any of its 14 discussions, including template and tool-call reports", "No LICENSE file and no copy of the base's Apache 2.0 text, and the card has no limitations, context, languages or cut-off", "The tool format and parser aren't documented on the card" ], "agentNotes": [ "Quickest start is `ollama run mimo-v2.6:9b`, Ollama's 6.6 GB q4_K_M build with text and image input", "Serve it as the card does, `sglang serve --model-path XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B --reasoning-parser mimo`, and add `--tool-call-parser mimo` for parsed tool calls", "SGLang's mimo reasoning parser expects thinking to be asked for, so pass `chat_template_kwargs` with `enable_thinking` true, as the card does, and read `reasoning_content`", "Calls come back as function and parameter blocks inside tool_call, the same shape vLLM's and SGLang's qwen3_coder parsers read", "The generation config samples at temperature 0.6, top_k 20 and top_p 0.95", "Images and video go in through Qwen3.5's processor; the template's audio tokens have no audio encoder behind them", "The MTP head isn't in the files, so skip MTP speculative decoding even though config.json lists a layer", "It's an SFT checkpoint meant for further RL, and discussions report runaway generation on llama.cpp, so cap max_tokens", "If you redistribute the weights, include the Apache 2.0 text of Qwen3.5-9B, which section 4(a) asks for and the repository lacks" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.3, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 61 } ], "editorialScores": { "interface": 70, "reach": 80, "risk": 65, "upkeep": 40 }, "provenanceScore": 47, "checked": { "categories": { "interface": "2026-11-03", "reach": "2026-11-03", "risk": "2026-11-03", "upkeep": "2026-11-03" }, "last": "2026-11-03", "lastMoved": "2026-11-03", "oldest": "2026-11-03", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "sglang serve --model-path XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B \\\n --reasoning-parser mimo --tool-call-parser mimo --host 0.0.0.0 --port 30000\n# or, with llama.cpp and llama.cpp's own GGUF:\nllama-server -hf ggml-org/MiMo-V2.6-Distill-Qwen-9B-GGUF:Q8_0 --jinja", "http": "curl http://localhost:30000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"chat_template_kwargs\": {\"enable_thinking\": true}}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/mimo-v2-6-distill-qwen-9b" }, "sameCompany": [ "mimo-v2-6-flash-rl" ], "weights": { "trainedBy": "Xiaomi (MiMo team)", "builtOn": "Qwen/Qwen3.5-9B (supervised fine-tune on data generated by MiMo-V2.6; base Apache 2.0, declared in the card's metadata)", "params": "9.41B", "context": 262144, "goodFor": "A 9B agentic model for coding, terminal and tool tasks, with images in, meant as a starting point for RL fine-tuning.", "runtimes": [ "llama.cpp", "Ollama", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "ollama mimo-v2.6:9b-q4_K_M", "url": "https://ollama.com/library/mimo-v2.6:9b-q4_K_M", "who": "ollama", "precision": "q4_k_m", "sizeGB": 6.6, "memoryGB": 8, "format": "ollama", "runsOn": [ "Ollama" ], "note": "Size as Ollama's tags page shows it (the default 9b tag is listed at 6.6 to 8.7 GB across formats), text and image input, 256K context. Ollama also lists 9b-q8_0 (10 GB), 9b-mxfp8 (11 GB), 9b-nvfp4 (8.7 GB) and BF16 GGUF and MLX builds (19 GB)" }, { "name": "ggml-org MiMo-V2.6-Distill-Qwen-9B-GGUF (Q8_0)", "url": "https://huggingface.co/ggml-org/MiMo-V2.6-Distill-Qwen-9B-GGUF", "who": "llama.cpp", "precision": "q8_0", "sizeGB": 10.15, "memoryGB": 16, "format": "gguf", "runsOn": [ "llama.cpp" ], "note": "From ggml-org, the llama.cpp project's organisation. 9.53 GB of Q8_0 weights plus the 0.62 GB Q8_0 vision projector, from the Hub's model information on 10 November 2026. Recorded after the last grading, so Reach doesn't count it yet" }, { "name": "MiMo-V2.6-Distill-Qwen-9B", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B", "who": "publisher", "precision": "bf16", "sizeGB": 18.85, "memoryGB": 24, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)", "Transformers" ], "note": "Xiaomi's only build" } ], "run": "sglang serve --model-path XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B --reasoning-parser mimo --tool-call-parser mimo --context-length 131072 --port 30000", "runBuild": "MiMo-V2.6-Distill-Qwen-9B", "checked": "2026-11-03", "minMemoryGB": 8 }, "family": { "lab": "Xiaomi (MiMo)", "family": "MiMo-V2 (V2, V2.5, V2.6)", "url": "https://www.anchorterminal.com/open-weights/#xiaomi", "others": [ { "name": "MiMo-V2.6-Pro-MOPD", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Pro-MOPD", "params": "1024.22B (Hub safetensors count; the name states none)" }, { "name": "MiMo-V2.6-Flash-MOPD", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-MOPD", "params": "310.76B (Hub safetensors count; the name states none)" }, { "name": "MiMo-V2.6-Pro-RL", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Pro-RL", "params": "1024.22B (Hub safetensors count; the name states none)" }, { "name": "MiMo-V2.6-Flash-RL", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL", "params": "310.76B (Hub safetensors count; the name states none)", "listing": "https://www.anchorterminal.com/tools/mimo-v2-6-flash-rl" }, { "name": "MiMo-V2.5-Pro-Base", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.5-Pro-Base", "params": "1023.18B (Hub safetensors count; the name states none)" }, { "name": "MiMo-V2.5-Pro", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.5-Pro", "params": "1023.18B (Hub safetensors count; the name states none)" }, { "name": "MiMo-V2.5-Base", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.5-Base", "params": "310.76B (Hub safetensors count; the name states none)" }, { "name": "MiMo-V2.5", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.5", "params": "310.76B (Hub safetensors count; the name states none)" }, { "name": "MiMo-V2.5-ASR", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2.5-ASR", "params": "7.62B (Hub safetensors count; the name states none)" }, { "name": "MiMo-V2-Flash-Base", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2-Flash-Base", "params": "309.77B (Hub safetensors count; the name states none)" }, { "name": "MiMo-V2-Flash", "url": "https://huggingface.co/XiaomiMiMo/MiMo-V2-Flash", "params": "309.77B (Hub safetensors count; the name states none)" } ], "olderCount": 12, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "Xiaomi (the card and report name Xiaomi MiMo; no LICENSE file names a copyright holder)", "domain": "mimo.xiaomi.com", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-11-03", "notes": [ "The Hugging Face organisation XiaomiMiMo isn't verified. mimo.xiaomi.com links to it, and the MiMo-V2.6 technical report links this repository.", "Nothing is hosted for this model, so the licence stands in for terms of service and no privacy policy is scored.", "No changelog. The six commits are the upload on 21 September 2026, a README update on 22 September and two README updates on 28 October.", "mimo.xiaomi.com has no security.txt (404) and www.mi.com's returns 403. Xiaomi runs a company security centre at sec.xiaomi.com, which no MiMo page links." ], "score": 47 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.json", "live": { "slug": "mimo-v2-6-distill-qwen-9b", "securityTxt": { "url": "https://mimo.xiaomi.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-10T16:07:46.192470354Z" }, "domain": { "domain": "xiaomi.com", "registered": "2003-07-22", "source": "https://rdap.verisign.com/com/v1/domain/xiaomi.com", "checkedAt": "2026-11-08T15:08:19.964915329Z" }, "updatedAt": "2026-11-10T16:07:46.192470354Z" } }, "edges": [ { "by": 55, "category": "reach", "leads": "mimo-v2-6-distill-qwen-9b", "name": "Reach", "reasons": { "a": "Memory 15, the only build is the F32 safetensors set, 35.07 GB, and 35.07 GB × 1.2 = 42.1 GB, within 64 GB. Loaded as BF16, as the card's example does, it needs about half, but the line reads the file size. Runtimes 0, none of the six runs it in a released version. Builds 0, one set of weights and no quantised build. Terms 0, no licence for the weights. 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 nothing names an API that serves it. 15 + 0 + 0 + 0 + 10 + 0 = 25.", "b": "Memory 30 of 30, Ollama's library build at q4_K_M is 6.6 GB, 7.9 GB with a fifth added, while Xiaomi's only build is BF16 at 18.85 GB. Runtimes 25, it keeps Qwen3.5-9B's architecture, which released vLLM, SGLang, Transformers and llama.cpp run, and Ollama's own library carries this model (entry updated 3 November 2026; the 21 October check found none). Builds 0, Xiaomi publishes no quantised build. Terms 15, MIT on the card over an Apache 2.0 base, both with nothing added. Download 10, not gated. Hosted 0, no provider serves this distill." }, "scores": { "a": 25, "b": 80 } }, { "by": 50, "category": "interface", "leads": "mimo-v2-6-distill-qwen-9b", "name": "Agent interface", "reasons": { "a": "Chat template 20, A chat template in tokenizer_config.json (4,116 characters), which came with the Qwen3 tokenizer. Tool-calling format 0, none. Trained tool calling 0, not trained for tool calling. Structured output 0, Nothing about JSON or schema-constrained output. Reasoning control 0, no reasoning mode. Context 0, no context length is stated. 20 + 0 + 0 + 0 + 0 + 0 = 20.", "b": "Chat template 20, a Jinja file in the repository. Tool-calling format 10 of 25, the format is only in the template and the card names no tool parser. Trained tool calling 20, several calls a turn and agentic fine-tuning. Structured output 0, not documented. Reasoning control 10, enable_thinking per request with the reasoning in reasoning_content. Context 10, 262,144 tokens from the base's native length, though the card doesn't say." }, "scores": { "a": 20, "b": 70 } }, { "by": 25, "category": "risk", "leads": "mimo-v2-6-distill-qwen-9b", "name": "Risk", "reasons": { "a": "File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the ByteDance-Seed organisation, which the ByteDance-Seed GitHub repository for the model links to (10). Safety evaluation 0, no safety results. Agent guidance 5, General cautions in the GitHub model card: not instruction-tuned or safety-aligned, not for use as an assistant, for facts or advice, or for high-impact decisions about people. Licence risk 0, With no licence for the weights there is nothing to hold ByteDance to. Security programme 5, the GitHub repository's SECURITY.md sends reports to ByteDance's security centre and says how they're assessed (5). 15 + 15 + 0 + 5 + 0 + 5 = 40.", "b": "File safety 25, safetensors only and no repository code runs. Provenance 15, the files are in Xiaomi's MiMo organisation, which mimo.xiaomi.com links to, with a checksum on every file. Safety evaluation 0, the technical report has no safety results. Agent guidance 5, the card's Use Restrictions section (28 October 2026) gives general cautions, with nothing on prompt injection, refusals or safeguards. Licence risk 15, MIT and Apache 2.0 with no conditions, and the card says its restrictions add none. Security programme 5 of 10, Xiaomi's company security centre takes reports, but nothing links it to MiMo and no advisories were found." }, "scores": { "a": 40, "b": 65 } }, { "by": 18, "category": "upkeep", "leads": "cola2", "name": "Documentation and upkeep", "reasons": { "a": "Model card 8, Intended use and limitations (the out-of-scope list, and the unconverged latent model) and the architecture are on the card and the GitHub model card it links. Training data 15, the GitHub model card names the source (OLMo 2 pretraining text, retokenised) and the mix by stage with token counts, 346.03B in all. Last change 20, All six commits are from 6 November 2026, four days before this check, the last one updating a checksum in the README. Responsiveness 0, no discussions on the repository, so nobody has asked anything yet and the line reads as none answered, as settled in calibration. Version policy 5, A first release. File health 10, Config, files and card agree: F32 weights, a float32 config and a card that says to load them as bfloat16, with SHA256SUMS to check the download. 8 + 15 + 20 + 0 + 5 + 10 = 58.", "b": "Model card 5 of 20, intended use and parameters only. Training data 5, a domain mix with token counts but no sources or cut-off. Last change 20, README updates on 28 October 2026. Responsiveness 0, Xiaomi answered none of the 14 discussions. Version policy 5, a first release. File health 5, no LICENSE file, a config that lists an MTP layer the weights lack, and template and tool-call reports waiting without a reply." }, "scores": { "a": 58, "b": 40 } } ], "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "ByteDance (Seed)", "b": "Xiaomi (MiMo team)", "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": "None stated for the weights (the code is Apache 2.0)", "b": "MIT (metadata only, no LICENSE file); built on Qwen3.5-9B under 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": "2026-09-21", "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": "2.3/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep.", "question": "Which is better for AI agents, Cola2 or MiMo-V2.6 Distill Qwen 9B?" } ], "goodFor": [ { "aheadOn": [ "Documentation and upkeep, 58 against 40" ], "also": null, "goodFor": "Researchers working on latent or diffusion language models who want a checkpoint to study", "slug": "cola2", "watchFor": "No licence stated for the weights" }, { "aheadOn": [ "Reach, 80 against 25", "Risk, 65 against 40", "Agent interface, 70 against 20" ], "also": null, "goodFor": "Researchers and agents that want a small coding and terminal-agent model to fine-tune further on a 24 GB GPU, or to run at 4-bit through Ollama in about 8 GB.", "slug": "mimo-v2-6-distill-qwen-9b", "watchFor": "Only BF16 from Xiaomi, about 23 GB to run; the smaller builds are Ollama's" } ], "history": { "cola2": null, "mimo-v2-6-distill-qwen-9b": [ { "causes": [ "product" ], "date": "2026-11-03", "delta": 0, "from": 61, "fromGrade": "C", "to": 61, "toGrade": "C" } ] }, "job": { 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"json": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Hy-Memory-30B-A3B vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Hy3 vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/hy3-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/inkling-small-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Inkling-Small vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/inkling-small-vs-mimo-v2-6-distill-qwen-9b" }, { "json": "https://www.anchorterminal.com/compare/inkling-vs-mimo-v2-6-distill-qwen-9b.json", "title": "Inkling vs MiMo-V2.6 Distill Qwen 9B", "url": "https://www.anchorterminal.com/compare/inkling-vs-mimo-v2-6-distill-qwen-9b" }, { "json": 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4.7 1B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minicpm-v-4-7-1b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minicpm-v-4-7-35b-a3b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs MiniCPM-V 4.7 35B-A3B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minicpm-v-4-7-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minicpm5-2b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minimax-m2-5.json", "title": "MiMo-V2.6 Distill Qwen 9B vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minimax-m2-7.json", "title": "MiMo-V2.6 Distill Qwen 9B vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minimax-m3-1-flash.json", "title": "MiMo-V2.6 Distill Qwen 9B vs MiniMax-M3.1-Flash", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-minimax-m3-1-flash" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-mistral-large-4.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Mistral Large 4", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-mistral-large-4" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-muse-glimmer-30b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nanbeige-4-2-3b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Nanbeige4.2-3B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nanbeige-4-2-3b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nanbeige-4-3-33b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Nanbeige4.3-33B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nanbeige-4-3-33b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-5-bolt-e4b-4gb.json", "title": "MiMo-V2.6 Distill Qwen 9B vs NVIDIA Nemotron 3.5 Bolt E4B 4GB", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-5-bolt-e4b-4gb" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-30b-a3b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-4b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-super-120b-a12b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-ultra-550b-a55b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-north-mini-code-1-0.json", "title": "MiMo-V2.6 Distill Qwen 9B vs North Mini Code 1.0", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-north-mini-code-1-0" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-occamy-1-0.json", "title": "MiMo-V2.6 Distill Qwen 9B vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-occamy-1-0" }, { "json": 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"title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-4b-instruct-2507.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-0-8b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-122b-a10b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-2b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-397b-a17b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-4b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-9b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-6-27b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-6-35b-a3b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-27b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-flash-next.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-coder-30b-a3b-instruct.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-coder-next.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-omni-30b-a3b-instruct.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-2b-instruct.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-30b-a3b-instruct.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-32b-instruct.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-4b-instruct.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-8b-instruct.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwopus3-8-27b-flash-v2.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-recursive-flint.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Recursive Flint", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-recursive-flint" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-ripple-65b-preview.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Ripple-65B Preview", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-ripple-65b-preview" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-sensenova-loop-9b-preview.json", "title": "MiMo-V2.6 Distill Qwen 9B vs SenseNova-Loop-9B-Preview", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-sensenova-loop-9b-preview" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-smollm3-3b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-spark-x2-6-4b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-step-3-7-flash.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Step 3.7 Flash", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-step-3-7-flash" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-swift-1-5-qwen3-8-27b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-swift-1-5-qwen3-8-flash-next.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-thinkingcap-qwen3-8-27b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-thinkingcap-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-unlimited-ocr-2.json", "title": "MiMo-V2.6 Distill Qwen 9B vs Baidu Unlimited-OCR-2", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-unlimited-ocr-2" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-wevisone-vl-2b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs WeVisOne-VL-2B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-wevisone-vl-2b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-wevisone-vl-4b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs WeVisOne-VL-4B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-wevisone-vl-4b" }, { "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-zaya1-8b.json", "title": "MiMo-V2.6 Distill Qwen 9B vs ZAYA1-8B", "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-zaya1-8b" } ], "panel": null, "scores": [ { "key": "capability", "name": "Capability", "pending": true, "weight": 35 }, { "by": 55, "cola2": 25, "edge": "mimo-v2-6-distill-qwen-9b", "key": "reach", "mimo-v2-6-distill-qwen-9b": 80, "name": "Reach", "weight": 25 }, { "by": 25, "cola2": 40, "edge": "mimo-v2-6-distill-qwen-9b", "key": "risk", "mimo-v2-6-distill-qwen-9b": 65, "name": "Risk", "weight": 20 }, { "by": 50, "cola2": 20, "edge": "mimo-v2-6-distill-qwen-9b", "key": "interface", "mimo-v2-6-distill-qwen-9b": 70, "name": "Agent interface", "weight": 10 }, { "by": 18, "cola2": 58, "edge": "cola2", "key": "upkeep", "mimo-v2-6-distill-qwen-9b": 40, "name": "Documentation and upkeep", "weight": 10 } ], "summary": "MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep. Both do open-weight models you run yourself.", "tasks": null, "tutorials": [], "verdicts": { "cola2": "A research release, and an honest one: ByteDance Seed says it's a base model with an unconverged latent stage, scoring below Llama-3-8B on its own table. It's here for people studying continuous-latent generation. Agents can't use it as a model: 32-token completions, no chat or tools, the repository's own code to load it, and no licence on the weights.", "mimo-v2-6-distill-qwen-9b": "A 9B cousin tuned on MiMo-V2.6's agent work for coding, terminal tasks and visual coding, released as a base for RL research. Ollama's library build needs about 8 GB at 4-bit, while Xiaomi ships only BF16. The main risks are no safety results while a seventh of its tuning is offensive security, and nobody at Xiaomi answering reports." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/cola2-vs-mimo-v2-6-distill-qwen-9b", "json": "https://www.anchorterminal.com/compare/cola2-vs-mimo-v2-6-distill-qwen-9b.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/cola2-vs-mimo-v2-6-distill-qwen-9b.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/cola2-vs-mimo-v2-6-distill-qwen-9b.min.md" }, "markdown": "MiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep. Both do open-weight models you run yourself.\n\n- Cola2: grade F, 33.9/100, rank #160 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/cola2.md · JSON https://www.anchorterminal.com/api/v1/tools/cola2.json\n- MiMo-V2.6 Distill Qwen 9B: grade C, 61/100, rank #47 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/mimo-v2-6-distill-qwen-9b.md · JSON https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-distill-qwen-9b.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### Cola2 (F)\n\nGood for: Researchers working on latent or diffusion language models who want a checkpoint to study\n\nAhead on:\n- Documentation and upkeep, 58 against 40\n\nWatch for: No licence stated for the weights\n\n### MiMo-V2.6 Distill Qwen 9B (C)\n\nGood for: Researchers and agents that want a small coding and terminal-agent model to fine-tune further on a 24 GB GPU, or to run at 4-bit through Ollama in about 8 GB.\n\nAhead on:\n- Reach, 80 against 25\n- Risk, 65 against 40\n- Agent interface, 70 against 20\n\nWatch for: Only BF16 from Xiaomi, about 23 GB to run; the smaller builds are Ollama's\n\n\n## Why the edge\n\n### Reach: MiMo-V2.6 Distill Qwen 9B +55\n\n- Cola2 (25): Memory 15, the only build is the F32 safetensors set, 35.07 GB, and 35.07 GB × 1.2 = 42.1 GB, within 64 GB. Loaded as BF16, as the card's example does, it needs about half, but the line reads the file size. Runtimes 0, none of the six runs it in a released version. Builds 0, one set of weights and no quantised build. Terms 0, no licence for the weights. 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 nothing names an API that serves it. 15 + 0 + 0 + 0 + 10 + 0 = 25.\n- MiMo-V2.6 Distill Qwen 9B (80): Memory 30 of 30, Ollama's library build at q4_K_M is 6.6 GB, 7.9 GB with a fifth added, while Xiaomi's only build is BF16 at 18.85 GB. Runtimes 25, it keeps Qwen3.5-9B's architecture, which released vLLM, SGLang, Transformers and llama.cpp run, and Ollama's own library carries this model (entry updated 3 November 2026; the 21 October check found none). Builds 0, Xiaomi publishes no quantised build. Terms 15, MIT on the card over an Apache 2.0 base, both with nothing added. Download 10, not gated. Hosted 0, no provider serves this distill.\n\n### Agent interface: MiMo-V2.6 Distill Qwen 9B +50\n\n- Cola2 (20): Chat template 20, A chat template in tokenizer_config.json (4,116 characters), which came with the Qwen3 tokenizer. Tool-calling format 0, none. Trained tool calling 0, not trained for tool calling. Structured output 0, Nothing about JSON or schema-constrained output. Reasoning control 0, no reasoning mode. Context 0, no context length is stated. 20 + 0 + 0 + 0 + 0 + 0 = 20.\n- MiMo-V2.6 Distill Qwen 9B (70): Chat template 20, a Jinja file in the repository. Tool-calling format 10 of 25, the format is only in the template and the card names no tool parser. Trained tool calling 20, several calls a turn and agentic fine-tuning. Structured output 0, not documented. Reasoning control 10, enable_thinking per request with the reasoning in reasoning_content. Context 10, 262,144 tokens from the base's native length, though the card doesn't say.\n\n### Risk: MiMo-V2.6 Distill Qwen 9B +25\n\n- Cola2 (40): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, the files sit in the ByteDance-Seed organisation, which the ByteDance-Seed GitHub repository for the model links to (10). Safety evaluation 0, no safety results. Agent guidance 5, General cautions in the GitHub model card: not instruction-tuned or safety-aligned, not for use as an assistant, for facts or advice, or for high-impact decisions about people. Licence risk 0, With no licence for the weights there is nothing to hold ByteDance to. Security programme 5, the GitHub repository's SECURITY.md sends reports to ByteDance's security centre and says how they're assessed (5). 15 + 15 + 0 + 5 + 0 + 5 = 40.\n- MiMo-V2.6 Distill Qwen 9B (65): File safety 25, safetensors only and no repository code runs. Provenance 15, the files are in Xiaomi's MiMo organisation, which mimo.xiaomi.com links to, with a checksum on every file. Safety evaluation 0, the technical report has no safety results. Agent guidance 5, the card's Use Restrictions section (28 October 2026) gives general cautions, with nothing on prompt injection, refusals or safeguards. Licence risk 15, MIT and Apache 2.0 with no conditions, and the card says its restrictions add none. Security programme 5 of 10, Xiaomi's company security centre takes reports, but nothing links it to MiMo and no advisories were found.\n\n### Documentation and upkeep: Cola2 +18\n\n- Cola2 (58): Model card 8, Intended use and limitations (the out-of-scope list, and the unconverged latent model) and the architecture are on the card and the GitHub model card it links. Training data 15, the GitHub model card names the source (OLMo 2 pretraining text, retokenised) and the mix by stage with token counts, 346.03B in all. Last change 20, All six commits are from 6 November 2026, four days before this check, the last one updating a checksum in the README. Responsiveness 0, no discussions on the repository, so nobody has asked anything yet and the line reads as none answered, as settled in calibration. Version policy 5, A first release. File health 10, Config, files and card agree: F32 weights, a float32 config and a card that says to load them as bfloat16, with SHA256SUMS to check the download. 8 + 15 + 20 + 0 + 5 + 10 = 58.\n- MiMo-V2.6 Distill Qwen 9B (40): Model card 5 of 20, intended use and parameters only. Training data 5, a domain mix with token counts but no sources or cut-off. Last change 20, README updates on 28 October 2026. Responsiveness 0, Xiaomi answered none of the 14 discussions. Version policy 5, a first release. File health 5, no LICENSE file, a config that lists an MTP layer the weights lack, and template and tool-call reports waiting without a reply.\n\n## Score by category\n\n| Category | Weight | Cola2 | MiMo-V2.6 Distill Qwen 9B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 25 | 80 | MiMo-V2.6 Distill Qwen 9B +55 |\n| Risk | 20% (20 this run) | 40 | 65 | MiMo-V2.6 Distill Qwen 9B +25 |\n| Agent interface | 10% (10 this run) | 20 | 70 | MiMo-V2.6 Distill Qwen 9B +50 |\n| Documentation and upkeep | 10% (10 this run) | 58 | 40 | Cola2 +18 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **33.9 · F** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Cola2 | MiMo-V2.6 Distill Qwen 9B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | ByteDance (Seed) | Xiaomi (MiMo team) |\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 | None stated for the weights (the code is Apache 2.0) | MIT (metadata only, no LICENSE file); built on Qwen3.5-9B under Apache 2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-11-06 | 2026-09-21 |\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 | 2.3/5 (4) |\n\n## How the scores have moved\n\n### Cola2\n\nNo score change since it was listed.\n\n### MiMo-V2.6 Distill Qwen 9B\n\n- no change on 3 November 2026: product\n\n## Verdicts\n\n**Cola2.** A research release, and an honest one: ByteDance Seed says it's a base model with an unconverged latent stage, scoring below Llama-3-8B on its own table. It's here for people studying continuous-latent generation. Agents can't use it as a model: 32-token completions, no chat or tools, the repository's own code to load it, and no licence on the weights.\n\n**MiMo-V2.6 Distill Qwen 9B.** A 9B cousin tuned on MiMo-V2.6's agent work for coding, terminal tasks and visual coding, released as a base for RL research. Ollama's library build needs about 8 GB at 4-bit, while Xiaomi ships only BF16. The main risks are no safety results while a seventh of its tuning is offensive security, and nobody at Xiaomi answering reports.\n\n## Before you call either\n\n### Cola2\n\n1. Don't plan to use this as your model. It completes short prompts and wasn't tuned to follow instructions\n2. Don't use it commercially on the strength of this listing. The weights have no stated licence\n3. If you study it, read modeling_cola2.py first: trust_remote_code runs it\n4. Pin Transformers below 5, as the card requires\n5. Pass a seeded torch.Generator to generate(). Output varies between runs even with greedy decoding\n6. Check the download with `sha256sum -c SHA256SUMS`\n\n### MiMo-V2.6 Distill Qwen 9B\n\n1. Quickest start is `ollama run mimo-v2.6:9b`, Ollama's 6.6 GB q4_K_M build with text and image input\n2. Serve it as the card does, `sglang serve --model-path XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B --reasoning-parser mimo`, and add `--tool-call-parser mimo` for parsed tool calls\n3. SGLang's mimo reasoning parser expects thinking to be asked for, so pass `chat_template_kwargs` with `enable_thinking` true, as the card does, and read `reasoning_content`\n4. Calls come back as function and parameter blocks inside tool_call, the same shape vLLM's and SGLang's qwen3_coder parsers read\n5. The generation config samples at temperature 0.6, top_k 20 and top_p 0.95\n6. Images and video go in through Qwen3.5's processor; the template's audio tokens have no audio encoder behind them\n7. The MTP head isn't in the files, so skip MTP speculative decoding even though config.json lists a layer\n8. It's an SFT checkpoint meant for further RL, and discussions report runaway generation on llama.cpp, so cap max_tokens\n9. If you redistribute the weights, include the Apache 2.0 text of Qwen3.5-9B, which section 4(a) asks for and the repository lacks\n\n## Questions\n\n### Which is better for AI agents, Cola2 or MiMo-V2.6 Distill Qwen 9B?\n\nMiMo-V2.6 Distill Qwen 9B scores 61 (C) on agent readiness against Cola2's 33.9 (F), and leads in 3 of 4 scored categories. Cola2 leads on documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/cola2-vs-mimo-v2-6-distill-qwen-9b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/cola2-vs-mimo-v2-6-distill-qwen-9b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"cola2\", \"b\": \"mimo-v2-6-distill-qwen-9b\"}`. From a terminal: `anchor compare cola2 mimo-v2-6-distill-qwen-9b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/cola2.json and https://www.anchorterminal.com/api/v1/tools/mimo-v2-6-distill-qwen-9b.json\n\n## Other comparisons with Cola2 or MiMo-V2.6 Distill Qwen 9B\n\n- [Agents-A1-4B vs Cola2](https://www.anchorterminal.com/compare/agents-a1-4b-vs-cola2.md)\n- [Agents-A1-4B vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Apertus v1.5 8B vs Cola2](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-cola2.md)\n- [Apertus v1.5 8B vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Apodex-1.1-mini vs Cola2](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-cola2.md)\n- [Apodex-1.1-mini vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Arete-27B vs Cola2](https://www.anchorterminal.com/compare/arete-27b-vs-cola2.md)\n- [Arete-27B vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/arete-27b-vs-mimo-v2-6-distill-qwen-9b.md)\n- [BigBang-v1 vs Cola2](https://www.anchorterminal.com/compare/bigbang-v1-vs-cola2.md)\n- [BigBang-v1 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/bigbang-v1-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Carbon-X vs Cola2](https://www.anchorterminal.com/compare/carbon-x-vs-cola2.md)\n- [Carbon-X vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/carbon-x-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Cola2 vs Cosmos-Reason2-2B](https://www.anchorterminal.com/compare/cola2-vs-cosmos-reason2-2b.md)\n- [Cola2 vs Darwin-36B-Opus](https://www.anchorterminal.com/compare/cola2-vs-darwin-36b-opus.md)\n- [Cola2 vs DeepSeek-V3.2](https://www.anchorterminal.com/compare/cola2-vs-deepseek-v3-2.md)\n- [Cola2 vs DeepSeek V4.1 Flash](https://www.anchorterminal.com/compare/cola2-vs-deepseek-v4-1-flash.md)\n- [Cola2 vs DeepSeek-V4-Flash-0731](https://www.anchorterminal.com/compare/cola2-vs-deepseek-v4-flash-0731.md)\n- [Cola2 vs Devstral Small 2](https://www.anchorterminal.com/compare/cola2-vs-devstral-small-2.md)\n- [Cola2 vs DiffusionGemma 26B A4B IT](https://www.anchorterminal.com/compare/cola2-vs-diffusiongemma-26b-a4b-it.md)\n- [Cola2 vs EXAONE 4.5 33B](https://www.anchorterminal.com/compare/cola2-vs-exaone-4-5-33b.md)\n- [Cola2 vs Gemma 4 12B IT](https://www.anchorterminal.com/compare/cola2-vs-gemma-4-12b-it.md)\n- [Cola2 vs Gemma 4 26B A4B IT](https://www.anchorterminal.com/compare/cola2-vs-gemma-4-26b-a4b-it.md)\n- [Cola2 vs Gemma 4 31B IT](https://www.anchorterminal.com/compare/cola2-vs-gemma-4-31b-it.md)\n- [Cola2 vs Gemma 4 E2B IT](https://www.anchorterminal.com/compare/cola2-vs-gemma-4-e2b-it.md)\n- [Cola2 vs Gemma 4 E4B IT](https://www.anchorterminal.com/compare/cola2-vs-gemma-4-e4b-it.md)\n- 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Hy3](https://www.anchorterminal.com/compare/cola2-vs-hy3.md)\n- [Cola2 vs Inkling](https://www.anchorterminal.com/compare/cola2-vs-inkling.md)\n- [Cola2 vs Inkling-Small](https://www.anchorterminal.com/compare/cola2-vs-inkling-small.md)\n- [Cola2 vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/cola2-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [Cola2 vs Kimi K3](https://www.anchorterminal.com/compare/cola2-vs-kimi-k3.md)\n- [Cola2 vs Kimi K3.1 Pro](https://www.anchorterminal.com/compare/cola2-vs-kimi-k3-1-pro.md)\n- [Cola2 vs Kolibri-1](https://www.anchorterminal.com/compare/cola2-vs-kolibri-1.md)\n- [Cola2 vs Kronos](https://www.anchorterminal.com/compare/cola2-vs-kronos.md)\n- [Cola2 vs Laguna M.1](https://www.anchorterminal.com/compare/cola2-vs-laguna-m-1.md)\n- [Cola2 vs Laguna S 2.1](https://www.anchorterminal.com/compare/cola2-vs-laguna-s-2-1.md)\n- [Cola2 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/cola2-vs-laguna-xs-2-1.md)\n- [Cola2 vs LBS-27B](https://www.anchorterminal.com/compare/cola2-vs-lbs-27b.md)\n- [Cola2 vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/cola2-vs-lfm2-5-2-6b.md)\n- [Cola2 vs LFM3-1.7B](https://www.anchorterminal.com/compare/cola2-vs-lfm3-1-7b.md)\n- [Cola2 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/cola2-vs-lfm3-audio-2b.md)\n- [Cola2 vs LFM3-Omni-2B](https://www.anchorterminal.com/compare/cola2-vs-lfm3-omni-2b.md)\n- [Cola2 vs LFM3-VL-2B](https://www.anchorterminal.com/compare/cola2-vs-lfm3-vl-2b.md)\n- [Cola2 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/cola2-vs-ling-3-0-tiny.md)\n- [Cola2 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/cola2-vs-ling-3-1-flash-1019.md)\n- [Cola2 vs LongCat-2.5](https://www.anchorterminal.com/compare/cola2-vs-longcat-2-5.md)\n- [Cola2 vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/cola2-vs-mimo-v2-6-flash-rl.md)\n- [Cola2 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/cola2-vs-minicpm-o-4-5.md)\n- [Cola2 vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/cola2-vs-minicpm-v-4-7-1b.md)\n- [Cola2 vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/cola2-vs-minicpm-v-4-7-35b-a3b.md)\n- [Cola2 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/cola2-vs-minicpm5-2b.md)\n- [Cola2 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/cola2-vs-minimax-m2-5.md)\n- [Cola2 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/cola2-vs-minimax-m2-7.md)\n- [Cola2 vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/cola2-vs-minimax-m3-1-flash.md)\n- [Cola2 vs Mistral Large 4](https://www.anchorterminal.com/compare/cola2-vs-mistral-large-4.md)\n- [Cola2 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/cola2-vs-muse-glimmer-30b.md)\n- [Cola2 vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/cola2-vs-nanbeige-4-2-3b.md)\n- [Cola2 vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/cola2-vs-nanbeige-4-3-33b.md)\n- [Cola2 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/cola2-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [Cola2 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/cola2-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [Cola2 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/cola2-vs-nemotron-3-nano-30b-a3b.md)\n- [Cola2 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/cola2-vs-nemotron-3-nano-4b.md)\n- [Cola2 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/cola2-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Cola2 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/cola2-vs-nemotron-3-super-120b-a12b.md)\n- [Cola2 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/cola2-vs-nemotron-3-ultra-550b-a55b.md)\n- [Cola2 vs North Mini Code 1.0](https://www.anchorterminal.com/compare/cola2-vs-north-mini-code-1-0.md)\n- [Cola2 vs occamy-1.0](https://www.anchorterminal.com/compare/cola2-vs-occamy-1-0.md)\n- [Cola2 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/cola2-vs-olmo-3-7b-think.md)\n- [Cola2 vs Ornith-1.5-122B](https://www.anchorterminal.com/compare/cola2-vs-ornith-1-5-122b.md)\n- [Cola2 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/cola2-vs-ornith-1-5-35b-a3b.md)\n- [Cola2 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/cola2-vs-ornith-1-5-397b.md)\n- [Cola2 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/cola2-vs-ornith-1-5-9b.md)\n- [Cola2 vs OTel-2.0-LLM-31B-IT](https://www.anchorterminal.com/compare/cola2-vs-otel-2-0-llm-31b-it.md)\n- [Cola2 vs Qwen-AgentWorld-35B-A3B](https://www.anchorterminal.com/compare/cola2-vs-qwen-agentworld-35b-a3b.md)\n- [Cola2 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/cola2-vs-qwen3-30b-a3b-instruct-2507.md)\n- [Cola2 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/cola2-vs-qwen3-4b-instruct-2507.md)\n- [Cola2 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/cola2-vs-qwen3-5-0-8b.md)\n- [Cola2 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/cola2-vs-qwen3-5-122b-a10b.md)\n- [Cola2 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/cola2-vs-qwen3-5-2b.md)\n- [Cola2 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/cola2-vs-qwen3-5-397b-a17b.md)\n- [Cola2 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/cola2-vs-qwen3-5-4b.md)\n- [Cola2 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/cola2-vs-qwen3-5-9b.md)\n- [Cola2 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/cola2-vs-qwen3-6-27b.md)\n- [Cola2 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/cola2-vs-qwen3-6-35b-a3b.md)\n- [Cola2 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/cola2-vs-qwen3-8-27b.md)\n- [Cola2 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/cola2-vs-qwen3-8-flash-next.md)\n- [Cola2 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/cola2-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Cola2 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/cola2-vs-qwen3-coder-next.md)\n- [Cola2 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/cola2-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Cola2 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/cola2-vs-qwen3-vl-2b-instruct.md)\n- [Cola2 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/cola2-vs-qwen3-vl-30b-a3b-instruct.md)\n- [Cola2 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/cola2-vs-qwen3-vl-32b-instruct.md)\n- [Cola2 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/cola2-vs-qwen3-vl-4b-instruct.md)\n- [Cola2 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/cola2-vs-qwen3-vl-8b-instruct.md)\n- [Cola2 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/cola2-vs-qwopus3-8-27b-flash-v2.md)\n- [Cola2 vs Recursive Flint](https://www.anchorterminal.com/compare/cola2-vs-recursive-flint.md)\n- [Cola2 vs Ripple-65B Preview](https://www.anchorterminal.com/compare/cola2-vs-ripple-65b-preview.md)\n- [Cola2 vs SenseNova-Loop-9B-Preview](https://www.anchorterminal.com/compare/cola2-vs-sensenova-loop-9b-preview.md)\n- [Cola2 vs SmolLM3-3B](https://www.anchorterminal.com/compare/cola2-vs-smollm3-3b.md)\n- [Cola2 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/cola2-vs-spark-x2-6-4b.md)\n- [Cola2 vs Step 3.7 Flash](https://www.anchorterminal.com/compare/cola2-vs-step-3-7-flash.md)\n- [Cola2 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/cola2-vs-swift-1-5-qwen3-8-27b.md)\n- [Cola2 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/cola2-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Cola2 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/cola2-vs-thinkingcap-qwen3-8-27b.md)\n- [Cola2 vs Baidu Unlimited-OCR-2](https://www.anchorterminal.com/compare/cola2-vs-unlimited-ocr-2.md)\n- [Cola2 vs WeVisOne-VL-2B](https://www.anchorterminal.com/compare/cola2-vs-wevisone-vl-2b.md)\n- [Cola2 vs WeVisOne-VL-4B](https://www.anchorterminal.com/compare/cola2-vs-wevisone-vl-4b.md)\n- [Cola2 vs ZAYA1-8B](https://www.anchorterminal.com/compare/cola2-vs-zaya1-8b.md)\n- [Cosmos-Reason2-2B vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Darwin-36B-Opus vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-mimo-v2-6-distill-qwen-9b.md)\n- [DeepSeek-V3.2 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-mimo-v2-6-distill-qwen-9b.md)\n- [DeepSeek V4.1 Flash vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-mimo-v2-6-distill-qwen-9b.md)\n- [DeepSeek-V4-Flash-0731 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Devstral Small 2 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/devstral-small-2-vs-mimo-v2-6-distill-qwen-9b.md)\n- [DiffusionGemma 26B A4B IT vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-mimo-v2-6-distill-qwen-9b.md)\n- [EXAONE 4.5 33B vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Gemma 4 12B IT vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Gemma 4 26B A4B IT vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Gemma 4 31B IT vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Gemma 4 E2B IT vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Gemma 4 E4B IT vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-mimo-v2-6-distill-qwen-9b.md)\n- [GLM-4.5-Air vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-mimo-v2-6-distill-qwen-9b.md)\n- [GLM-4.7-Flash vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-mimo-v2-6-distill-qwen-9b.md)\n- [GLM-5.3-Flash vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-mimo-v2-6-distill-qwen-9b.md)\n- [GLM-5.3 vs MiMo-V2.6 Distill Qwen 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