{
  "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 and Kimi K3 score within a point of each other on agent readiness, 62.6 (B) and 62.4 (B). Kimi K3 leads on capability and risk.",
    "b": {
      "slug": "kimi-k3",
      "name": "Kimi K3",
      "vendor": "Moonshot AI",
      "vendorUrl": "https://www.moonshot.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Kimi K3 is Moonshot AI's open-weight multimodal mixture-of-experts model, 2.8T parameters with 104B active and a 1M-token context, trained in MXFP4 and published on Hugging Face under the modified-MIT Kimi K3 Licence.",
      "url": "https://www.anchorterminal.com/tools/kimi-k3",
      "markdownUrl": "https://www.anchorterminal.com/tools/kimi-k3.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/kimi-k3.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/kimi-k3.json",
      "repo": "https://huggingface.co/moonshotai/Kimi-K3",
      "license": "Kimi K3 License (modified MIT)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "moonshotai/Kimi-K3"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository is not gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under the Kimi K3 Licence. A company running a model-as-a-service business with more than $20 million in revenue over 12 months needs a separate agreement with Moonshot AI, at a price not published. Running it yourself costs the hardware, 1,561 GB of files (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/moonshotai/Kimi-K3",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "reasoning",
        "tool-calling",
        "modified-mit",
        "safetensors",
        "mxfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-09-02",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 62.4,
        "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": 24,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 75,
          "interface": 65,
          "reach": 50,
          "risk": 65,
          "upkeep": 41
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "Kimi K3 is a 2.8T multimodal agent model with a 1M-token context, parallel tool calls and per-request effort, for long coding and research sessions. Its 1,561 GB of files need a multi-node GPU cluster, so most agents will call a hosted copy. The main risks are Moonshot's Python running at load and prompt time, and no answers in its repository.",
        "bestFor": "Teams with a multi-node GPU cluster who want an open 1M-context agent model for long coding and research work",
        "strengths": [
          "1,048,576 tokens of context trained in, with indexed parallel tool calls in one turn",
          "Model code in released vLLM, SGLang and llama.cpp, with recipes linked from the card",
          "A third-party cyber evaluation by the UK AI Security Institute and CAISI",
          "Safetensors only, with a SHA-256 for every shard, downloadable with no account",
          "Served by Moonshot's API and five inference providers for agents without the hardware"
        ],
        "weaknesses": [
          "1,561 GB of files at its smallest publisher build, far beyond any single machine",
          "No Jinja template, so prompts, tokeniser and model load through Moonshot's Python with trust_remote_code",
          "No Moonshot reply in the 40 most recent discussions, and a tokeniser report waits unanswered",
          "No disclosure route for flaws and no prompt-injection guidance",
          "No training sources, sizes or knowledge cut-off, and the card leaves out limitations and languages"
        ],
        "agentNotes": [
          "Start it with SGLang on a node of 8 B300s, sglang serve --trust-remote-code --model-path moonshotai/Kimi-K3 --tp-size 8 --context-length 65536 --mem-fraction-static 0.82 --reasoning-parser kimi_k3 --tool-call-parser kimi_k3 --port 30000",
          "Use the kimi_k3 tool-call and reasoning parsers in vLLM or SGLang, and validate tool-call arguments against the schema, since vLLM's recipe says K3 sometimes emits a format its parser doesn't expect",
          "Pass the whole assistant message back every turn, reasoning_content and tool_calls included, or output becomes unstable",
          "Thinking is always on; set reasoning_effort to low or high when max is too slow",
          "Sampling per the card is temperature 1.0, with top-p 0.95 for single-step tasks and 1.0 for agentic ones",
          "Don't hand an ongoing session from another model to K3, and state boundaries in the system prompt, since Moonshot warns it can act on its own when intent is unclear",
          "Without the hardware, call it through Moonshot's API or an inference provider listed on its Hugging Face page"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "B",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 62.4
          }
        ],
        "editorialScores": {
          "capability": 75,
          "interface": 65,
          "reach": 50,
          "risk": 65,
          "upkeep": 41
        },
        "provenanceScore": 53,
        "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": "# SGLang, per its Kimi-K3 cookbook linked from the card (one node of 8 B300 GPUs)\nsglang serve --trust-remote-code --model-path moonshotai/Kimi-K3 --tp-size 8 \\\n  --context-length 65536 --mem-fraction-static 0.82 \\\n  --reasoning-parser kimi_k3 --tool-call-parser kimi_k3 --port 30000",
        "http": "curl http://localhost:30000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"moonshotai/Kimi-K3\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"reasoning_effort\": \"high\"\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/kimi-k3"
      },
      "weights": {
        "trainedBy": "Moonshot AI",
        "params": "2.8T",
        "active": "104B",
        "context": 1048576,
        "goodFor": "Large multimodal agent model for coding and long tool-calling sessions, text and images in, with always-on reasoning and JSON Schema output.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang"
        ],
        "builds": [
          {
            "name": "Kimi-K3",
            "url": "https://huggingface.co/moonshotai/Kimi-K3",
            "who": "publisher",
            "precision": "mxfp4",
            "sizeGB": 1560.9,
            "memoryGB": 2048,
            "format": "safetensors",
            "note": "Trained in MXFP4; the only build Moonshot publishes"
          }
        ],
        "run": "sglang serve --trust-remote-code --model-path moonshotai/Kimi-K3 --tp-size 8 --context-length 65536 --mem-fraction-static 0.82 --reasoning-parser kimi_k3 --tool-call-parser kimi_k3 --port 30000",
        "runBuild": "Kimi-K3",
        "checked": "2026-10-21",
        "minMemoryGB": 2048
      },
      "family": {
        "lab": "Moonshot AI (Kimi)",
        "family": "Kimi K3",
        "url": "https://www.anchorterminal.com/open-weights/#moonshot",
        "olderCount": 18,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Moonshot AI (the licence names Moonshot AI; the Kimi Platform terms name Moonshot AI PTE. LTD.)",
        "domain": "moonshot.ai",
        "domainRegistered": "",
        "domainNote": "moonshot.ai's registration date couldn't be read through RDAP on 21 October 2026.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/moonshotai/Kimi-K3/commits/main",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The licence names Moonshot AI. The Kimi Platform's terms (platform.kimi.ai/docs/agreement/modeluse) name Moonshot AI PTE. LTD. as the party for its API.",
          "Nothing is hosted, so the Kimi K3 Licence stands in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history. Its messages mostly say \"Update README.md\" or \"Update encoding_k3.py\" without saying what changed; the last change, on 2 September 2026, added an evaluation result.",
          "moonshot.ai, www.moonshot.ai, kimi.com and www.kimi.com answered /.well-known/security.txt with an HTML page and platform.kimi.ai with 404 on 21 October 2026, so no security.txt was found. The Kimi-K3 GitHub repository has no SECURITY.md."
        ],
        "score": 53
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/kimi-k3.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Tencent (Hy team)",
        "b": "Moonshot AI",
        "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": "Kimi K3 License (modified MIT)",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-07-20",
        "b": "2026-09-02",
        "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 and Kimi K3 score within a point of each other on agent readiness, 62.6 (B) and 62.4 (B). Kimi K3 leads on capability and risk.",
        "question": "Which is better for AI agents, Hy3 or Kimi K3?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reach, 70 against 50",
          "Agent interface, 75 against 65",
          "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, 75 against 57",
          "Risk, 65 against 60"
        ],
        "also": null,
        "goodFor": "Teams with a multi-node GPU cluster who want an open 1M-context agent model for long coding and research work",
        "slug": "kimi-k3",
        "watchFor": "1,561 GB of files at its smallest publisher build, far beyond any single 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-kimi-k3.json",
        "title": "Agents-A1-4B vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "Apertus v1.5 8B vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "Apodex-1.1-mini vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "BigBang-v1 vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "Cosmos-Reason2-2B vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "Darwin-36B-Opus vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "DeepSeek-V3.2 vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "DeepSeek V4.1 Flash vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "DeepSeek-V4-Flash-0731 vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "DiffusionGemma 26B A4B IT vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "Gemma 4 12B IT vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "Gemma 4 26B A4B IT vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "Gemma 4 31B IT vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "Gemma 4 E2B IT vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "Gemma 4 E4B IT vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "GLM-4.5-Air vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "GLM-4.7-Flash vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "GLM-5.3-Flash vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "GLM-5.3 vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "gpt-oss-120b vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "gpt-oss-20b vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-kimi-k3"
      },
      {
        "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-kimi-k3.json",
        "title": "Granite 4.2 3B vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-kimi-k3"
      },
      {
        "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-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-m2-5.json",
        "title": "Hy3 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-minimax-m2-5"
      },
      {
        "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",
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        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-0-8b.json",
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        "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",
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      {
        "json": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-5-2b.json",
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        "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",
        "title": "Hy3 vs Qwen3.8-Flash-Next",
        "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",
        "title": "Hy3 vs Qwen3-Coder-Next",
        "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",
        "title": "Hy3 vs Qwen3-Omni-30B-A3B-Instruct",
        "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",
        "title": "Hy3 vs Qwen3-VL-2B-Instruct",
        "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",
        "title": "Hy3 vs Qwen3-VL-30B-A3B-Instruct",
        "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",
        "title": "Hy3 vs Qwen3-VL-32B-Instruct",
        "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",
        "title": "Hy3 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-qwen3-vl-8b-instruct"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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": "https://www.anchorterminal.com/compare/hy3-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Hy3 vs Swift 1.5 Qwen3.8-Flash-Next",
        "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/hy3-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Hy3 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/hy3-vs-thinkingcap-qwen3-8-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-kimi-k3.json",
        "title": "Inkling-Small vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-kimi-k3"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-kimi-k3.json",
        "title": "Inkling vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-kimi-k3"
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      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-kimi-k3.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Kimi K3",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-kimi-k3"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-kolibri-1.json",
        "title": "Kimi K3 vs Kolibri-1",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-kolibri-1"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-m-1.json",
        "title": "Kimi K3 vs Laguna M.1",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-m-1"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-s-2-1.json",
        "title": "Kimi K3 vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-s-2-1"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-xs-2-1.json",
        "title": "Kimi K3 vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-xs-2-1"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-lfm2-5-2-6b.json",
        "title": "Kimi K3 vs LFM2.5-2.6B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-lfm2-5-2-6b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-ling-3-0-tiny.json",
        "title": "Kimi K3 vs Ling-3.0-tiny",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-ling-3-0-tiny"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-mimo-v2-6-distill-qwen-9b.json",
        "title": "Kimi K3 vs MiMo-V2.6 Distill Qwen 9B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-mimo-v2-6-distill-qwen-9b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm-o-4-5.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm-o-4-5"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm5-2b.json",
        "title": "Kimi K3 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minicpm5-2b"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-7.json",
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        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-minimax-m2-7"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-muse-glimmer-30b.json",
        "title": "Kimi K3 vs Muse Glimmer 30B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-muse-glimmer-30b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-5-lightning-30b-a3b.json",
        "title": "Kimi K3 vs Nemotron 3.5 Lightning 30B A3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-5-lightning-30b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-30b-a3b.json",
        "title": "Kimi K3 vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-4b.json",
        "title": "Kimi K3 vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Kimi K3 vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-super-120b-a12b.json",
        "title": "Kimi K3 vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-super-120b-a12b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Kimi K3 vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-nemotron-3-ultra-550b-a55b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0.json",
        "title": "Kimi K3 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-occamy-1-0"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-olmo-3-7b-think.json",
        "title": "Kimi K3 vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-olmo-3-7b-think"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-35b-a3b.json",
        "title": "Kimi K3 vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-397b.json",
        "title": "Kimi K3 vs Ornith-1.5-397B",
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-9b.json",
        "title": "Kimi K3 vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-ornith-1-5-9b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "Kimi K3 vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-30b-a3b-instruct-2507"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-4b-instruct-2507.json",
        "title": "Kimi K3 vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-0-8b.json",
        "title": "Kimi K3 vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-0-8b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-122b-a10b.json",
        "title": "Kimi K3 vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-122b-a10b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-2b.json",
        "title": "Kimi K3 vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-397b-a17b.json",
        "title": "Kimi K3 vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-397b-a17b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-4b.json",
        "title": "Kimi K3 vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-4b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-9b.json",
        "title": "Kimi K3 vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-5-9b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-6-27b.json",
        "title": "Kimi K3 vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-6-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-6-35b-a3b.json",
        "title": "Kimi K3 vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-6-35b-a3b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-8-27b.json",
        "title": "Kimi K3 vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-8-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-8-flash-next.json",
        "title": "Kimi K3 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-8-flash-next"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Kimi K3 vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-30b-a3b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-next.json",
        "title": "Kimi K3 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-coder-next"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Kimi K3 vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-2b-instruct.json",
        "title": "Kimi K3 vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-2b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Kimi K3 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-32b-instruct.json",
        "title": "Kimi K3 vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-4b-instruct.json",
        "title": "Kimi K3 vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-4b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-8b-instruct.json",
        "title": "Kimi K3 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Kimi K3 vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwopus3-8-27b-flash-v2"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-smollm3-3b.json",
        "title": "Kimi K3 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-spark-x2-6-4b.json",
        "title": "Kimi K3 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-spark-x2-6-4b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Kimi K3 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-swift-1-5-qwen3-8-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Kimi K3 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Kimi K3 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-thinkingcap-qwen3-8-27b"
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    "scores": [
      {
        "by": 18,
        "edge": "kimi-k3",
        "hy3": 57,
        "key": "capability",
        "kimi-k3": 75,
        "name": "Capability",
        "weight": 35
      },
      {
        "by": 20,
        "edge": "hy3",
        "hy3": 70,
        "key": "reach",
        "kimi-k3": 50,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 5,
        "edge": "kimi-k3",
        "hy3": 60,
        "key": "risk",
        "kimi-k3": 65,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 10,
        "edge": "hy3",
        "hy3": 75,
        "key": "interface",
        "kimi-k3": 65,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 15,
        "edge": "hy3",
        "hy3": 56,
        "key": "upkeep",
        "kimi-k3": 41,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Hy3 and Kimi K3 score within a point of each other on agent readiness, 62.6 (B) and 62.4 (B). Kimi K3 leads on capability and risk. 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.",
      "kimi-k3": "Kimi K3 is a 2.8T multimodal agent model with a 1M-token context, parallel tool calls and per-request effort, for long coding and research sessions. Its 1,561 GB of files need a multi-node GPU cluster, so most agents will call a hosted copy. The main risks are Moonshot's Python running at load and prompt time, and no answers in its repository."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/hy3-vs-kimi-k3",
    "json": "https://www.anchorterminal.com/compare/hy3-vs-kimi-k3.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/hy3-vs-kimi-k3.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/hy3-vs-kimi-k3.min.md"
  },
  "markdown": "Hy3 and Kimi K3 score within a point of each other on agent readiness, 62.6 (B) and 62.4 (B). Kimi K3 leads on capability and risk. 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- Kimi K3: grade B, 62.4/100, rank #29 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/kimi-k3.md · JSON https://www.anchorterminal.com/api/v1/tools/kimi-k3.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 50\n- Agent interface, 75 against 65\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### Kimi K3 (B)\n\nGood for: Teams with a multi-node GPU cluster who want an open 1M-context agent model for long coding and research work\n\nAhead on:\n- Capability, 75 against 57\n- Risk, 65 against 60\n\nWatch for: 1,561 GB of files at its smallest publisher build, far beyond any single machine\n\n\n## Score by category\n\n| Category | Weight | Hy3 | Kimi K3 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 57 | 75 | Kimi K3 +18 |\n| Reach | 25% (25 this run) | 70 | 50 | Hy3 +20 |\n| Risk | 20% (20 this run) | 60 | 65 | Kimi K3 +5 |\n| Agent interface | 10% (10 this run) | 75 | 65 | Hy3 +10 |\n| Documentation and upkeep | 10% (10 this run) | 56 | 41 | Hy3 +15 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **62.6 · B** | **62.4 · B** | |\n\n## Facts side by side\n\n| Fact | Hy3 | Kimi K3 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Tencent (Hy team) | Moonshot AI |\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 | Kimi K3 License (modified MIT) |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-20 | 2026-09-02 |\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**Kimi K3.** Kimi K3 is a 2.8T multimodal agent model with a 1M-token context, parallel tool calls and per-request effort, for long coding and research sessions. Its 1,561 GB of files need a multi-node GPU cluster, so most agents will call a hosted copy. The main risks are Moonshot's Python running at load and prompt time, and no answers in its repository.\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### Kimi K3\n\n1. Start it with SGLang on a node of 8 B300s, sglang serve --trust-remote-code --model-path moonshotai/Kimi-K3 --tp-size 8 --context-length 65536 --mem-fraction-static 0.82 --reasoning-parser kimi_k3 --tool-call-parser kimi_k3 --port 30000\n2. Use the kimi_k3 tool-call and reasoning parsers in vLLM or SGLang, and validate tool-call arguments against the schema, since vLLM's recipe says K3 sometimes emits a format its parser doesn't expect\n3. Pass the whole assistant message back every turn, reasoning_content and tool_calls included, or output becomes unstable\n4. Thinking is always on; set reasoning_effort to low or high when max is too slow\n5. Sampling per the card is temperature 1.0, with top-p 0.95 for single-step tasks and 1.0 for agentic ones\n6. Don't hand an ongoing session from another model to K3, and state boundaries in the system prompt, since Moonshot warns it can act on its own when intent is unclear\n7. Without the hardware, call it through Moonshot's API or an inference provider listed on its Hugging Face page\n\n## Questions\n\n### Which is better for AI agents, Hy3 or Kimi K3?\n\nHy3 and Kimi K3 score within a point of each other on agent readiness, 62.6 (B) and 62.4 (B). Kimi K3 leads on capability and risk.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/hy3-vs-kimi-k3.json, and with the fewest tokens: https://www.anchorterminal.com/compare/hy3-vs-kimi-k3.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"hy3\", \"b\": \"kimi-k3\"}`. From a terminal: `anchor compare hy3 kimi-k3`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/hy3.json and https://www.anchorterminal.com/api/v1/tools/kimi-k3.json\n\n## Other comparisons with Hy3 or Kimi K3\n\n- [Agents-A1-4B vs Hy3](https://www.anchorterminal.com/compare/agents-a1-4b-vs-hy3.md)\n- [Agents-A1-4B vs Kimi K3](https://www.anchorterminal.com/compare/agents-a1-4b-vs-kimi-k3.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 Kimi K3](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-kimi-k3.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 Kimi K3](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-kimi-k3.md)\n- [BigBang-v1 vs Hy3](https://www.anchorterminal.com/compare/bigbang-v1-vs-hy3.md)\n- [BigBang-v1 vs Kimi K3](https://www.anchorterminal.com/compare/bigbang-v1-vs-kimi-k3.md)\n- 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