{
  "data": {
    "a": {
      "slug": "deepseek-v3-2",
      "name": "DeepSeek-V3.2",
      "vendor": "DeepSeek",
      "vendorUrl": "https://www.deepseek.com",
      "kind": "weights",
      "category": "open-weights",
      "summary": "DeepSeek-V3.2 is DeepSeek's open-weight mixture-of-experts reasoning model with DeepSeek Sparse Attention, trained for tool use with a 128K-token context, published in FP8 under MIT. DeepSeek's API stopped serving it on 24 April 2026, moving to V4 Flash.",
      "url": "https://www.anchorterminal.com/tools/deepseek-v3-2",
      "markdownUrl": "https://www.anchorterminal.com/tools/deepseek-v3-2.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/deepseek-v3-2.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/deepseek-v3-2.json",
      "repo": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2",
      "license": "MIT",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "deepseek-ai/DeepSeek-V3.2"
        }
      ],
      "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 MIT licence. DeepSeek's own API served V3.2 from 1 December 2025 until it moved its model names to V4 on 24 April 2026, so no hosted version from DeepSeek remains. Running it yourself costs the hardware, 689.5 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/deepseek-ai/DeepSeek-V3.2",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "reasoning",
        "tool-calling",
        "mit",
        "safetensors",
        "fp8",
        "self-hosted"
      ],
      "lastRelease": "2025-12-01",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 58.6,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 54,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 69,
          "interface": 60,
          "reach": 60,
          "risk": 50,
          "upkeep": 34
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "DeepSeek-V3.2 is an MIT-licensed reasoning model trained for parallel tool calls, with thinking chosen per request, for long agent work. It needs about 690 GB of FP8 files, eight 80 GB GPUs in vLLM's recipe and prompts built from DeepSeek's Python. The main risk is neglect, with no file changes since December 2025 and no safety evaluation.",
        "bestFor": "Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider",
        "strengths": [
          "MIT licence with nothing added, downloadable with no account",
          "Released model code in vLLM, SGLang, llama.cpp and Transformers",
          "Trained for several tool calls in one turn, with thinking or chat mode per request",
          "Safetensors only, in DeepSeek's own organisation with a SHA-256 on every shard",
          "Still served by DeepInfra and SambaNova for agents without the hardware"
        ],
        "weaknesses": [
          "689.5 GB of FP8 files and no smaller build from DeepSeek or a runtime library, far beyond 107.4 GB",
          "No Jinja template, so prompts come from running DeepSeek's encoding code",
          "DeepSeek names no runtime tool parser and documents no structured output",
          "No change since 1 December 2025 and no DeepSeek reply in its discussions",
          "No safety evaluation, agent-use guidance, languages or knowledge cut-off published"
        ],
        "agentNotes": [
          "Start it with vLLM's recipe, vllm serve deepseek-ai/DeepSeek-V3.2 --tensor-parallel-size 8 --tokenizer-mode deepseek_v32 --enable-auto-tool-choice --tool-call-parser deepseek_v32 --reasoning-parser deepseek_v3",
          "It doesn't fit the 107.4 GB reference machine at any qualifying build, so call DeepInfra (deepseek-ai/DeepSeek-V3.2) or SambaNova (DeepSeek-V3.2) instead",
          "Outside vLLM, build prompts with encoding/encoding_dsv32.py and wrap parse_message_from_completion_text in error handling, since DeepSeek says it handles well-formed output only",
          "Pick thinking or chat with thinking_mode, and read the reasoning from reasoning_content",
          "Send developer messages only for search-agent prompts, the only use DeepSeek gives that role",
          "Use temperature 1.0 and top_p 0.95 and keep prompts within 128K tokens"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 58.6
          }
        ],
        "editorialScores": {
          "capability": 69,
          "interface": 60,
          "reach": 60,
          "risk": 50,
          "upkeep": 34
        },
        "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": "# vLLM's own recipe for DeepSeek-V3.2 (8 GPUs)\nvllm serve deepseek-ai/DeepSeek-V3.2 --tensor-parallel-size 8 \\\n  --tokenizer-mode deepseek_v32 --enable-auto-tool-choice \\\n  --tool-call-parser deepseek_v32 --reasoning-parser deepseek_v3\n# or DeepSeek's reference demo, from the inference folder\npython convert.py --hf-ckpt-path \"$HF_CKPT_PATH\" --save-path \"$SAVE_PATH\" --n-experts 256 --model-parallel 8\ntorchrun --nproc-per-node 8 generate.py --ckpt-path \"$SAVE_PATH\" --config config_671B_v3.2.json --interactive"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/deepseek-v3-2"
      },
      "sameCompany": [
        "deepseek-api",
        "deepseek-search-api",
        "deepseek-v4-1-flash",
        "deepseek-v4-flash-0731"
      ],
      "weights": {
        "trainedBy": "DeepSeek",
        "builtOn": "deepseek-ai/DeepSeek-V3.2-Exp-Base (continued from DeepSeek-V3.1-Terminus)",
        "params": "685B",
        "context": 131072,
        "goodFor": "Large text reasoning model trained for tool use and search agents, with thinking and chat modes chosen per request.",
        "runtimes": [
          "llama.cpp",
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "DeepSeek-V3.2",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 689.5,
            "memoryGB": 1024,
            "format": "safetensors",
            "note": "Native FP8 (E4M3) with BF16 and F32 for the rest; the only build DeepSeek publishes"
          }
        ],
        "run": "vllm serve deepseek-ai/DeepSeek-V3.2 --tensor-parallel-size 8 --tokenizer-mode deepseek_v32 --enable-auto-tool-choice --tool-call-parser deepseek_v32 --reasoning-parser deepseek_v3",
        "runBuild": "DeepSeek-V3.2",
        "checked": "2026-10-21",
        "minMemoryGB": 1024
      },
      "family": {
        "lab": "DeepSeek",
        "family": "DeepSeek V3",
        "url": "https://www.anchorterminal.com/open-weights/#deepseek",
        "others": [
          {
            "name": "DeepSeek-V3-Base",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3-Base",
            "params": "671B total, 37B activated"
          },
          {
            "name": "DeepSeek-V3",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3",
            "params": "671B total, 37B activated"
          },
          {
            "name": "DeepSeek-V3-0324",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3-0324",
            "params": "not stated on card"
          },
          {
            "name": "DeepSeek-V3.1-Base",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.1-Base",
            "params": "671B total, 37B activated"
          },
          {
            "name": "DeepSeek-V3.1",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.1",
            "params": "671B total, 37B activated"
          },
          {
            "name": "DeepSeek-V3.1-Terminus",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.1-Terminus",
            "params": "not stated on card"
          },
          {
            "name": "DeepSeek-V3.2-Exp-Base",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Exp-Base",
            "params": "not stated on card"
          },
          {
            "name": "DeepSeek-V3.2-Exp",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Exp",
            "params": "not stated on card (inference config named config_671B_v3.2.json)"
          },
          {
            "name": "DeepSeek-V3.2-Speciale",
            "url": "https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale",
            "params": "not stated on card"
          }
        ],
        "olderCount": 72
      },
      "area": "models",
      "provenance": {
        "legalEntity": "DeepSeek (the MIT licence names DeepSeek, and DeepSeek's platform terms name Hangzhou DeepSeek Artificial Intelligence Co., Ltd.)",
        "domain": "deepseek.com",
        "domainRegistered": "2000-08-13",
        "domainNote": "deepseek.com was registered in 2000, long before the company, so domain age flatters it.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The legal entity is the one DeepSeek's platform terms name, read for the deepseek-api listing. The weights' licence names only DeepSeek.",
          "Nothing is hosted, so the MIT licence stands in for terms of service and no privacy policy is scored.",
          "No changelog for the weights. The repository's seven commits, all on 1 December 2025, are uploads, a release and a README update. The DeepSeek-V3.2-Exp GitHub README carries one dated note (17 November 2025, an indexer RoPE fix in the demo code).",
          "RDAP gives 13 August 2000 as the registration date of deepseek.com (read 21 October 2026).",
          "deepseek.com/.well-known/security.txt and www.deepseek.com/.well-known/security.txt answered 404 on 21 October 2026.",
          "DeepSeek's site footer has a Report Security Issue link to security@deepseek.com, a company-wide address, read from https://www.deepseek.com/en/transparency/ on 21 October 2026."
        ],
        "score": 60
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/deepseek-v3-2.json"
    },
    "answer": "Laguna S 2.1 scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in every scored category.",
    "b": {
      "slug": "laguna-s-2-1",
      "name": "Laguna S 2.1",
      "vendor": "Poolside",
      "vendorUrl": "https://poolside.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Laguna S 2.1 is Poolside's open-weight Mixture-of-Experts model for agentic coding, 118B total and 8B active parameters, with switchable reasoning and a 1,048,576-token context, published on Hugging Face under OpenMDW-1.1.",
      "url": "https://www.anchorterminal.com/tools/laguna-s-2-1",
      "markdownUrl": "https://www.anchorterminal.com/tools/laguna-s-2-1.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/laguna-s-2-1.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/laguna-s-2-1.json",
      "repo": "https://huggingface.co/poolside/Laguna-S-2.1",
      "license": "OpenMDW-1.1",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-S-2.1"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-S-2.1-FP8"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-S-2.1-INT4"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-S-2.1-NVFP4"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-S-2.1-NVFP4-mlx"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-S-2.1-GGUF"
        },
        {
          "registry": "ollama",
          "name": "laguna-s-2.1"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The Hub reports gated false for the main repository and every build, although the card's metadata carries an unused gate description pointing to Poolside's privacy policy (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under OpenMDW-1.1. Running it yourself costs the hardware, 235.1 GB for the BF16 files, 96.0 GB for Poolside's Q4_K_M GGUF and 66 GB for Ollama's MLX NVFP4 build. Poolside's API, OpenRouter, Featherless AI, Vercel AI Gateway and Baseten host it (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/poolside/Laguna-S-2.1",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "coding",
        "reasoning",
        "tool-calling",
        "long-context",
        "openmdw-1.1",
        "safetensors",
        "gguf",
        "fp8",
        "nvfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-08-19",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 32,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "interface": 85,
          "reach": 75,
          "risk": 55,
          "upkeep": 41
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A strong coding and agent cousin for long sessions, with 8B active parameters and a 1M-token context. At 4-bit it needs a 96 to 128 GB machine, tight on a 128 GB one. The main risks are that nobody at Poolside answers its many reports, there are no safety results, and a build card misdescribes its file.",
        "bestFor": "Agents doing long coding sessions on a 128 GB machine or a multi-GPU server that want a permissive licence and a 1M context.",
        "strengths": [
          "Released support in llama.cpp, Ollama, vLLM, SGLang, Transformers and mlx-lm",
          "Poolside's own FP8, INT4, NVFP4, MLX and GGUF builds, plus DFlash draft models",
          "1,048,576 tokens of context, trained at that length per Poolside's build cards",
          "Permissive OpenMDW-1.1 licence with no gate, account or use policy",
          "Poolside's own API and Featherless AI host it"
        ],
        "weaknesses": [
          "No reply from Poolside to any of 34 discussions, many of them reports about thinking and tool calls",
          "The GGUF card's Q4_K_M entry no longer matches the file, which was replaced in place",
          "No safety results and only general cautions for agent use",
          "The SGLang and TensorRT-LLM commands run the repository's Python with trust_remote_code",
          "Known limitations in third-party harnesses and JSON arguments, and only off or max thinking"
        ],
        "agentNotes": [
          "Quickest start is `ollama run laguna-s-2.1`, 96 GB for the default Q4_K_M, or the 66 GB nvfp4 tag on Apple Silicon",
          "On our reference machine try `llama-server -hf poolside/Laguna-S-2.1-GGUF:Q4_K_M --jinja -c 65536`, from a llama.cpp release with the laguna architecture (b11772 has it). The 96 GB file leaves little room for context in 107.4 GB",
          "With vLLM or SGLang use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1`, and with TensorRT-LLM `--tool_parser poolside_v1 --reasoning_parser laguna`",
          "Thinking is on by default in the template, pass `chat_template_kwargs` with `enable_thinking` false to turn it off, and keep `reasoning_content` from earlier turns",
          "The GGUFs ship set to 262,144 tokens. For 1M with llama.cpp add `--ctx-size 1048576 --rope-scaling yarn --rope-scale 128 --yarn-orig-ctx 8192`, which Poolside says can cost quality",
          "Sampling per the generation config is temperature 1.0 and top_k 20, and Poolside suggests temperature 0.7 and top_p 0.95 at 1M",
          "Expect occasional tool-schema slips in harnesses unlike Poolside's own, and validate JSON arguments, which Poolside lists as known limitations"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 85,
          "reach": 75,
          "risk": 55,
          "upkeep": 41
        },
        "provenanceScore": 71,
        "checked": {
          "categories": {
            "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": "ollama run laguna-s-2.1\n# or, with vLLM on four GPUs:\nvllm serve poolside/Laguna-S-2.1 --tensor-parallel-size 4 --tool-call-parser poolside_v1 \\\n  --reasoning-parser poolside_v1 --enable-auto-tool-choice --default-chat-template-kwargs '{\"enable_thinking\": true}'",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"laguna-s-2.1\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/laguna-s-2-1"
      },
      "sameCompany": [
        "laguna-m-1",
        "laguna-xs-2-1"
      ],
      "weights": {
        "trainedBy": "Poolside",
        "params": "117.6B total, 8B active",
        "context": 1048576,
        "goodFor": "Long-horizon agentic coding and terminal work with up to 1M tokens of context, on a 128 GB machine at 4-bit or a multi-GPU server.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "LM Studio",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Laguna-S-2.1-NVFP4-mlx",
            "url": "https://huggingface.co/poolside/Laguna-S-2.1-NVFP4-mlx",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 71.9,
            "memoryGB": 96,
            "format": "mlx",
            "runsOn": [
              "MLX"
            ]
          },
          {
            "name": "ollama laguna-s-2.1:nvfp4",
            "url": "https://ollama.com/library/laguna-s-2.1:nvfp4",
            "who": "ollama",
            "precision": "nvfp4",
            "sizeGB": 66,
            "memoryGB": 96,
            "format": "mlx",
            "runsOn": [
              "Ollama"
            ],
            "note": "Ollama's MLX build, for Apple Silicon. Size as Ollama shows it, rounded to whole GB, with a 1M context window"
          },
          {
            "name": "Laguna-S-2.1-INT4",
            "url": "https://huggingface.co/poolside/Laguna-S-2.1-INT4",
            "who": "publisher",
            "precision": "int4 (w4a16)",
            "sizeGB": 99.7,
            "memoryGB": 128,
            "format": "safetensors"
          },
          {
            "name": "Laguna-S-2.1-NVFP4",
            "url": "https://huggingface.co/poolside/Laguna-S-2.1-NVFP4",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 99.7,
            "memoryGB": 128,
            "format": "safetensors",
            "note": "For NVIDIA Blackwell GPUs and DGX Spark"
          },
          {
            "name": "Laguna-S-2.1-GGUF Q4_K_M",
            "url": "https://huggingface.co/poolside/Laguna-S-2.1-GGUF",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 96,
            "memoryGB": 128,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "laguna-s-2.1-Q4_K_M.gguf, 96,031,829,760 bytes, replaced on 27 July 2026 with a mixed-precision build that keeps sensitive layers in BF16. The build card still lists it as 68 GB. The repository also holds Q8_0 (128.8 GB, 192 GB of memory), F16 (235.2 GB) and a 2.2 GB DFlash draft"
          },
          {
            "name": "ollama laguna-s-2.1:latest",
            "url": "https://ollama.com/library/laguna-s-2.1:latest",
            "who": "ollama",
            "precision": "q4_k_m",
            "sizeGB": 96,
            "memoryGB": 128,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "Size as Ollama's tags page shows it, rounded to whole GB. Its model blob (948255a146c0) isn't Poolside's GGUF file. The library also has q8_0 (128 GB), f16 (235 GB) and MLX tags"
          },
          {
            "name": "Laguna-S-2.1-FP8",
            "url": "https://huggingface.co/poolside/Laguna-S-2.1-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 131.3,
            "memoryGB": 192,
            "format": "safetensors"
          },
          {
            "name": "Laguna-S-2.1",
            "url": "https://huggingface.co/poolside/Laguna-S-2.1",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 235.1,
            "memoryGB": 512,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang",
              "Transformers"
            ]
          }
        ],
        "run": "llama-server -hf poolside/Laguna-S-2.1-GGUF:Q4_K_M --jinja -c 65536 --port 8000",
        "runBuild": "Laguna-S-2.1-GGUF Q4_K_M",
        "checked": "2026-10-21",
        "minMemoryGB": 96
      },
      "family": {
        "lab": "Poolside",
        "family": "Laguna 2 (XS.2, XS 2.1, S 2.1)",
        "url": "https://www.anchorterminal.com/open-weights/#poolside",
        "others": [
          {
            "name": "Laguna-XS-2.1",
            "url": "https://huggingface.co/poolside/Laguna-XS-2.1",
            "params": "33.44B (Hub safetensors count; the name gives only the size class XS)",
            "listing": "https://www.anchorterminal.com/tools/laguna-xs-2-1"
          },
          {
            "name": "Laguna-S-2.1-base",
            "url": "https://huggingface.co/poolside/Laguna-S-2.1-base",
            "params": "not stated (no safetensors count on the Hub; the instruct model is 117.56B)"
          },
          {
            "name": "Laguna-XS.2",
            "url": "https://huggingface.co/poolside/Laguna-XS.2",
            "params": "33.44B (Hub safetensors count; the name gives only the size class XS)"
          }
        ],
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Poolside, Inc. (named in Poolside's Terms of Use)",
        "domain": "poolside.ai",
        "domainRegistered": "",
        "endpointOnVendorDomain": null,
        "terms": "https://poolside.ai/legal/eula",
        "privacy": "https://poolside.ai/legal/privacy",
        "statusPage": "",
        "changelog": "https://docs.poolside.ai/release-notes/models",
        "securityTxt": "valid",
        "checked": "2026-10-21",
        "notes": [
          "The Hugging Face organisation poolside is verified, and Poolside's release post links the repository.",
          "Nothing is hosted for this listing, so the OpenMDW-1.1 licence stands in for terms of service and no privacy policy is scored.",
          "Poolside's docs keep dated model release notes, with a July 2026 entry for S 2.1.",
          "security.txt is PGP-signed, names a security contact at poolside.ai and expires on 1 April 2028. The domain's registration date wasn't checked."
        ],
        "score": 71
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/laguna-s-2-1.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "DeepSeek",
        "b": "Poolside",
        "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": "MIT",
        "b": "OpenMDW-1.1",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2025-12-01",
        "b": "2026-08-19",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "",
        "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": "2.3/5 (4)",
        "b": "2.3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Laguna S 2.1 scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in every scored category.",
        "question": "Which is better for AI agents, DeepSeek-V3.2 or Laguna S 2.1?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": null,
        "also": null,
        "goodFor": "Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider",
        "slug": "deepseek-v3-2",
        "watchFor": "689.5 GB of FP8 files and no smaller build from DeepSeek or a runtime library, far beyond 107.4 GB"
      },
      {
        "aheadOn": [
          "Reach, 75 against 60",
          "Risk, 55 against 50",
          "Agent interface, 85 against 60",
          "Documentation and upkeep, 41 against 34"
        ],
        "also": null,
        "goodFor": "Agents doing long coding sessions on a 128 GB machine or a multi-GPU server that want a permissive licence and a 1M context.",
        "slug": "laguna-s-2-1",
        "watchFor": "No reply from Poolside to any of 34 discussions, many of them reports about thinking and tool calls"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-deepseek-v3-2.json",
        "title": "Agents-A1-4B vs DeepSeek-V3.2",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-deepseek-v3-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-s-2-1.json",
        "title": "Agents-A1-4B vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-deepseek-v3-2.json",
        "title": "Apertus v1.5 8B vs DeepSeek-V3.2",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-deepseek-v3-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-s-2-1.json",
        "title": "Apertus v1.5 8B vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-deepseek-v3-2.json",
        "title": "Apodex-1.1-mini vs DeepSeek-V3.2",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-deepseek-v3-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-s-2-1.json",
        "title": "Apodex-1.1-mini vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v3-2.json",
        "title": "BigBang-v1 vs DeepSeek-V3.2",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v3-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-s-2-1.json",
        "title": "BigBang-v1 vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v3-2.json",
        "title": "Cosmos-Reason2-2B vs DeepSeek-V3.2",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v3-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-s-2-1.json",
        "title": "Cosmos-Reason2-2B vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-deepseek-v3-2.json",
        "title": "Darwin-36B-Opus vs DeepSeek-V3.2",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-deepseek-v3-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-s-2-1.json",
        "title": "Darwin-36B-Opus vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-deepseek-v4-1-flash.json",
        "title": "DeepSeek-V3.2 vs DeepSeek V4.1 Flash",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-deepseek-v4-1-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-deepseek-v4-flash-0731.json",
        "title": "DeepSeek-V3.2 vs DeepSeek-V4-Flash-0731",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-deepseek-v4-flash-0731"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-diffusiongemma-26b-a4b-it.json",
        "title": "DeepSeek-V3.2 vs DiffusionGemma 26B A4B IT",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-diffusiongemma-26b-a4b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-12b-it.json",
        "title": "DeepSeek-V3.2 vs Gemma 4 12B IT",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-12b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-26b-a4b-it.json",
        "title": "DeepSeek-V3.2 vs Gemma 4 26B A4B IT",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-26b-a4b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-31b-it.json",
        "title": "DeepSeek-V3.2 vs Gemma 4 31B IT",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-31b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-e2b-it.json",
        "title": "DeepSeek-V3.2 vs Gemma 4 E2B IT",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-e2b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-e4b-it.json",
        "title": "DeepSeek-V3.2 vs Gemma 4 E4B IT",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-e4b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-4-5-air.json",
        "title": "DeepSeek-V3.2 vs GLM-4.5-Air",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-4-5-air"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-4-7-flash.json",
        "title": "DeepSeek-V3.2 vs GLM-4.7-Flash",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-4-7-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3.json",
        "title": "DeepSeek-V3.2 vs GLM-5.3",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3-flash.json",
        "title": "DeepSeek-V3.2 vs GLM-5.3-Flash",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gpt-oss-120b.json",
        "title": "DeepSeek-V3.2 vs gpt-oss-120b",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gpt-oss-120b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gpt-oss-20b.json",
        "title": "DeepSeek-V3.2 vs gpt-oss-20b",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gpt-oss-20b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-granite-4-2-3b.json",
        "title": "DeepSeek-V3.2 vs Granite 4.2 3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-granite-4-2-3b"
      },
      {
        "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-inkling.json",
        "title": "DeepSeek-V3.2 vs Inkling",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-small.json",
        "title": "DeepSeek-V3.2 vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-small"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-internvl3-5-gpt-oss-20b-a4b-preview.json",
        "title": "DeepSeek-V3.2 vs InternVL3.5-GPT-OSS-20B-A4B-Preview",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-internvl3-5-gpt-oss-20b-a4b-preview"
      },
      {
        "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-v3-2-vs-kolibri-1.json",
        "title": "DeepSeek-V3.2 vs Kolibri-1",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-kolibri-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-m-1.json",
        "title": "DeepSeek-V3.2 vs Laguna M.1",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-m-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-xs-2-1.json",
        "title": "DeepSeek-V3.2 vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-xs-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-lfm2-5-2-6b.json",
        "title": "DeepSeek-V3.2 vs LFM2.5-2.6B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-lfm2-5-2-6b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ling-3-0-tiny.json",
        "title": "DeepSeek-V3.2 vs Ling-3.0-tiny",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ling-3-0-tiny"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-mimo-v2-6-distill-qwen-9b.json",
        "title": "DeepSeek-V3.2 vs MiMo-V2.6 Distill Qwen 9B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-mimo-v2-6-distill-qwen-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm-o-4-5.json",
        "title": "DeepSeek-V3.2 vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b.json",
        "title": "DeepSeek-V3.2 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-5.json",
        "title": "DeepSeek-V3.2 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-7.json",
        "title": "DeepSeek-V3.2 vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-muse-glimmer-30b.json",
        "title": "DeepSeek-V3.2 vs Muse Glimmer 30B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-muse-glimmer-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-5-lightning-30b-a3b.json",
        "title": "DeepSeek-V3.2 vs Nemotron 3.5 Lightning 30B A3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-5-lightning-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-30b-a3b.json",
        "title": "DeepSeek-V3.2 vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-4b.json",
        "title": "DeepSeek-V3.2 vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "DeepSeek-V3.2 vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-super-120b-a12b.json",
        "title": "DeepSeek-V3.2 vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-super-120b-a12b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "DeepSeek-V3.2 vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-occamy-1-0.json",
        "title": "DeepSeek-V3.2 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-olmo-3-7b-think.json",
        "title": "DeepSeek-V3.2 vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-35b-a3b.json",
        "title": "DeepSeek-V3.2 vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-397b.json",
        "title": "DeepSeek-V3.2 vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-9b.json",
        "title": "DeepSeek-V3.2 vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "DeepSeek-V3.2 vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-4b-instruct-2507.json",
        "title": "DeepSeek-V3.2 vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-0-8b.json",
        "title": "DeepSeek-V3.2 vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-122b-a10b.json",
        "title": "DeepSeek-V3.2 vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-2b.json",
        "title": "DeepSeek-V3.2 vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-397b-a17b.json",
        "title": "DeepSeek-V3.2 vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-4b.json",
        "title": "DeepSeek-V3.2 vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-9b.json",
        "title": "DeepSeek-V3.2 vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-6-27b.json",
        "title": "DeepSeek-V3.2 vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-6-35b-a3b.json",
        "title": "DeepSeek-V3.2 vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-27b.json",
        "title": "DeepSeek-V3.2 vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-flash-next.json",
        "title": "DeepSeek-V3.2 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-next.json",
        "title": "DeepSeek-V3.2 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-2b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-32b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-4b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-8b-instruct.json",
        "title": "DeepSeek-V3.2 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwopus3-8-27b-flash-v2.json",
        "title": "DeepSeek-V3.2 vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-smollm3-3b.json",
        "title": "DeepSeek-V3.2 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-spark-x2-6-4b.json",
        "title": "DeepSeek-V3.2 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-27b.json",
        "title": "DeepSeek-V3.2 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "DeepSeek-V3.2 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-thinkingcap-qwen3-8-27b.json",
        "title": "DeepSeek-V3.2 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-s-2-1.json",
        "title": "DeepSeek V4.1 Flash vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-s-2-1.json",
        "title": "DeepSeek-V4-Flash-0731 vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-s-2-1.json",
        "title": "DiffusionGemma 26B A4B IT vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-s-2-1.json",
        "title": "Gemma 4 12B IT vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-s-2-1.json",
        "title": "Gemma 4 26B A4B IT vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-s-2-1.json",
        "title": "Gemma 4 31B IT vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-s-2-1.json",
        "title": "Gemma 4 E2B IT vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-s-2-1.json",
        "title": "Gemma 4 E4B IT vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-s-2-1.json",
        "title": "GLM-4.5-Air vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-s-2-1.json",
        "title": "GLM-4.7-Flash vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-s-2-1.json",
        "title": "GLM-5.3-Flash vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-s-2-1.json",
        "title": "GLM-5.3 vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-s-2-1.json",
        "title": "gpt-oss-120b vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-s-2-1.json",
        "title": "gpt-oss-20b vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-s-2-1.json",
        "title": "Granite 4.2 3B vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-s-2-1"
      },
      {
        "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/inkling-small-vs-laguna-s-2-1.json",
        "title": "Inkling-Small vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1.json",
        "title": "Inkling vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-s-2-1.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-s-2-1"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-s-2-1.json",
        "title": "Kolibri-1 vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-laguna-s-2-1.json",
        "title": "Laguna M.1 vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-laguna-s-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-laguna-xs-2-1.json",
        "title": "Laguna S 2.1 vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-laguna-xs-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm2-5-2-6b.json",
        "title": "Laguna S 2.1 vs LFM2.5-2.6B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm2-5-2-6b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ling-3-0-tiny.json",
        "title": "Laguna S 2.1 vs Ling-3.0-tiny",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ling-3-0-tiny"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-mimo-v2-6-distill-qwen-9b.json",
        "title": "Laguna S 2.1 vs MiMo-V2.6 Distill Qwen 9B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-mimo-v2-6-distill-qwen-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm-o-4-5.json",
        "title": "Laguna S 2.1 vs MiniCPM-o 4.5",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm-o-4-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm5-2b.json",
        "title": "Laguna S 2.1 vs MiniCPM5-2B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minimax-m2-5.json",
        "title": "Laguna S 2.1 vs MiniMax-M2.5",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minimax-m2-5"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minimax-m2-7.json",
        "title": "Laguna S 2.1 vs MiniMax-M2.7",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minimax-m2-7"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-muse-glimmer-30b.json",
        "title": "Laguna S 2.1 vs Muse Glimmer 30B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-muse-glimmer-30b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-5-lightning-30b-a3b.json",
        "title": "Laguna S 2.1 vs Nemotron 3.5 Lightning 30B A3B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-5-lightning-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-30b-a3b.json",
        "title": "Laguna S 2.1 vs Nemotron 3 Nano 30B A3B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-30b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-4b.json",
        "title": "Laguna S 2.1 vs Nemotron 3 Nano 4B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "Laguna S 2.1 vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-super-120b-a12b.json",
        "title": "Laguna S 2.1 vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-super-120b-a12b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "Laguna S 2.1 vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-occamy-1-0.json",
        "title": "Laguna S 2.1 vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-olmo-3-7b-think.json",
        "title": "Laguna S 2.1 vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-35b-a3b.json",
        "title": "Laguna S 2.1 vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-397b.json",
        "title": "Laguna S 2.1 vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-9b.json",
        "title": "Laguna S 2.1 vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "Laguna S 2.1 vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-4b-instruct-2507.json",
        "title": "Laguna S 2.1 vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-0-8b.json",
        "title": "Laguna S 2.1 vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-0-8b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-122b-a10b.json",
        "title": "Laguna S 2.1 vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-2b.json",
        "title": "Laguna S 2.1 vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-397b-a17b.json",
        "title": "Laguna S 2.1 vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-4b.json",
        "title": "Laguna S 2.1 vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-9b.json",
        "title": "Laguna S 2.1 vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-6-27b.json",
        "title": "Laguna S 2.1 vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-6-35b-a3b.json",
        "title": "Laguna S 2.1 vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-8-27b.json",
        "title": "Laguna S 2.1 vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-8-flash-next.json",
        "title": "Laguna S 2.1 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Laguna S 2.1 vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-coder-next.json",
        "title": "Laguna S 2.1 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Laguna S 2.1 vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-2b-instruct.json",
        "title": "Laguna S 2.1 vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Laguna S 2.1 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-32b-instruct.json",
        "title": "Laguna S 2.1 vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-4b-instruct.json",
        "title": "Laguna S 2.1 vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-8b-instruct.json",
        "title": "Laguna S 2.1 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Laguna S 2.1 vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-smollm3-3b.json",
        "title": "Laguna S 2.1 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-spark-x2-6-4b.json",
        "title": "Laguna S 2.1 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Laguna S 2.1 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Laguna S 2.1 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Laguna S 2.1 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 15,
        "deepseek-v3-2": 60,
        "edge": "laguna-s-2-1",
        "key": "reach",
        "laguna-s-2-1": 75,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 5,
        "deepseek-v3-2": 50,
        "edge": "laguna-s-2-1",
        "key": "risk",
        "laguna-s-2-1": 55,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 25,
        "deepseek-v3-2": 60,
        "edge": "laguna-s-2-1",
        "key": "interface",
        "laguna-s-2-1": 85,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 7,
        "deepseek-v3-2": 34,
        "edge": "laguna-s-2-1",
        "key": "upkeep",
        "laguna-s-2-1": 41,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Laguna S 2.1 scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in every scored category. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "deepseek-v3-2": "DeepSeek-V3.2 is an MIT-licensed reasoning model trained for parallel tool calls, with thinking chosen per request, for long agent work. It needs about 690 GB of FP8 files, eight 80 GB GPUs in vLLM's recipe and prompts built from DeepSeek's Python. The main risk is neglect, with no file changes since December 2025 and no safety evaluation.",
      "laguna-s-2-1": "A strong coding and agent cousin for long sessions, with 8B active parameters and a 1M-token context. At 4-bit it needs a 96 to 128 GB machine, tight on a 128 GB one. The main risks are that nobody at Poolside answers its many reports, there are no safety results, and a build card misdescribes its file."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-s-2-1",
    "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-s-2-1.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-s-2-1.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-s-2-1.min.md"
  },
  "markdown": "Laguna S 2.1 scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in every scored category. Both do open-weight models you run yourself.\n\n- DeepSeek-V3.2: grade C, 58.6/100, rank #65 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/deepseek-v3-2.md · JSON https://www.anchorterminal.com/api/v1/tools/deepseek-v3-2.json\n- Laguna S 2.1: grade C, 61/100, rank #39 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-s-2-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-s-2-1.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### DeepSeek-V3.2 (C)\n\nGood for: Teams with an eight-GPU server who want an MIT agent model with broad runtime support, or agents calling it through a hosted provider\n\nWatch for: 689.5 GB of FP8 files and no smaller build from DeepSeek or a runtime library, far beyond 107.4 GB\n\n### Laguna S 2.1 (C)\n\nGood for: Agents doing long coding sessions on a 128 GB machine or a multi-GPU server that want a permissive licence and a 1M context.\n\nAhead on:\n- Reach, 75 against 60\n- Risk, 55 against 50\n- Agent interface, 85 against 60\n- Documentation and upkeep, 41 against 34\n\nWatch for: No reply from Poolside to any of 34 discussions, many of them reports about thinking and tool calls\n\n\n## Score by category\n\n| Category | Weight | DeepSeek-V3.2 | Laguna S 2.1 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 60 | 75 | Laguna S 2.1 +15 |\n| Risk | 20% (20 this run) | 50 | 55 | Laguna S 2.1 +5 |\n| Agent interface | 10% (10 this run) | 60 | 85 | Laguna S 2.1 +25 |\n| Documentation and upkeep | 10% (10 this run) | 34 | 41 | Laguna S 2.1 +7 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **58.6 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | DeepSeek-V3.2 | Laguna S 2.1 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | DeepSeek | Poolside |\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 | MIT | OpenMDW-1.1 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2025-12-01 | 2026-08-19 |\n| Terms last updated | no document linked |  |\n| Privacy policy last updated | 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 | 2.3/5 (4) | 2.3/5 (4) |\n\n## Verdicts\n\n**DeepSeek-V3.2.** DeepSeek-V3.2 is an MIT-licensed reasoning model trained for parallel tool calls, with thinking chosen per request, for long agent work. It needs about 690 GB of FP8 files, eight 80 GB GPUs in vLLM's recipe and prompts built from DeepSeek's Python. The main risk is neglect, with no file changes since December 2025 and no safety evaluation.\n\n**Laguna S 2.1.** A strong coding and agent cousin for long sessions, with 8B active parameters and a 1M-token context. At 4-bit it needs a 96 to 128 GB machine, tight on a 128 GB one. The main risks are that nobody at Poolside answers its many reports, there are no safety results, and a build card misdescribes its file.\n\n## Before you call either\n\n### DeepSeek-V3.2\n\n1. Start it with vLLM's recipe, vllm serve deepseek-ai/DeepSeek-V3.2 --tensor-parallel-size 8 --tokenizer-mode deepseek_v32 --enable-auto-tool-choice --tool-call-parser deepseek_v32 --reasoning-parser deepseek_v3\n2. It doesn't fit the 107.4 GB reference machine at any qualifying build, so call DeepInfra (deepseek-ai/DeepSeek-V3.2) or SambaNova (DeepSeek-V3.2) instead\n3. Outside vLLM, build prompts with encoding/encoding_dsv32.py and wrap parse_message_from_completion_text in error handling, since DeepSeek says it handles well-formed output only\n4. Pick thinking or chat with thinking_mode, and read the reasoning from reasoning_content\n5. Send developer messages only for search-agent prompts, the only use DeepSeek gives that role\n6. Use temperature 1.0 and top_p 0.95 and keep prompts within 128K tokens\n\n### Laguna S 2.1\n\n1. Quickest start is `ollama run laguna-s-2.1`, 96 GB for the default Q4_K_M, or the 66 GB nvfp4 tag on Apple Silicon\n2. On our reference machine try `llama-server -hf poolside/Laguna-S-2.1-GGUF:Q4_K_M --jinja -c 65536`, from a llama.cpp release with the laguna architecture (b11772 has it). The 96 GB file leaves little room for context in 107.4 GB\n3. With vLLM or SGLang use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1`, and with TensorRT-LLM `--tool_parser poolside_v1 --reasoning_parser laguna`\n4. Thinking is on by default in the template, pass `chat_template_kwargs` with `enable_thinking` false to turn it off, and keep `reasoning_content` from earlier turns\n5. The GGUFs ship set to 262,144 tokens. For 1M with llama.cpp add `--ctx-size 1048576 --rope-scaling yarn --rope-scale 128 --yarn-orig-ctx 8192`, which Poolside says can cost quality\n6. Sampling per the generation config is temperature 1.0 and top_k 20, and Poolside suggests temperature 0.7 and top_p 0.95 at 1M\n7. Expect occasional tool-schema slips in harnesses unlike Poolside's own, and validate JSON arguments, which Poolside lists as known limitations\n\n## Questions\n\n### Which is better for AI agents, DeepSeek-V3.2 or Laguna S 2.1?\n\nLaguna S 2.1 scores 61 (C) on agent readiness against DeepSeek-V3.2's 58.6 (C), and leads in every scored category.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-s-2-1.json, and with the fewest tokens: https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-s-2-1.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"deepseek-v3-2\", \"b\": \"laguna-s-2-1\"}`. From a terminal: `anchor compare deepseek-v3-2 laguna-s-2-1`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/deepseek-v3-2.json and https://www.anchorterminal.com/api/v1/tools/laguna-s-2-1.json\n\n## Other comparisons with DeepSeek-V3.2 or Laguna S 2.1\n\n- [Agents-A1-4B vs DeepSeek-V3.2](https://www.anchorterminal.com/compare/agents-a1-4b-vs-deepseek-v3-2.md)\n- [Agents-A1-4B vs Laguna S 2.1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-s-2-1.md)\n- [Apertus v1.5 8B vs DeepSeek-V3.2](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-deepseek-v3-2.md)\n- [Apertus v1.5 8B vs Laguna S 2.1](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-s-2-1.md)\n- [Apodex-1.1-mini vs DeepSeek-V3.2](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-deepseek-v3-2.md)\n- [Apodex-1.1-mini vs Laguna S 2.1](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-s-2-1.md)\n- [BigBang-v1 vs DeepSeek-V3.2](https://www.anchorterminal.com/compare/bigbang-v1-vs-deepseek-v3-2.md)\n- [BigBang-v1 vs Laguna S 2.1](https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-s-2-1.md)\n- [Cosmos-Reason2-2B vs DeepSeek-V3.2](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-deepseek-v3-2.md)\n- [Cosmos-Reason2-2B vs Laguna S 2.1](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-s-2-1.md)\n- [Darwin-36B-Opus vs DeepSeek-V3.2](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-deepseek-v3-2.md)\n- [Darwin-36B-Opus vs Laguna S 2.1](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-s-2-1.md)\n- [DeepSeek-V3.2 vs DeepSeek V4.1 Flash](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-deepseek-v4-1-flash.md)\n- [DeepSeek-V3.2 vs DeepSeek-V4-Flash-0731](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-deepseek-v4-flash-0731.md)\n- [DeepSeek-V3.2 vs DiffusionGemma 26B A4B IT](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-diffusiongemma-26b-a4b-it.md)\n- [DeepSeek-V3.2 vs Gemma 4 12B IT](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-12b-it.md)\n- [DeepSeek-V3.2 vs Gemma 4 26B A4B IT](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-26b-a4b-it.md)\n- [DeepSeek-V3.2 vs Gemma 4 31B IT](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-31b-it.md)\n- [DeepSeek-V3.2 vs Gemma 4 E2B IT](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-e2b-it.md)\n- [DeepSeek-V3.2 vs Gemma 4 E4B IT](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gemma-4-e4b-it.md)\n- [DeepSeek-V3.2 vs GLM-4.5-Air](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-4-5-air.md)\n- [DeepSeek-V3.2 vs GLM-4.7-Flash](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-4-7-flash.md)\n- [DeepSeek-V3.2 vs GLM-5.3](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3.md)\n- [DeepSeek-V3.2 vs GLM-5.3-Flash](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-glm-5-3-flash.md)\n- [DeepSeek-V3.2 vs gpt-oss-120b](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gpt-oss-120b.md)\n- [DeepSeek-V3.2 vs gpt-oss-20b](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-gpt-oss-20b.md)\n- [DeepSeek-V3.2 vs Granite 4.2 3B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-granite-4-2-3b.md)\n- [DeepSeek-V3.2 vs Hy3](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-hy3.md)\n- [DeepSeek-V3.2 vs Inkling](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling.md)\n- [DeepSeek-V3.2 vs Inkling-Small](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-inkling-small.md)\n- [DeepSeek-V3.2 vs InternVL3.5-GPT-OSS-20B-A4B-Preview](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-internvl3-5-gpt-oss-20b-a4b-preview.md)\n- [DeepSeek-V3.2 vs Kimi K3](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-kimi-k3.md)\n- [DeepSeek-V3.2 vs Kolibri-1](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-kolibri-1.md)\n- [DeepSeek-V3.2 vs Laguna M.1](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-m-1.md)\n- [DeepSeek-V3.2 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-xs-2-1.md)\n- [DeepSeek-V3.2 vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-lfm2-5-2-6b.md)\n- [DeepSeek-V3.2 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ling-3-0-tiny.md)\n- [DeepSeek-V3.2 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-mimo-v2-6-distill-qwen-9b.md)\n- [DeepSeek-V3.2 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm-o-4-5.md)\n- [DeepSeek-V3.2 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minicpm5-2b.md)\n- [DeepSeek-V3.2 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-5.md)\n- [DeepSeek-V3.2 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-minimax-m2-7.md)\n- [DeepSeek-V3.2 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-muse-glimmer-30b.md)\n- [DeepSeek-V3.2 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [DeepSeek-V3.2 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-30b-a3b.md)\n- [DeepSeek-V3.2 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-4b.md)\n- [DeepSeek-V3.2 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [DeepSeek-V3.2 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-super-120b-a12b.md)\n- [DeepSeek-V3.2 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-nemotron-3-ultra-550b-a55b.md)\n- [DeepSeek-V3.2 vs occamy-1.0](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-occamy-1-0.md)\n- [DeepSeek-V3.2 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-olmo-3-7b-think.md)\n- [DeepSeek-V3.2 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-35b-a3b.md)\n- [DeepSeek-V3.2 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-397b.md)\n- [DeepSeek-V3.2 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-ornith-1-5-9b.md)\n- [DeepSeek-V3.2 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-30b-a3b-instruct-2507.md)\n- [DeepSeek-V3.2 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-4b-instruct-2507.md)\n- [DeepSeek-V3.2 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-0-8b.md)\n- [DeepSeek-V3.2 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-122b-a10b.md)\n- [DeepSeek-V3.2 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-2b.md)\n- [DeepSeek-V3.2 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-397b-a17b.md)\n- [DeepSeek-V3.2 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-4b.md)\n- [DeepSeek-V3.2 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-5-9b.md)\n- [DeepSeek-V3.2 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-6-27b.md)\n- [DeepSeek-V3.2 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-6-35b-a3b.md)\n- [DeepSeek-V3.2 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-27b.md)\n- [DeepSeek-V3.2 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-8-flash-next.md)\n- [DeepSeek-V3.2 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-30b-a3b-instruct.md)\n- [DeepSeek-V3.2 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-coder-next.md)\n- [DeepSeek-V3.2 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-omni-30b-a3b-instruct.md)\n- [DeepSeek-V3.2 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-2b-instruct.md)\n- [DeepSeek-V3.2 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-30b-a3b-instruct.md)\n- [DeepSeek-V3.2 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-32b-instruct.md)\n- [DeepSeek-V3.2 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-4b-instruct.md)\n- [DeepSeek-V3.2 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwen3-vl-8b-instruct.md)\n- [DeepSeek-V3.2 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-qwopus3-8-27b-flash-v2.md)\n- [DeepSeek-V3.2 vs SmolLM3-3B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-smollm3-3b.md)\n- [DeepSeek-V3.2 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-spark-x2-6-4b.md)\n- [DeepSeek-V3.2 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-27b.md)\n- [DeepSeek-V3.2 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-swift-1-5-qwen3-8-flash-next.md)\n- [DeepSeek-V3.2 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-thinkingcap-qwen3-8-27b.md)\n- [DeepSeek V4.1 Flash vs Laguna S 2.1](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-s-2-1.md)\n- [DeepSeek-V4-Flash-0731 vs Laguna S 2.1](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-s-2-1.md)\n- [DiffusionGemma 26B A4B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-s-2-1.md)\n- [Gemma 4 12B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-s-2-1.md)\n- [Gemma 4 26B A4B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-s-2-1.md)\n- [Gemma 4 31B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-s-2-1.md)\n- [Gemma 4 E2B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-s-2-1.md)\n- [Gemma 4 E4B IT vs Laguna S 2.1](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-s-2-1.md)\n- [GLM-4.5-Air vs Laguna S 2.1](https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-s-2-1.md)\n- [GLM-4.7-Flash vs Laguna S 2.1](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-s-2-1.md)\n- [GLM-5.3-Flash vs Laguna S 2.1](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-s-2-1.md)\n- [GLM-5.3 vs Laguna S 2.1](https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-s-2-1.md)\n- [gpt-oss-120b vs Laguna S 2.1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-s-2-1.md)\n- [gpt-oss-20b vs Laguna S 2.1](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-s-2-1.md)\n- [Granite 4.2 3B vs Laguna S 2.1](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-s-2-1.md)\n- [Hy3 vs Laguna S 2.1](https://www.anchorterminal.com/compare/hy3-vs-laguna-s-2-1.md)\n- [Inkling-Small vs Laguna S 2.1](https://www.anchorterminal.com/compare/inkling-small-vs-laguna-s-2-1.md)\n- [Inkling vs Laguna S 2.1](https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs Laguna S 2.1](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-s-2-1.md)\n- [Kimi K3 vs Laguna S 2.1](https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-s-2-1.md)\n- [Kolibri-1 vs Laguna S 2.1](https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-s-2-1.md)\n- [Laguna M.1 vs Laguna S 2.1](https://www.anchorterminal.com/compare/laguna-m-1-vs-laguna-s-2-1.md)\n- [Laguna S 2.1 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-laguna-xs-2-1.md)\n- [Laguna S 2.1 vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm2-5-2-6b.md)\n- [Laguna S 2.1 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ling-3-0-tiny.md)\n- [Laguna S 2.1 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Laguna S 2.1 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm-o-4-5.md)\n- [Laguna S 2.1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minicpm5-2b.md)\n- [Laguna S 2.1 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minimax-m2-5.md)\n- [Laguna S 2.1 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-minimax-m2-7.md)\n- [Laguna S 2.1 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-muse-glimmer-30b.md)\n- [Laguna S 2.1 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [Laguna S 2.1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-30b-a3b.md)\n- [Laguna S 2.1 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-4b.md)\n- [Laguna S 2.1 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Laguna S 2.1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-super-120b-a12b.md)\n- [Laguna S 2.1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-nemotron-3-ultra-550b-a55b.md)\n- [Laguna S 2.1 vs occamy-1.0](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-occamy-1-0.md)\n- [Laguna S 2.1 vs Olmo 3 7B Think](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-olmo-3-7b-think.md)\n- [Laguna S 2.1 vs Ornith-1.5-35B-A3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-35b-a3b.md)\n- [Laguna S 2.1 vs Ornith-1.5-397B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-397b.md)\n- [Laguna S 2.1 vs Ornith-1.5-9B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-ornith-1-5-9b.md)\n- [Laguna S 2.1 vs Qwen3-30B-A3B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-30b-a3b-instruct-2507.md)\n- [Laguna S 2.1 vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-4b-instruct-2507.md)\n- [Laguna S 2.1 vs Qwen3.5-0.8B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-0-8b.md)\n- [Laguna S 2.1 vs Qwen3.5-122B-A10B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-122b-a10b.md)\n- [Laguna S 2.1 vs Qwen3.5-2B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-2b.md)\n- [Laguna S 2.1 vs Qwen3.5-397B-A17B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-397b-a17b.md)\n- [Laguna S 2.1 vs Qwen3.5-4B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-4b.md)\n- [Laguna S 2.1 vs Qwen3.5-9B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-5-9b.md)\n- [Laguna S 2.1 vs Qwen3.6-27B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-6-27b.md)\n- [Laguna S 2.1 vs Qwen3.6-35B-A3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-6-35b-a3b.md)\n- [Laguna S 2.1 vs Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-8-27b.md)\n- [Laguna S 2.1 vs Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-8-flash-next.md)\n- [Laguna S 2.1 vs Qwen3-Coder-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-coder-30b-a3b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-Coder-Next](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-coder-next.md)\n- [Laguna S 2.1 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-omni-30b-a3b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-VL-2B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-2b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-VL-30B-A3B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-30b-a3b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-VL-32B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-32b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-VL-4B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-4b-instruct.md)\n- [Laguna S 2.1 vs Qwen3-VL-8B-Instruct](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-vl-8b-instruct.md)\n- [Laguna S 2.1 vs Qwopus3.8-27B-Flash-V2](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwopus3-8-27b-flash-v2.md)\n- [Laguna S 2.1 vs SmolLM3-3B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-smollm3-3b.md)\n- [Laguna S 2.1 vs Spark-X2.6-4B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-spark-x2-6-4b.md)\n- [Laguna S 2.1 vs Swift 1.5 Qwen3.8-27B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-27b.md)\n- [Laguna S 2.1 vs Swift 1.5 Qwen3.8-Flash-Next](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-swift-1-5-qwen3-8-flash-next.md)\n- [Laguna S 2.1 vs ThinkingCap (Qwen3.8 27B)](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-thinkingcap-qwen3-8-27b.md)\n",
  "meta": {
    "attribution": "Anchor Terminal (https://www.anchorterminal.com)",
    "attributionRequired": true,
    "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)",
    "docs": "https://www.anchorterminal.com/docs/",
    "generatedAt": "2026-10-21",
    "license": "CC-BY-4.0",
    "method": "https://www.anchorterminal.com/benchmark/",
    "methodology": "0.6",
    "openapi": "https://www.anchorterminal.com/openapi.json",
    "preview": false,
    "run": "2026-10-01",
    "runLabel": "October 2026 research run",
    "terms": "https://www.anchorterminal.com/terms/#data"
  },
  "page": {
    "breadcrumbs": [
      {
        "name": "Home",
        "url": "https://www.anchorterminal.com/"
      },
      {
        "name": "Compare",
        "url": "https://www.anchorterminal.com/compare/"
      },
      {
        "name": "DeepSeek-V3.2 vs Laguna S 2.1",
        "url": ""
      }
    ],
    "description": "Laguna S 2.1 scores 61 (C) to DeepSeek-V3.2's 58.6 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.",
    "facts": [
      "DeepSeek-V3.2 C 58.6",
      "Laguna S 2.1 C 61",
      "scores"
    ],
    "h1": "DeepSeek-V3.2 vs Laguna S 2.1",
    "image": "https://www.anchorterminal.com/assets/og/compare-deepseek-v3-2-vs-laguna-s-2-1.png",
    "path": "/compare/deepseek-v3-2-vs-laguna-s-2-1",
    "published": "2026-10-01",
    "section": "tools",
    "title": "DeepSeek-V3.2 vs Laguna S 2.1 for AI agents in 2026: scores and prices",
    "toc": null,
    "updated": "2026-10-21",
    "url": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-s-2-1"
  },
  "tokens": {
    "markdown": 6050,
    "slim": 430
  },
  "version": 1
}