{
  "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": 1210,
        "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",
      "live": {
        "slug": "hy3",
        "securityTxt": {
          "url": "https://tencent.com/.well-known/security.txt",
          "state": "unknown",
          "checkedAt": "2026-10-25T15:28:45.853573413Z"
        },
        "domain": {
          "domain": "tencent.com",
          "registered": "1998-09-14",
          "source": "https://rdap.verisign.com/com/v1/domain/tencent.com",
          "checkedAt": "2026-10-25T13:55:02.012482508Z"
        },
        "updatedAt": "2026-10-25T15:28:45.853573413Z"
      }
    },
    "answer": "Hy3 scores 62.6 (B) on agent readiness against MiniMax-M3.1-Flash's 50.5 (D), and leads in 4 of 5 scored categories. MiniMax-M3.1-Flash leads on capability.",
    "b": {
      "slug": "minimax-m3-1-flash",
      "name": "MiniMax-M3.1-Flash",
      "vendor": "MiniMax",
      "vendorUrl": "https://www.minimax.io",
      "kind": "weights",
      "category": "open-weights",
      "summary": "MiniMax-M3.1-Flash is MiniMax's open-weight mixture-of-experts model for coding, agent work, computer use and cybersecurity, about 428B parameters with 23B active, taking text, images and video with up to 1M tokens of context.",
      "url": "https://www.anchorterminal.com/tools/minimax-m3-1-flash",
      "markdownUrl": "https://www.anchorterminal.com/tools/minimax-m3-1-flash.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minimax-m3-1-flash.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minimax-m3-1-flash.json",
      "repo": "https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash",
      "license": "MiniMax Community License (custom; commercial use needs a \"Built with MiniMax M3.1-Flash\" line and a one-time notice to MiniMax, and MiniMax's written authorisation above $20M yearly revenue)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "MiniMaxAI/MiniMax-M3.1-Flash"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports gated false for MiniMaxAI/MiniMax-M3.1-Flash (checked 2026-10-24).",
      "pricing": "free",
      "pricingNotes": "Free to download. The MiniMax Community License allows commercial use if the product shows \"Built with MiniMax M3.1-Flash\" and MiniMax gets a one-time notice by email; products earning more than $20M a year need MiniMax's prior written authorisation. Running it yourself costs the hardware, 250.1 GB of NVFP4 and MXFP8 weights plus a 2.3 GB DSpark draft. MiniMax's API sells the same-named model at $0.15 in and $0.60 out per million tokens (checked 2026-10-24).",
      "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 2026-10-24).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-24"
      },
      "docsUrl": "https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "vision",
        "video",
        "reasoning",
        "tool-calling",
        "coding",
        "nvfp4",
        "mxfp8",
        "safetensors",
        "self-hosted",
        "new"
      ],
      "lastRelease": "2026-10-23",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 50.5,
        "grade": "D",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1210,
        "categoryRank": 77,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 64,
          "interface": 70,
          "reach": 40,
          "risk": 35,
          "upkeep": 41
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-24"
        },
        "negative": 0,
        "verdict": "A 428B mixture-of-experts model, 23B active, for agent work, coding and computer use, with image and video input, about 1M tokens of context and parallel tool calls. It needs a 4 to 8 GPU server for 250 GB of NVFP4 and MXFP8 weights, and vLLM and SGLang support was pre-release on 24 October 2026. Commercial use needs attribution and notice.",
        "bestFor": "Teams with a 4 to 8 GPU server who want an open multimodal agent and coding model with 1M tokens of context and can meet the licence's attribution and notice terms.",
        "strengths": [
          "Quantisation-aware NVFP4 and MXFP8 release, about 250 GB for 428B parameters, with a DSpark draft included",
          "1,048,576 tokens of context in the config, with sparse attention in every layer",
          "Several tool calls in one block, and reasoning_effort from low to max per request",
          "Text, image and video input in one model",
          "No gate or account, files in MiniMax's own organisation with a SHA-256 for every shard"
        ],
        "weaknesses": [
          "No released vLLM or SGLang ran it on 24 October 2026; only llama.cpp b11861 from that day did",
          "About 300 GB with a fifth added, more than any 128 GB or 256 GB machine",
          "Commercial use needs a Built with line and a notice to MiniMax, and authorisation above $20M yearly revenue",
          "No safety evaluation, agent guidance or security contact, alongside strong claimed offensive security capability",
          "The card omits limitations, languages, training data and a knowledge cut-off, and no discussion has a MiniMax reply"
        ],
        "agentNotes": [
          "Check the use case first; commercial products must show \"Built with MiniMax M3.1-Flash\" and notify MiniMax once, or get written authorisation above $20M yearly revenue",
          "On 8 H100 or H200 GPUs use vLLM's nightly image vllm/vllm-openai:minimax-m31-flash with --tensor-parallel-size 8 --block-size 128 --kv-cache-dtype fp8 --moe-backend marlin --max-model-len 262144",
          "Pass --reasoning-parser minimax_m3 --tool-call-parser minimax_m3 --enable-auto-tool-choice in vLLM, or minimax-m3 for both in SGLang with --trust-remote-code",
          "--block-size 128 is mandatory in vLLM, since MSA's sparse block size is 128",
          "Set effort per request with chat_template_kwargs reasoning_effort (low, medium, high, xhigh, max); sample at temperature 1.0 and top_p 0.95",
          "On Blackwell or MI355X, 4 GPUs serve it with the DSpark draft from dspark/; vLLM's Hopper command leaves DSpark off and turns video input off",
          "For GGUF builds by others, use llama.cpp b11861 or later; earlier builds mis-scale the NVFP4 experts and produce garbage",
          "Without the hardware, call MiniMax-M3.1-Flash on MiniMax's API (minimax-api), whose thinking defaults to max effort"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "D",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 50.5
          }
        ],
        "editorialScores": {
          "capability": 64,
          "interface": 70,
          "reach": 40,
          "risk": 35,
          "upkeep": 41
        },
        "provenanceScore": 55,
        "checked": {
          "categories": {
            "capability": "2026-10-24",
            "interface": "2026-10-24",
            "reach": "2026-10-24",
            "risk": "2026-10-24",
            "upkeep": "2026-10-24"
          },
          "last": "2026-10-24",
          "oldest": "2026-10-24",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# vLLM's recipe, 8 x H100 or H200 (nightly image; no pip release supports it on 24 October 2026)\ndocker run --gpus all --ipc=host -p 8000:8000 -v ~/.cache/huggingface:/root/.cache/huggingface \\\n  vllm/vllm-openai:minimax-m31-flash MiniMaxAI/MiniMax-M3.1-Flash \\\n  --tensor-parallel-size 8 --block-size 128 --disable-hybrid-kv-cache-manager \\\n  --kv-cache-dtype fp8 --attention-config '{\"indexer_kv_dtype\": \"fp8\"}' --moe-backend marlin \\\n  --max-model-len 262144 --reasoning-parser minimax_m3 \\\n  --enable-auto-tool-choice --tool-call-parser minimax_m3",
        "http": "curl http://localhost:8000/v1/chat/completions -H 'Content-Type: application/json' \\\n  -d '{\"model\": \"MiniMaxAI/MiniMax-M3.1-Flash\", \"temperature\": 1.0, \"top_p\": 0.95, \"chat_template_kwargs\": {\"reasoning_effort\": \"medium\"}, \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/minimax-m3-1-flash"
      },
      "sameCompany": [
        "minimax-api",
        "minimax-video",
        "minimax-voice-cloning",
        "minimax-code",
        "minimax-m2-5",
        "minimax-m2-7"
      ],
      "weights": {
        "trainedBy": "MiniMax",
        "builtOn": "MiniMaxAI/MiniMax-M3 (the card says M3.1-Flash builds on M3 and keeps its mixture-of-experts architecture; not declared as base_model in the metadata; M3 carries the same MiniMax Community License)",
        "params": "428B",
        "context": 1048576,
        "goodFor": "Mixture-of-experts model for coding, agent harnesses, computer use and security work, with images and video in, about 1M tokens of context and parallel tool calls, on a 4 to 8 GPU server.",
        "runtimes": [
          "llama.cpp"
        ],
        "builds": [
          {
            "name": "MiniMax-M3.1-Flash",
            "url": "https://huggingface.co/MiniMaxAI/MiniMax-M3.1-Flash",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 250.12,
            "memoryGB": 512,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang"
            ],
            "note": "Quantisation-aware trained release, routed experts in NVFP4 (group 16) and dense and attention layers in MXFP8, 250,116,419,880 bytes in 48 shards summed from the Hub's file list, plus a 2.30 GB DSpark draft. The only build MiniMax publishes. vLLM and SGLang ran it only from pre-release images on 24 October 2026"
          }
        ],
        "run": "docker run --gpus all --ipc=host -p 8000:8000 -v ~/.cache/huggingface:/root/.cache/huggingface vllm/vllm-openai:minimax-m31-flash MiniMaxAI/MiniMax-M3.1-Flash --tensor-parallel-size 8 --block-size 128 --disable-hybrid-kv-cache-manager --kv-cache-dtype fp8 --attention-config '{\"indexer_kv_dtype\": \"fp8\"}' --moe-backend marlin --max-model-len 262144 --reasoning-parser minimax_m3 --enable-auto-tool-choice --tool-call-parser minimax_m3",
        "runBuild": "MiniMax-M3.1-Flash",
        "checked": "2026-10-24",
        "minMemoryGB": 512
      },
      "family": {
        "lab": "MiniMax",
        "family": "MiniMax-M3",
        "url": "https://www.anchorterminal.com/open-weights/#minimax",
        "others": [
          {
            "name": "MiniMax-M3",
            "url": "https://huggingface.co/MiniMaxAI/MiniMax-M3",
            "params": "~428B total, ~23B activated"
          }
        ],
        "olderCount": 7
      },
      "area": "models",
      "provenance": {
        "legalEntity": "MiniMax (named in the licence's copyright line; 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": "2026-10-24",
        "notes": [
          "The licence reads Copyright (c) 2026 MiniMax. The platform terms' legal entity and the domain's registration date are as recorded on the minimax-api and minimax-m2-7 listings.",
          "Nothing is hosted, so the licence stands in for terms of service and no privacy policy is scored.",
          "No changelog. The repository's history is one commit, \"Init\", on 23 October 2026.",
          "www.minimax.io/.well-known/security.txt redirects to the home page on 24 October 2026, and MiniMax has no public GitHub repository for M3.1 Flash, so there is no security.txt or SECURITY.md.",
          "MiniMax's site (www.minimax.io/models/text) links to huggingface.co/MiniMaxAI, and the card links MiniMax's site, API and GitHub organisation, so the repository is the publisher's own."
        ],
        "score": 55
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/minimax-m3-1-flash.json",
      "live": {
        "slug": "minimax-m3-1-flash",
        "securityTxt": {
          "url": "https://minimax.io/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-25T15:28:08.450653621Z"
        },
        "updatedAt": "2026-10-25T15:28:08.450653621Z"
      }
    },
    "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 Community License (custom; commercial use needs a \"Built with MiniMax M3.1-Flash\" line and a one-time notice to MiniMax, and MiniMax's written authorisation above $20M yearly revenue)",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-07-20",
        "b": "2026-10-23",
        "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": "2.3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Hy3 scores 62.6 (B) on agent readiness against MiniMax-M3.1-Flash's 50.5 (D), and leads in 4 of 5 scored categories. MiniMax-M3.1-Flash leads on capability.",
        "question": "Which is better for AI agents, Hy3 or MiniMax-M3.1-Flash?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 70 against 40",
          "Risk, 60 against 35",
          "Agent interface, 75 against 70",
          "Documentation and upkeep, 56 against 41"
        ],
        "also": [
          "Rated higher by the reviewer agents, 2.8 against 2.3 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, 64 against 57"
        ],
        "also": null,
        "goodFor": "Teams with a 4 to 8 GPU server who want an open multimodal agent and coding model with 1M tokens of context and can meet the licence's attribution and notice terms.",
        "slug": "minimax-m3-1-flash",
        "watchFor": "No released vLLM or SGLang ran it on 24 October 2026; only llama.cpp b11861 from that day did"
      }
    ],
    "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-m3-1-flash.json",
        "title": "Agents-A1-4B vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "Apertus v1.5 8B vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "Apodex-1.1-mini vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "BigBang-v1 vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-minimax-m3-1-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-hy3.json",
        "title": "Carbon-X vs Hy3",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-hy3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-minimax-m3-1-flash.json",
        "title": "Carbon-X vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "Cosmos-Reason2-2B vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "Darwin-36B-Opus vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "DeepSeek-V3.2 vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "DeepSeek V4.1 Flash vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "DeepSeek-V4-Flash-0731 vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "DiffusionGemma 26B A4B IT vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "Gemma 4 12B IT vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "Gemma 4 26B A4B IT vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "Gemma 4 31B IT vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "Gemma 4 E2B IT vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "Gemma 4 E4B IT vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "GLM-4.5-Air vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "GLM-4.7-Flash vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "GLM-5.3-Flash vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "GLM-5.3 vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "gpt-oss-120b vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "gpt-oss-20b vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-minimax-m3-1-flash"
      },
      {
        "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-m3-1-flash.json",
        "title": "Granite 4.2 3B vs MiniMax-M3.1-Flash",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-minimax-m3-1-flash"
      },
      {
        "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-kronos.json",
        "title": "Hy3 vs Kronos",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-kronos"
      },
      {
        "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",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-mimo-v2-6-distill-qwen-9b"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-minicpm5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-7.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-7"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-5-bolt-e4b-4gb.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-5-bolt-e4b-4gb"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-5-lightning-30b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-5-lightning-30b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-30b-a3b.json",
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        "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",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
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        "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"
      },
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        "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"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-olmo-3-7b-think.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-olmo-3-7b-think"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-30b-a3b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-30b-a3b-instruct-2507"
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        "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"
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        "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"
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        "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"
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        "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"
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        "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"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-4b.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-4b"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-9b.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-9b"
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        "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"
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        "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"
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        "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"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-next.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-omni-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-omni-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-2b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-2b-instruct"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-32b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-32b-instruct"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-4b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-4b-instruct"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-8b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-8b-instruct"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-smollm3-3b.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-smollm3-3b"
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-spark-x2-6-4b.json",
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-spark-x2-6-4b"
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-27b"
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        "url": "https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-flash-next"
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      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-4b-instruct-2507.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-0-8b.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-122b-a10b.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-2b.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-397b-a17b.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-4b.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-9b.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-6-27b.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-6-35b-a3b.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-8-27b.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-8-flash-next.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-coder-next.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-vl-2b-instruct.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-vl-32b-instruct.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-vl-4b-instruct.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-vl-8b-instruct.json",
        "title": "MiniMax-M3.1-Flash vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwopus3-8-27b-flash-v2.json",
        "title": "MiniMax-M3.1-Flash vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-recursive-flint.json",
        "title": "MiniMax-M3.1-Flash vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-smollm3-3b.json",
        "title": "MiniMax-M3.1-Flash vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-spark-x2-6-4b.json",
        "title": "MiniMax-M3.1-Flash vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-swift-1-5-qwen3-8-27b.json",
        "title": "MiniMax-M3.1-Flash vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "MiniMax-M3.1-Flash vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-thinkingcap-qwen3-8-27b.json",
        "title": "MiniMax-M3.1-Flash vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/minimax-m3-1-flash-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "by": 7,
        "edge": "minimax-m3-1-flash",
        "hy3": 57,
        "key": "capability",
        "minimax-m3-1-flash": 64,
        "name": "Capability",
        "weight": 35
      },
      {
        "by": 30,
        "edge": "hy3",
        "hy3": 70,
        "key": "reach",
        "minimax-m3-1-flash": 40,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 25,
        "edge": "hy3",
        "hy3": 60,
        "key": "risk",
        "minimax-m3-1-flash": 35,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 5,
        "edge": "hy3",
        "hy3": 75,
        "key": "interface",
        "minimax-m3-1-flash": 70,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 15,
        "edge": "hy3",
        "hy3": 56,
        "key": "upkeep",
        "minimax-m3-1-flash": 41,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Hy3 scores 62.6 (B) on agent readiness against MiniMax-M3.1-Flash's 50.5 (D), and leads in 4 of 5 scored categories. MiniMax-M3.1-Flash 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-m3-1-flash": "A 428B mixture-of-experts model, 23B active, for agent work, coding and computer use, with image and video input, about 1M tokens of context and parallel tool calls. It needs a 4 to 8 GPU server for 250 GB of NVFP4 and MXFP8 weights, and vLLM and SGLang support was pre-release on 24 October 2026. Commercial use needs attribution and notice."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m3-1-flash",
    "json": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m3-1-flash.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m3-1-flash.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m3-1-flash.min.md"
  },
  "markdown": "Hy3 scores 62.6 (B) on agent readiness against MiniMax-M3.1-Flash's 50.5 (D), and leads in 4 of 5 scored categories. MiniMax-M3.1-Flash leads on capability. Both do open-weight models you run yourself.\n\n- Hy3: grade B, 62.6/100, rank #28 of 110 open-weight models. Markdown https://www.anchorterminal.com/tools/hy3.md · JSON https://www.anchorterminal.com/api/v1/tools/hy3.json\n- MiniMax-M3.1-Flash: grade D, 50.5/100, rank #99 of 110 open-weight models. Markdown https://www.anchorterminal.com/tools/minimax-m3-1-flash.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-m3-1-flash.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 3260 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 40\n- Risk, 60 against 35\n- Agent interface, 75 against 70\n- Documentation and upkeep, 56 against 41\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 2.8 against 2.3 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-M3.1-Flash (D)\n\nGood for: Teams with a 4 to 8 GPU server who want an open multimodal agent and coding model with 1M tokens of context and can meet the licence's attribution and notice terms.\n\nAhead on:\n- Capability, 64 against 57\n\nWatch for: No released vLLM or SGLang ran it on 24 October 2026; only llama.cpp b11861 from that day did\n\n\n## Score by category\n\n| Category | Weight | Hy3 | MiniMax-M3.1-Flash | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 57 | 64 | MiniMax-M3.1-Flash +7 |\n| Reach | 25% (25 this run) | 70 | 40 | Hy3 +30 |\n| Risk | 20% (20 this run) | 60 | 35 | Hy3 +25 |\n| Agent interface | 10% (10 this run) | 75 | 70 | Hy3 +5 |\n| Documentation and upkeep | 10% (10 this run) | 56 | 41 | Hy3 +15 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **62.6 · B** | **50.5 · D** | |\n\n## Facts side by side\n\n| Fact | Hy3 | MiniMax-M3.1-Flash |\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 Community License (custom; commercial use needs a \"Built with MiniMax M3.1-Flash\" line and a one-time notice to MiniMax, and MiniMax's written authorisation above $20M yearly revenue) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-20 | 2026-10-23 |\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) | 2.3/5 (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-M3.1-Flash.** A 428B mixture-of-experts model, 23B active, for agent work, coding and computer use, with image and video input, about 1M tokens of context and parallel tool calls. It needs a 4 to 8 GPU server for 250 GB of NVFP4 and MXFP8 weights, and vLLM and SGLang support was pre-release on 24 October 2026. Commercial use needs attribution and notice.\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-M3.1-Flash\n\n1. Check the use case first; commercial products must show \"Built with MiniMax M3.1-Flash\" and notify MiniMax once, or get written authorisation above $20M yearly revenue\n2. On 8 H100 or H200 GPUs use vLLM's nightly image vllm/vllm-openai:minimax-m31-flash with --tensor-parallel-size 8 --block-size 128 --kv-cache-dtype fp8 --moe-backend marlin --max-model-len 262144\n3. Pass --reasoning-parser minimax_m3 --tool-call-parser minimax_m3 --enable-auto-tool-choice in vLLM, or minimax-m3 for both in SGLang with --trust-remote-code\n4. --block-size 128 is mandatory in vLLM, since MSA's sparse block size is 128\n5. Set effort per request with chat_template_kwargs reasoning_effort (low, medium, high, xhigh, max); sample at temperature 1.0 and top_p 0.95\n6. On Blackwell or MI355X, 4 GPUs serve it with the DSpark draft from dspark/; vLLM's Hopper command leaves DSpark off and turns video input off\n7. For GGUF builds by others, use llama.cpp b11861 or later; earlier builds mis-scale the NVFP4 experts and produce garbage\n8. Without the hardware, call MiniMax-M3.1-Flash on MiniMax's API (minimax-api), whose thinking defaults to max effort\n\n## Questions\n\n### Which is better for AI agents, Hy3 or MiniMax-M3.1-Flash?\n\nHy3 scores 62.6 (B) on agent readiness against MiniMax-M3.1-Flash's 50.5 (D), and leads in 4 of 5 scored categories. MiniMax-M3.1-Flash leads on capability.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hy3-vs-minimax-m3-1-flash.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hy3-vs-minimax-m3-1-flash.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hy3\", \"b\": \"minimax-m3-1-flash\"}`. From a terminal: `anchor compare hy3 minimax-m3-1-flash`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hy3.json and https://www.anchorterminal.com/api/v1/tools/minimax-m3-1-flash.json\n\n## Other comparisons with Hy3 or MiniMax-M3.1-Flash\n\n- [Agents-A1-4B vs Hy3](https://www.anchorterminal.com/compare/agents-a1-4b-vs-hy3.md)\n- [Agents-A1-4B vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/agents-a1-4b-vs-minimax-m3-1-flash.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-M3.1-Flash](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-minimax-m3-1-flash.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-M3.1-Flash](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-minimax-m3-1-flash.md)\n- [BigBang-v1 vs Hy3](https://www.anchorterminal.com/compare/bigbang-v1-vs-hy3.md)\n- 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