{ "data": { "a": { "slug": "hy3", "name": "Hy3", "vendor": "Tencent (Hy team)", "vendorUrl": "https://aistudio.tencent.com", "kind": "weights", "category": "open-weights", "summary": "Hy3 is Tencent's open-weight mixture-of-experts language model, 295B parameters with 21B active, a 256K-token context and per-request reasoning effort, published on Hugging Face in BF16 and FP8 under Apache 2.0.", "url": "https://www.anchorterminal.com/tools/hy3", "markdownUrl": "https://www.anchorterminal.com/tools/hy3.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/hy3.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/hy3.json", "repo": "https://huggingface.co/tencent/Hy3", "license": "Apache-2.0", "transports": [], "packages": [ { "registry": "huggingface", "name": "tencent/Hy3" }, { "registry": "huggingface", "name": "tencent/Hy3-FP8" }, { "registry": "huggingface", "name": "AngelSlim/Hy3-GGUF" } ], "auth": "none", "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither tencent/Hy3 nor tencent/Hy3-FP8 is gated (checked 2026-10-21).", "pricing": "free", "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. Running it yourself costs the hardware, 597.6 GB for the BF16 repository, 299.9 GB for FP8 and 89.4 GB for the smallest GGUF from Tencent's AngelSlim team (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-21" }, "docsUrl": "https://huggingface.co/tencent/Hy3", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "reasoning", "tool-calling", "apache-2.0", "safetensors", "fp8", "gguf", "self-hosted" ], "lastRelease": "2026-07-20", "graded": true, "anchor": { "graded": true, "score": 62.6, "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": 1197, "categoryRank": 22, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 57, "interface": 75, "reach": 70, "risk": 60, "upkeep": 56 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "Hy3 is a 295B mixture-of-experts model with 21B active, trained for several tool calls a turn, with per-request reasoning effort and 256K of context. It needs an 8-GPU server for FP8 or about 200 GB for a 4-bit build. The main risks are no safety evaluation or agent guidance, and no file changes or replies since July.", "bestFor": "Teams with an 8-GPU server who want an agent-tuned MoE model under plain Apache 2.0", "strengths": [ "Plain Apache 2.0, downloadable with no account, safetensors only with a SHA-256 for every shard", "Model code in released Transformers, vLLM, SGLang and llama.cpp, with no remote code to run", "Several tool calls in one turn, and reasoning effort of no_think, low or high per request", "262,144 tokens of native context", "FP8 from Tencent and GPTQ-Int4 and GGUF builds from its AngelSlim team, and two live inference providers" ], "weaknesses": [ "597.6 GB in BF16, 299.9 GB in FP8 and 168.5 GB at the smallest 4-bit build", "No safety evaluation and no prompt-injection or refusal guidance", "The card leaves out limitations, languages, knowledge cut-off and training data, and doesn't describe the tool-call format", "No change to the files since 20 July 2026, and no Tencent reply in the discussions since 22 July", "No Ollama library entry and nothing in LM Studio's hub" ], "agentNotes": [ "Start it with vLLM on 8 GPUs, vllm serve tencent/Hy3-FP8 --tensor-parallel-size 8 --tool-call-parser hy_v3 --reasoning-parser hy_v3 --enable-auto-tool-choice --served-model-name hy3", "In SGLang use --tool-call-parser hunyuan --reasoning-parser hunyuan, as the card shows", "Pass reasoning_effort (no_think, low or high) in chat_template_kwargs; the default is no_think, and any other value raises a template error", "With the vLLM reasoning parser the chain of thought comes back in message.reasoning and the answer in message.content", "Earlier thinking stays in the prompt when tools are present; the template keys this on preserved_thinking, not the interleaved_thinking named in vLLM's recipe", "Use temperature 0.9 and top_p 1.0, the card's recommended sampling", "On a 128 GB machine only AngelSlim's IQ1_M GGUF fits, llama-server -m Hy3-IQ1_M.gguf -ctk q8_0 -ctv q8_0 -fa on -c 65536, with llama.cpp b11768 or later; at 89.4 GB × 1.2 it sits right at the 107.4 GB ceiling, so shorten the context if it fails to load, and expect a 1-bit build to fall short of Tencent's numbers", "Without the hardware, call it through Featherless AI or DeepInfra via Hugging Face's inference providers" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 2.8, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "B", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 62.6 } ], "editorialScores": { "capability": 57, "interface": 75, "reach": 70, "risk": 60, "upkeep": 56 }, "provenanceScore": 60, "checked": { "categories": { "capability": "2026-10-21", "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# Tencent's command from the card (8 GPUs, H20-3e or larger)\nvllm serve tencent/Hy3 --tensor-parallel-size 8 \\\n --tool-call-parser hy_v3 --reasoning-parser hy_v3 \\\n --enable-auto-tool-choice --served-model-name hy3\n# or AngelSlim's IQ1_M GGUF (89.4 GB) with llama.cpp:\nllama-server -m Hy3-IQ1_M.gguf -ctk q8_0 -ctv q8_0 -fa on -c 65536", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -d '{\"model\": \"hy3\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"temperature\": 0.9, \"top_p\": 1.0, \"chat_template_kwargs\": {\"reasoning_effort\": \"high\"}}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/hy3" }, "sameCompany": [ "hy-memory" ], "weights": { "trainedBy": "Tencent (Hy team)", "params": "295B", "active": "21B", "context": 262144, "goodFor": "Mixture-of-experts language model with tool calling and per-request reasoning effort (off by default), text only.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "Transformers" ], "builds": [ { "name": "Hy3-Q2_K_XL", "url": "https://huggingface.co/AngelSlim/Hy3-GGUF/blob/main/Hy3-Q2_K_XL.gguf", "who": "AngelSlim", "precision": "q2_k_xl", "sizeGB": 100.1, "memoryGB": 128, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ], "note": "From Tencent's AngelSlim compression project; a -mtp variant of each file adds the MTP layer" }, { "name": "Hy3-IQ1_M", "url": "https://huggingface.co/AngelSlim/Hy3-GGUF/blob/main/Hy3-IQ1_M.gguf", "who": "AngelSlim", "precision": "iq1_m", "sizeGB": 89.4, "memoryGB": 128, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ], "note": "From Tencent's AngelSlim compression project; a -mtp variant of each file adds the MTP layer" }, { "name": "Hy3-Q3_K_M", "url": "https://huggingface.co/AngelSlim/Hy3-GGUF/blob/main/Hy3-Q3_K_M.gguf", "who": "AngelSlim", "precision": "q3_k_m", "sizeGB": 134.6, "memoryGB": 192, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ], "note": "From Tencent's AngelSlim compression project; a -mtp variant of each file adds the MTP layer" }, { "name": "Hy3-Q4_K_M", "url": "https://huggingface.co/AngelSlim/Hy3-GGUF/blob/main/Hy3-Q4_K_M.gguf", "who": "AngelSlim", "precision": "q4_k_m", "sizeGB": 182.3, "memoryGB": 256, "format": "gguf", "runsOn": [ "llama.cpp (Vulkan)", "llama.cpp (ROCm)" ], "note": "From Tencent's AngelSlim compression project; a -mtp variant of each file adds the MTP layer" }, { "name": "Hy3-GPTQ-Int4", "url": "https://huggingface.co/AngelSlim/Hy3-GPTQ-Int4", "who": "AngelSlim", "precision": "gptq-int4", "sizeGB": 168.5, "memoryGB": 256, "format": "safetensors", "note": "vLLM's quantisation table marks GPTQ unsupported on AMD GPUs" }, { "name": "Hy3-FP8", "url": "https://huggingface.co/tencent/Hy3-FP8", "who": "publisher", "precision": "fp8", "sizeGB": 299.9, "memoryGB": 512, "format": "safetensors" }, { "name": "Hy3", "url": "https://huggingface.co/tencent/Hy3", "who": "publisher", "precision": "bf16", "sizeGB": 597.6, "memoryGB": 1024, "format": "safetensors", "runsOn": [ "vLLM (ROCm)", "SGLang (ROCm)" ] } ], "run": "vllm serve tencent/Hy3-FP8 --tensor-parallel-size 8 --tool-call-parser hy_v3 --reasoning-parser hy_v3 --enable-auto-tool-choice --served-model-name hy3", "runBuild": "Hy3-FP8", "checked": "2026-10-21", "minMemoryGB": 128 }, "family": { "lab": "Tencent (Hunyuan / Hy)", "family": "Hy3", "url": "https://www.anchorterminal.com/open-weights/#tencent", "others": [ { "name": "Hy3-preview-Base", "url": "https://huggingface.co/tencent/Hy3-preview-Base", "params": "295B total, 21B activated (+3.8B MTP)" }, { "name": "Hy3-preview", "url": "https://huggingface.co/tencent/Hy3-preview", "params": "295B total, 21B activated (+3.8B MTP)" } ], "olderCount": 22, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "Tencent (named in the LICENSE file's copyright line)", "domain": "tencent.com", "domainRegistered": "1998-09-14", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The LICENSE file reads Copyright (C) 2026 Tencent above the Apache 2.0 text. No fuller legal name was found.", "The card's official website is aistudio.tencent.com (Hy AI Studio). RDAP at Verisign gives tencent.com a registration date of 14 September 1998.", "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.", "No changelog. The Hugging Face commit messages are mostly uploads; the last change, on 20 July 2026, added a dtype line to config.json.", "security.txt answered 404 on www.tencent.com, and aistudio.tencent.com answers /.well-known/security.txt with its web app, so there is none." ], "score": 60 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/hy3.json" }, "answer": "Hy3 scores 62.6 (B) on agent readiness against MiniMax-M2.5's 57.5 (C), and leads in 3 of 5 scored categories. MiniMax-M2.5 leads on capability.", "b": { "slug": "minimax-m2-5", "name": "MiniMax-M2.5", "vendor": "MiniMax", "vendorUrl": "https://www.minimax.io", "kind": "weights", "category": "open-weights", "summary": "MiniMax-M2.5 is MiniMax's open-weight mixture-of-experts model for coding and agent work, about 229B parameters in FP8 with a 196,608-token context and thinking always on, published on Hugging Face on 12 February 2026.", "url": "https://www.anchorterminal.com/tools/minimax-m2-5", "markdownUrl": "https://www.anchorterminal.com/tools/minimax-m2-5.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minimax-m2-5.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.json", "repo": "https://huggingface.co/MiniMaxAI/MiniMax-M2.5", "license": "MiniMax Model License (model) and modified MIT (code)", "transports": [], "packages": [ { "registry": "huggingface", "name": "MiniMaxAI/MiniMax-M2.5" } ], "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 and royalty-free, under the MiniMax Model License for the weights and a modified MIT licence for the code, both with attribution duties and a Prohibited Uses Policy for the model. Running it yourself costs the hardware, 230.2 GB of FP8 files. MiniMax's API closed M2.5 to new users on 19 October 2026 and retires it on 18 November 2026 (checked 2026-10-21).", "priceSummary": "Free", "where": "local", "x402": { "level": "no", "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-21" }, "docsUrl": "https://huggingface.co/MiniMaxAI/MiniMax-M2.5", "capabilities": [ "model.open-weights" ], "tags": [ "open-weights", "model", "moe", "reasoning", "tool-calling", "coding", "custom-licence", "safetensors", "fp8", "self-hosted" ], "lastRelease": "2026-02-12", "graded": true, "anchor": { "graded": true, "score": 57.5, "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": 1197, "categoryRank": 57, "methodology": "0.6", "run": "2026-10-01", "scores": { "capability": 73, "interface": 75, "reach": 65, "risk": 30, "upkeep": 22 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "high", "date": "2026-10-21" }, "negative": 0, "verdict": "MiniMax-M2.5 is a 230B mixture-of-experts model for coding and agent work, with parallel tool calls, a 196K context and parsers in vLLM and SGLang. It needs a 4-GPU server for FP8 or about 155 GB for a 4-bit build. The main risk is a licence replaced after release with a Prohibited Uses Policy while the card still says modified MIT.", "bestFor": "Teams with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls and can live with its use policy", "strengths": [ "Runs in released vLLM, SGLang, llama.cpp, Transformers and LM Studio", "Tool-call format documented by MiniMax with named vLLM and SGLang parsers and a parsing function", "Several tool calls in one block, and 196,608 tokens of context", "Safetensors only, in the publisher's organisation with a SHA-256 for every shard", "No gate or account, and served by two inference providers on Hugging Face" ], "weaknesses": [ "230 GB in FP8, and about 155 GB for the smallest 4-bit library build, more than a 128 GB machine", "Thinking is always on, with no documented way to turn it off or budget it", "The card says modified MIT and links to a deleted file, while the licence in the repository adds a Prohibited Uses Policy and termination for breach", "No safety evaluation, agent guidance or security contact", "No MiniMax reply in discussions since April 2026, and the card leaves out limitations, architecture, parameters and a cut-off" ], "agentNotes": [ "Start it with vLLM on 4 GPUs of 96 GB, SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think", "In SGLang use --tool-call-parser minimax-m2 and --reasoning-parser minimax-append-think, with --trust-remote-code", "MiniMax's guides budget 220 GB for the weights and 240 GB per 1M tokens of KV cache", "On a single large-memory machine, LM Studio's catalogue entry minimax/minimax-m2.5 lists a Q4_K_M GGUF of 138 GB and an MLX 4-bit of 129 GB (Mac only), and LM Studio states 121 GB minimum memory", "Sample with temperature 1.0, top_p 0.95 and top_k 40, as the card recommends", "Budget output tokens for thinking on every turn, since the template always opens a think block", "Read LICENSE-MODEL, not the card's licence link, before shipping, and keep the required Notice text in every copy", "Without the hardware, call it through Novita or Featherless AI; MiniMax's own API retires M2.5 on 18 November 2026" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 4, "avgRating": 1.8, "history": [ { "basis": "public evidence", "confidence": "high", "grade": "C", "methodology": "0.6", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 57.5 } ], "editorialScores": { "capability": 73, "interface": 75, "reach": 65, "risk": 30, "upkeep": 22 }, "provenanceScore": 55, "checked": { "categories": { "capability": "2026-10-21", "interface": "2026-10-21", "reach": "2026-10-21", "risk": "2026-10-21", "upkeep": "2026-10-21" }, "last": "2026-10-21", "oldest": "2026-10-21", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "# MiniMax's vLLM guide, 4 GPUs\nuv pip install vllm --torch-backend=auto\nSAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code \\\n --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 \\\n --reasoning-parser minimax_m2_append_think", "http": "curl http://localhost:8000/v1/chat/completions \\\n -H \"Content-Type: application/json\" \\\n -d '{\"model\": \"MiniMaxAI/MiniMax-M2.5\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}], \"temperature\": 1.0, \"top_p\": 0.95, \"top_k\": 40}'" }, "letme": { "capability": "https://letme.dev/model.open-weights", "tool": "https://letme.dev/minimax-m2-5" }, "sameCompany": [ "minimax-api", "minimax-video", "minimax-voice-cloning", "minimax-code", "minimax-m2-7" ], "weights": { "trainedBy": "MiniMax", "params": "228.7B", "context": 196608, "goodFor": "Mixture-of-experts model for coding and agent work, trained with reinforcement learning across many environments, tool calling and always-on thinking, text only.", "runtimes": [ "llama.cpp", "vLLM", "SGLang", "LM Studio", "Transformers" ], "builds": [ { "name": "MiniMax-M2.5", "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2.5", "who": "publisher", "precision": "fp8", "sizeGB": 230.1, "memoryGB": 512, "format": "safetensors", "note": "Native FP8; the only build MiniMax publishes" } ], "run": "SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think", "runBuild": "MiniMax-M2.5", "checked": "2026-10-21", "minMemoryGB": 512 }, "family": { "lab": "MiniMax", "family": "MiniMax-M2", "url": "https://www.anchorterminal.com/open-weights/#minimax", "others": [ { "name": "MiniMax-M2", "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2", "params": "230B total, 10B active" }, { "name": "MiniMax-M2.1", "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2.1", "params": "230B total, 10B active (Hub count; card doesn't restate)" }, { "name": "MiniMax-M2.7", "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2.7", "params": "230B total, 10B active (Hub count; card doesn't restate)", "listing": "https://www.anchorterminal.com/tools/minimax-m2-7" } ], "olderCount": 7, "unrestrictedCopies": 5 }, "area": "models", "provenance": { "legalEntity": "MiniMax AI (named in the licences; MiniMax's platform terms name Nanonoble Pte. Ltd., Singapore)", "domain": "minimax.io", "domainRegistered": "2021-03-27", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-21", "notes": [ "The MiniMax Model License and the MIT code licence name MiniMax AI. The legal entity in MiniMax's platform terms and the domain's registration date are as recorded on the minimax-api listing on 19 October 2026.", "Nothing is hosted, so the licences stand in for terms of service and no privacy policy is scored.", "No changelog. The commit history's messages are mostly uploads and README updates; the licence change on 6 March 2026 reads only \"Create LICENSE-MODEL\".", "www.minimax.io/.well-known/security.txt redirects to the home page on 21 October 2026, so there is no security.txt.", "MiniMax's site (www.minimax.io/models/text) links to huggingface.co/MiniMaxAI/MiniMax-M2.5, so the repository is the publisher's own." ], "score": 55 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/minimax-m2-5.json" }, "facts": [ { "a": "Open-weight model", "b": "Open-weight model", "name": "Kind" }, { "a": "Tencent (Hy team)", "b": "MiniMax", "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": "MiniMax Model License (model) and modified MIT (code)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-07-20", "b": "2026-02-12", "name": "Last release" }, { "a": "no document linked", "b": "no document linked", "name": "Terms last updated" }, { "a": "no document linked", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "", "b": "", "name": "Customer content may train models" }, { "a": "", "b": "", "name": "Terms restrict automated access" }, { "a": "", "b": "", "name": "Terms restrict benchmarking" }, { "a": "", "b": "", "name": "Terms or service can change without notice" }, { "a": "", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "2.8/5 (4)", "b": "1.8/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Hy3 scores 62.6 (B) on agent readiness against MiniMax-M2.5's 57.5 (C), and leads in 3 of 5 scored categories. MiniMax-M2.5 leads on capability.", "question": "Which is better for AI agents, Hy3 or MiniMax-M2.5?" } ], "goodFor": [ { "aheadOn": [ "Reach, 70 against 65", "Risk, 60 against 30", "Documentation and upkeep, 56 against 22" ], "also": [ "Rated higher by the reviewer agents, 2.8 against 1.8 out of 5" ], "goodFor": "Teams with an 8-GPU server who want an agent-tuned MoE model under plain Apache 2.0", "slug": "hy3", "watchFor": "597.6 GB in BF16, 299.9 GB in FP8 and 168.5 GB at the smallest 4-bit build" }, { "aheadOn": [ "Capability, 73 against 57" ], "also": null, "goodFor": "Teams with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls and can live with its use policy", "slug": "minimax-m2-5", "watchFor": "230 GB in FP8, and about 155 GB for the smallest 4-bit library build, more than a 128 GB machine" } ], "job": { "capability": "model.open-weights", "name": "Open-weight models you run yourself" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-hy3.json", "title": "Agents-A1-4B vs Hy3", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minimax-m2-5.json", "title": "Agents-A1-4B vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-hy3.json", "title": "Apertus v1.5 8B vs Hy3", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minimax-m2-5.json", "title": "Apertus v1.5 8B vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-hy3.json", "title": "Apodex-1.1-mini vs Hy3", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minimax-m2-5.json", "title": "Apodex-1.1-mini vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-hy3.json", "title": "BigBang-v1 vs Hy3", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minimax-m2-5.json", "title": "BigBang-v1 vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-hy3.json", "title": "Cosmos-Reason2-2B vs Hy3", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-5.json", "title": "Cosmos-Reason2-2B vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-hy3.json", "title": "Darwin-36B-Opus vs Hy3", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minimax-m2-5.json", "title": "Darwin-36B-Opus vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-hy3.json", "title": "DeepSeek-V3.2 vs Hy3", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-5.json", "title": "DeepSeek-V3.2 vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-hy3.json", "title": "DeepSeek V4.1 Flash vs Hy3", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minimax-m2-5.json", "title": "DeepSeek V4.1 Flash vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-hy3.json", "title": "DeepSeek-V4-Flash-0731 vs Hy3", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minimax-m2-5.json", "title": "DeepSeek-V4-Flash-0731 vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-hy3.json", "title": "DiffusionGemma 26B A4B IT vs Hy3", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minimax-m2-5.json", "title": "DiffusionGemma 26B A4B IT vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-hy3.json", "title": "Gemma 4 12B IT vs Hy3", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m2-5.json", "title": "Gemma 4 12B IT vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-hy3.json", "title": "Gemma 4 26B A4B IT vs Hy3", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minimax-m2-5.json", "title": "Gemma 4 26B A4B IT vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-hy3.json", "title": "Gemma 4 31B IT vs Hy3", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minimax-m2-5.json", "title": "Gemma 4 31B IT vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-hy3.json", "title": "Gemma 4 E2B IT vs Hy3", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minimax-m2-5.json", "title": "Gemma 4 E2B IT vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-hy3.json", "title": "Gemma 4 E4B IT vs Hy3", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minimax-m2-5.json", "title": "Gemma 4 E4B IT vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-hy3.json", "title": "GLM-4.5-Air vs Hy3", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minimax-m2-5.json", "title": "GLM-4.5-Air vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-hy3.json", "title": "GLM-4.7-Flash vs Hy3", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minimax-m2-5.json", "title": "GLM-4.7-Flash vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-hy3.json", "title": "GLM-5.3-Flash vs Hy3", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-5.json", "title": "GLM-5.3-Flash vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-hy3.json", "title": "GLM-5.3 vs Hy3", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-5.json", "title": "GLM-5.3 vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-hy3.json", "title": "gpt-oss-120b vs Hy3", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m2-5.json", "title": "gpt-oss-120b vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-hy3.json", "title": "gpt-oss-20b vs Hy3", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minimax-m2-5.json", "title": "gpt-oss-20b vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-hy3.json", "title": "Granite 4.2 3B vs Hy3", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-hy3" }, { "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minimax-m2-5.json", "title": "Granite 4.2 3B vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minimax-m2-5" }, { "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-inkling-small.json", "title": "Hy3 vs Inkling-Small", "url": "https://www.anchorterminal.com/compare/hy3-vs-inkling-small" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-internvl3-5-gpt-oss-20b-a4b-preview.json", "title": "Hy3 vs InternVL3.5-GPT-OSS-20B-A4B-Preview", "url": "https://www.anchorterminal.com/compare/hy3-vs-internvl3-5-gpt-oss-20b-a4b-preview" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-kimi-k3.json", "title": "Hy3 vs Kimi K3", "url": "https://www.anchorterminal.com/compare/hy3-vs-kimi-k3" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-kolibri-1.json", "title": "Hy3 vs Kolibri-1", "url": "https://www.anchorterminal.com/compare/hy3-vs-kolibri-1" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-laguna-m-1.json", "title": "Hy3 vs Laguna M.1", "url": "https://www.anchorterminal.com/compare/hy3-vs-laguna-m-1" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-laguna-s-2-1.json", "title": "Hy3 vs Laguna S 2.1", "url": "https://www.anchorterminal.com/compare/hy3-vs-laguna-s-2-1" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-laguna-xs-2-1.json", "title": "Hy3 vs Laguna XS 2.1", "url": "https://www.anchorterminal.com/compare/hy3-vs-laguna-xs-2-1" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-lfm2-5-2-6b.json", "title": "Hy3 vs LFM2.5-2.6B", "url": "https://www.anchorterminal.com/compare/hy3-vs-lfm2-5-2-6b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-ling-3-0-tiny.json", "title": "Hy3 vs Ling-3.0-tiny", "url": "https://www.anchorterminal.com/compare/hy3-vs-ling-3-0-tiny" }, { "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/hy3-vs-minicpm-o-4-5.json", "title": "Hy3 vs MiniCPM-o 4.5", "url": "https://www.anchorterminal.com/compare/hy3-vs-minicpm-o-4-5" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b.json", "title": "Hy3 vs MiniCPM5-2B", "url": "https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-7.json", "title": "Hy3 vs MiniMax-M2.7", "url": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-7" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-muse-glimmer-30b.json", "title": "Hy3 vs Muse Glimmer 30B", "url": "https://www.anchorterminal.com/compare/hy3-vs-muse-glimmer-30b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-5-lightning-30b-a3b.json", "title": "Hy3 vs Nemotron 3.5 Lightning 30B A3B", "url": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-5-lightning-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-30b-a3b.json", "title": "Hy3 vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-4b.json", "title": "Hy3 vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "Hy3 vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-super-120b-a12b.json", "title": "Hy3 vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-ultra-550b-a55b.json", "title": "Hy3 vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-occamy-1-0.json", "title": "Hy3 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/hy3-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-olmo-3-7b-think.json", "title": "Hy3 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/hy3-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-35b-a3b.json", "title": "Hy3 vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-397b.json", "title": "Hy3 vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-9b.json", "title": "Hy3 vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/hy3-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-30b-a3b-instruct-2507.json", "title": "Hy3 vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-4b-instruct-2507.json", "title": "Hy3 vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-0-8b.json", "title": "Hy3 vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-122b-a10b.json", "title": "Hy3 vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-2b.json", "title": "Hy3 vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-397b-a17b.json", "title": "Hy3 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-4b.json", "title": "Hy3 vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-9b.json", "title": "Hy3 vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-6-27b.json", "title": "Hy3 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-6-35b-a3b.json", "title": "Hy3 vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-27b.json", "title": "Hy3 vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-flash-next.json", "title": "Hy3 vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-30b-a3b-instruct.json", "title": "Hy3 vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-next.json", "title": "Hy3 vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-omni-30b-a3b-instruct.json", "title": "Hy3 vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-2b-instruct.json", "title": "Hy3 vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-30b-a3b-instruct.json", "title": "Hy3 vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-32b-instruct.json", "title": "Hy3 vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-4b-instruct.json", "title": "Hy3 vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-8b-instruct.json", "title": "Hy3 vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-qwopus3-8-27b-flash-v2.json", "title": "Hy3 vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/hy3-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-smollm3-3b.json", "title": "Hy3 vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/hy3-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-spark-x2-6-4b.json", "title": "Hy3 vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/hy3-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-27b.json", "title": "Hy3 vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-27b" }, { "json": 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MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-5.json", "title": "Kimi K3 vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-minimax-m2-5.json", "title": "Kolibri-1 vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m2-5.json", "title": "Laguna M.1 vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-minimax-m2-5" }, { "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minimax-m2-5.json", "title": "Laguna S 2.1 vs MiniMax-M2.5", "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minimax-m2-5" }, { "json": 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"https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-nano-30b-a3b.json", "title": "MiniMax-M2.5 vs Nemotron 3 Nano 30B A3B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-nano-30b-a3b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-nano-4b.json", "title": "MiniMax-M2.5 vs Nemotron 3 Nano 4B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-nano-4b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json", "title": "MiniMax-M2.5 vs Nemotron 3 Nano Omni 30B A3B Reasoning", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-nano-omni-30b-a3b-reasoning" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-super-120b-a12b.json", "title": "MiniMax-M2.5 vs Nemotron 3 Super 120B A12B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-super-120b-a12b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-ultra-550b-a55b.json", "title": "MiniMax-M2.5 vs Nemotron 3 Ultra 550B A55B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-nemotron-3-ultra-550b-a55b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-occamy-1-0.json", "title": "MiniMax-M2.5 vs occamy-1.0", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-occamy-1-0" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-olmo-3-7b-think.json", "title": "MiniMax-M2.5 vs Olmo 3 7B Think", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-olmo-3-7b-think" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-ornith-1-5-35b-a3b.json", "title": "MiniMax-M2.5 vs Ornith-1.5-35B-A3B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-ornith-1-5-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-ornith-1-5-397b.json", "title": "MiniMax-M2.5 vs Ornith-1.5-397B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-ornith-1-5-397b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-ornith-1-5-9b.json", "title": "MiniMax-M2.5 vs Ornith-1.5-9B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-ornith-1-5-9b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-30b-a3b-instruct-2507.json", "title": "MiniMax-M2.5 vs Qwen3-30B-A3B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-30b-a3b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-4b-instruct-2507.json", "title": "MiniMax-M2.5 vs Qwen3-4B-Instruct-2507", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-4b-instruct-2507" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-0-8b.json", "title": "MiniMax-M2.5 vs Qwen3.5-0.8B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-0-8b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-122b-a10b.json", "title": "MiniMax-M2.5 vs Qwen3.5-122B-A10B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-122b-a10b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-2b.json", "title": "MiniMax-M2.5 vs Qwen3.5-2B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-2b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-397b-a17b.json", "title": "MiniMax-M2.5 vs Qwen3.5-397B-A17B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-397b-a17b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-4b.json", "title": "MiniMax-M2.5 vs Qwen3.5-4B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-4b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-9b.json", "title": "MiniMax-M2.5 vs Qwen3.5-9B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-5-9b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-6-27b.json", "title": "MiniMax-M2.5 vs Qwen3.6-27B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-6-27b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-6-35b-a3b.json", "title": "MiniMax-M2.5 vs Qwen3.6-35B-A3B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-6-35b-a3b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-8-27b.json", "title": "MiniMax-M2.5 vs Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-8-flash-next.json", "title": "MiniMax-M2.5 vs Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-coder-30b-a3b-instruct.json", "title": "MiniMax-M2.5 vs Qwen3-Coder-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-coder-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-coder-next.json", "title": "MiniMax-M2.5 vs Qwen3-Coder-Next", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-coder-next" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-omni-30b-a3b-instruct.json", "title": "MiniMax-M2.5 vs Qwen3-Omni-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-omni-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-2b-instruct.json", "title": "MiniMax-M2.5 vs Qwen3-VL-2B-Instruct", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-2b-instruct" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-30b-a3b-instruct.json", "title": "MiniMax-M2.5 vs Qwen3-VL-30B-A3B-Instruct", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-30b-a3b-instruct" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-32b-instruct.json", "title": "MiniMax-M2.5 vs Qwen3-VL-32B-Instruct", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-32b-instruct" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-4b-instruct.json", "title": "MiniMax-M2.5 vs Qwen3-VL-4B-Instruct", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-4b-instruct" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-8b-instruct.json", "title": "MiniMax-M2.5 vs Qwen3-VL-8B-Instruct", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-vl-8b-instruct" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwopus3-8-27b-flash-v2.json", "title": "MiniMax-M2.5 vs Qwopus3.8-27B-Flash-V2", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwopus3-8-27b-flash-v2" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-smollm3-3b.json", "title": "MiniMax-M2.5 vs SmolLM3-3B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-smollm3-3b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-spark-x2-6-4b.json", "title": "MiniMax-M2.5 vs Spark-X2.6-4B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-spark-x2-6-4b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-27b.json", "title": "MiniMax-M2.5 vs Swift 1.5 Qwen3.8-27B", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-27b" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-flash-next.json", "title": "MiniMax-M2.5 vs Swift 1.5 Qwen3.8-Flash-Next", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-swift-1-5-qwen3-8-flash-next" }, { "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-thinkingcap-qwen3-8-27b.json", "title": "MiniMax-M2.5 vs ThinkingCap (Qwen3.8 27B)", "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-thinkingcap-qwen3-8-27b" } ], "scores": [ { "by": 16, "edge": "minimax-m2-5", "hy3": 57, "key": "capability", "minimax-m2-5": 73, "name": "Capability", "weight": 35 }, { "by": 5, "edge": "hy3", "hy3": 70, "key": "reach", "minimax-m2-5": 65, "name": "Reach", "weight": 25 }, { "by": 30, "edge": "hy3", "hy3": 60, "key": "risk", "minimax-m2-5": 30, "name": "Risk", "weight": 20 }, { "by": 0, "edge": "", "hy3": 75, "key": "interface", "minimax-m2-5": 75, "name": "Agent interface", "weight": 10 }, { "by": 34, "edge": "hy3", "hy3": 56, "key": "upkeep", "minimax-m2-5": 22, "name": "Documentation and upkeep", "weight": 10 } ], "summary": "Hy3 scores 62.6 (B) on agent readiness against MiniMax-M2.5's 57.5 (C), and leads in 3 of 5 scored categories. MiniMax-M2.5 leads on capability. Both do open-weight models you run yourself.", "tutorials": [], "verdicts": { "hy3": "Hy3 is a 295B mixture-of-experts model with 21B active, trained for several tool calls a turn, with per-request reasoning effort and 256K of context. It needs an 8-GPU server for FP8 or about 200 GB for a 4-bit build. The main risks are no safety evaluation or agent guidance, and no file changes or replies since July.", "minimax-m2-5": "MiniMax-M2.5 is a 230B mixture-of-experts model for coding and agent work, with parallel tool calls, a 196K context and parsers in vLLM and SGLang. It needs a 4-GPU server for FP8 or about 155 GB for a 4-bit build. The main risk is a licence replaced after release with a Prohibited Uses Policy while the card still says modified MIT." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5", "json": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5.min.md" }, "markdown": "Hy3 scores 62.6 (B) on agent readiness against MiniMax-M2.5's 57.5 (C), and leads in 3 of 5 scored categories. MiniMax-M2.5 leads on capability. Both do open-weight models you run yourself.\n\n- Hy3: grade B, 62.6/100, rank #27 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/hy3.md · JSON https://www.anchorterminal.com/api/v1/tools/hy3.json\n- MiniMax-M2.5: grade C, 57.5/100, rank #71 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/minimax-m2-5.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.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 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Hy3 (B)\n\nGood for: Teams with an 8-GPU server who want an agent-tuned MoE model under plain Apache 2.0\n\nAhead on:\n- Reach, 70 against 65\n- Risk, 60 against 30\n- Documentation and upkeep, 56 against 22\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 2.8 against 1.8 out of 5\n\nWatch for: 597.6 GB in BF16, 299.9 GB in FP8 and 168.5 GB at the smallest 4-bit build\n\n### MiniMax-M2.5 (C)\n\nGood for: Teams with a 4 to 8 GPU server who want an open agent and coding model with parallel tool calls and can live with its use policy\n\nAhead on:\n- Capability, 73 against 57\n\nWatch for: 230 GB in FP8, and about 155 GB for the smallest 4-bit library build, more than a 128 GB machine\n\n\n## Score by category\n\n| Category | Weight | Hy3 | MiniMax-M2.5 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 57 | 73 | MiniMax-M2.5 +16 |\n| Reach | 25% (25 this run) | 70 | 65 | Hy3 +5 |\n| Risk | 20% (20 this run) | 60 | 30 | Hy3 +30 |\n| Agent interface | 10% (10 this run) | 75 | 75 | even |\n| Documentation and upkeep | 10% (10 this run) | 56 | 22 | Hy3 +34 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **62.6 · B** | **57.5 · C** | |\n\n## Facts side by side\n\n| Fact | Hy3 | MiniMax-M2.5 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Tencent (Hy team) | MiniMax |\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 | MiniMax Model License (model) and modified MIT (code) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-20 | 2026-02-12 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models | | |\n| Terms restrict automated access | | |\n| Terms restrict benchmarking | | |\n| Terms or service can change without notice | | |\n| Arbitration or class-action waiver | | |\n| Agent reviews | 2.8/5 (4) | 1.8/5 (4) |\n\n## Verdicts\n\n**Hy3.** Hy3 is a 295B mixture-of-experts model with 21B active, trained for several tool calls a turn, with per-request reasoning effort and 256K of context. It needs an 8-GPU server for FP8 or about 200 GB for a 4-bit build. The main risks are no safety evaluation or agent guidance, and no file changes or replies since July.\n\n**MiniMax-M2.5.** MiniMax-M2.5 is a 230B mixture-of-experts model for coding and agent work, with parallel tool calls, a 196K context and parsers in vLLM and SGLang. It needs a 4-GPU server for FP8 or about 155 GB for a 4-bit build. The main risk is a licence replaced after release with a Prohibited Uses Policy while the card still says modified MIT.\n\n## Before you call either\n\n### Hy3\n\n1. Start it with vLLM on 8 GPUs, vllm serve tencent/Hy3-FP8 --tensor-parallel-size 8 --tool-call-parser hy_v3 --reasoning-parser hy_v3 --enable-auto-tool-choice --served-model-name hy3\n2. In SGLang use --tool-call-parser hunyuan --reasoning-parser hunyuan, as the card shows\n3. Pass reasoning_effort (no_think, low or high) in chat_template_kwargs; the default is no_think, and any other value raises a template error\n4. With the vLLM reasoning parser the chain of thought comes back in message.reasoning and the answer in message.content\n5. Earlier thinking stays in the prompt when tools are present; the template keys this on preserved_thinking, not the interleaved_thinking named in vLLM's recipe\n6. Use temperature 0.9 and top_p 1.0, the card's recommended sampling\n7. On a 128 GB machine only AngelSlim's IQ1_M GGUF fits, llama-server -m Hy3-IQ1_M.gguf -ctk q8_0 -ctv q8_0 -fa on -c 65536, with llama.cpp b11768 or later; at 89.4 GB × 1.2 it sits right at the 107.4 GB ceiling, so shorten the context if it fails to load, and expect a 1-bit build to fall short of Tencent's numbers\n8. Without the hardware, call it through Featherless AI or DeepInfra via Hugging Face's inference providers\n\n### MiniMax-M2.5\n\n1. Start it with vLLM on 4 GPUs of 96 GB, SAFETENSORS_FAST_GPU=1 vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code --tensor-parallel-size 4 --enable-auto-tool-choice --tool-call-parser minimax_m2 --reasoning-parser minimax_m2_append_think\n2. In SGLang use --tool-call-parser minimax-m2 and --reasoning-parser minimax-append-think, with --trust-remote-code\n3. MiniMax's guides budget 220 GB for the weights and 240 GB per 1M tokens of KV cache\n4. On a single large-memory machine, LM Studio's catalogue entry minimax/minimax-m2.5 lists a Q4_K_M GGUF of 138 GB and an MLX 4-bit of 129 GB (Mac only), and LM Studio states 121 GB minimum memory\n5. Sample with temperature 1.0, top_p 0.95 and top_k 40, as the card recommends\n6. Budget output tokens for thinking on every turn, since the template always opens a think block\n7. Read LICENSE-MODEL, not the card's licence link, before shipping, and keep the required Notice text in every copy\n8. Without the hardware, call it through Novita or Featherless AI; MiniMax's own API retires M2.5 on 18 November 2026\n\n## Questions\n\n### Which is better for AI agents, Hy3 or MiniMax-M2.5?\n\nHy3 scores 62.6 (B) on agent readiness against MiniMax-M2.5's 57.5 (C), and leads in 3 of 5 scored categories. MiniMax-M2.5 leads on capability.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hy3\", \"b\": \"minimax-m2-5\"}`. From a terminal: `anchor compare hy3 minimax-m2-5`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hy3.json and https://www.anchorterminal.com/api/v1/tools/minimax-m2-5.json\n\n## Other comparisons with Hy3 or MiniMax-M2.5\n\n- [Agents-A1-4B vs Hy3](https://www.anchorterminal.com/compare/agents-a1-4b-vs-hy3.md)\n- [Agents-A1-4B vs MiniMax-M2.5](https://www.anchorterminal.com/compare/agents-a1-4b-vs-minimax-m2-5.md)\n- [Apertus v1.5 8B vs Hy3](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-hy3.md)\n- [Apertus v1.5 8B vs MiniMax-M2.5](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minimax-m2-5.md)\n- [Apodex-1.1-mini vs Hy3](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-hy3.md)\n- [Apodex-1.1-mini vs MiniMax-M2.5](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minimax-m2-5.md)\n- [BigBang-v1 vs Hy3](https://www.anchorterminal.com/compare/bigbang-v1-vs-hy3.md)\n- [BigBang-v1 vs 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