{
  "data": {
    "a": {
      "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",
      "dns": "laguna-s-2-1.grade.anchorterminal.com",
      "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 and Featherless AI host it; Poolside's OpenRouter endpoints expired on 31 October 2026 (checked 2026-11-03).",
      "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": 1518,
        "categoryRank": 35,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 85,
          "reach": 75,
          "risk": 55,
          "upkeep": 41
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-03"
        },
        "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": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 85,
          "reach": 75,
          "risk": 55,
          "upkeep": 41
        },
        "provenanceScore": 69,
        "checked": {
          "categories": {
            "interface": "2026-11-03",
            "reach": "2026-11-03",
            "risk": "2026-11-03",
            "upkeep": "2026-11-03"
          },
          "last": "2026-11-03",
          "oldest": "2026-11-03",
          "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}'\n# or, with llama.cpp and Unsloth's GGUF, a third party's conversion:\nllama-server -hf unsloth/Laguna-S-2.1-GGUF:UD-Q4_K_M --jinja",
        "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": "unsloth Laguna-S-2.1-GGUF (UD-Q4_K_M)",
            "url": "https://huggingface.co/unsloth/Laguna-S-2.1-GGUF",
            "who": "unsloth",
            "precision": "q4_k_m",
            "sizeGB": 73.12,
            "memoryGB": 96,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "From Unsloth, a third party's conversion and not Poolside's. 73.12 GB of UD-Q4_K_M weights, from the Hub's model information on 10 November 2026. Recorded after the last grading, so Reach doesn't count it"
          },
          {
            "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": 69
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/laguna-s-2-1.json",
      "live": {
        "slug": "laguna-s-2-1",
        "securityTxt": {
          "url": "https://poolside.ai/.well-known/security.txt",
          "state": "valid",
          "expires": "2028-04-01T12:00:00.000Z",
          "checkedAt": "2026-11-10T16:09:25.614312659Z"
        },
        "domain": {
          "domain": "poolside.ai",
          "registered": "2020-07-07",
          "source": "https://rdap.identitydigital.services/rdap/domain/poolside.ai",
          "checkedAt": "2026-11-08T14:58:52.089559761Z"
        },
        "updatedAt": "2026-11-10T16:09:25.614312659Z"
      }
    },
    "answer": "Laguna S 2.1 and LFM3-Audio-2B score within a point of each other on agent readiness, 61 (C) and 61 (C). LFM3-Audio-2B leads on reach and documentation and upkeep.",
    "b": {
      "slug": "lfm3-audio-2b",
      "name": "LFM3-Audio-2B",
      "vendor": "Liquid AI",
      "vendorUrl": "https://www.liquid.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "LFM3-Audio-2B is Liquid AI's open-weight 2B audio model for on-device use, taking text or speech and answering in text, speech or both, with transcription, translation, tool calling and a 32K-token context, released on 27 October 2026.",
      "url": "https://www.anchorterminal.com/tools/lfm3-audio-2b",
      "markdownUrl": "https://www.anchorterminal.com/tools/lfm3-audio-2b.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/lfm3-audio-2b.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/lfm3-audio-2b.json",
      "dns": "lfm3-audio-2b.grade.anchorterminal.com",
      "repo": "https://huggingface.co/LiquidAI/LFM3-Audio-2B",
      "license": "LFM Open License v1.0 (free commercial use below $10M annual revenue)",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "LiquidAI/LFM3-Audio-2B"
        },
        {
          "registry": "huggingface",
          "name": "LiquidAI/LFM3-Audio-2B-GGUF"
        },
        {
          "registry": "huggingface",
          "name": "LiquidAI/LFM3-Audio-2B-MLX-4bit"
        },
        {
          "registry": "ollama",
          "name": "lfm3-audio"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. The repository and Liquid's GGUF, MLX and ONNX repositories are not gated (checked 2026-11-10).",
      "pricing": "free",
      "pricingNotes": "Free to download and use under the LFM Open License v1.0, commercial use included for organisations with under $10M in annual revenue; above that, commercial use isn't licensed. Running it yourself costs little hardware, 1.10 GB for Liquid's Q4_K_M GGUF with its 0.17 GB projector file and 4.16 GB in BF16. Liquid's API also serves it, at prices shown in its console (checked 2026-11-10).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-11-10).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-11-10"
      },
      "docsUrl": "https://docs.liquid.ai/lfm/models/lfm3-audio-2b",
      "llmsTxt": "https://docs.liquid.ai/llms.txt",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "audio",
        "speech",
        "speech-to-speech",
        "transcription",
        "small",
        "edge",
        "tool-calling",
        "custom-licence",
        "safetensors",
        "gguf",
        "mlx",
        "onnx",
        "self-hosted"
      ],
      "lastRelease": "2026-11-03",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 61,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1518,
        "categoryRank": 56,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 85,
          "reach": 80,
          "risk": 40,
          "upkeep": 52
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-10"
        },
        "negative": 0,
        "verdict": "A 2B model that listens and speaks on an 8 GB machine, transcribes and translates 19 languages and turns spoken requests into tool calls. Only llama.cpp and Ollama run it in a release. The context is 32K, voice chat is English only, Liquid hasn't answered the repository's questions, and there are no safety results or data sources.",
        "bestFor": "Voice agents on a laptop or phone that need speech in, speech out and tool calls from one small model",
        "strengths": [
          "Speech in and speech out on an 8 GB machine, streamed",
          "Transcribes, speaks and translates 19 languages and locales",
          "Tool calls from spoken requests, in a documented format",
          "Reasoning can be turned on per text reply",
          "Liquid's own API serves it"
        ],
        "weaknesses": [
          "Only llama.cpp and Ollama run it in a release, though the card lists vLLM and SGLang",
          "A 32K-token context",
          "Voice chat is English only",
          "Neither question on the repository has a reply from Liquid",
          "Loading in Transformers runs code from the repository",
          "No safety results, security contact or training data description"
        ],
        "agentNotes": [
          "Start it with `llama-server -hf LiquidAI/LFM3-Audio-2B-GGUF:Q4_K_M --jinja` or `ollama run lfm3-audio`",
          "llama.cpp ships examples/realtime_client.py for live speech with this model",
          "Prefill the assistant turn with an open think tag to let it reason before a text reply",
          "The context is 32K",
          "Voice chat is English only, while transcription, synthesis and translation cover 19 languages and locales",
          "Liquid doesn't recommend it for agentic coding or complex multi-step reasoning"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "low",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 61
          }
        ],
        "editorialScores": {
          "interface": 85,
          "reach": 80,
          "risk": 40,
          "upkeep": 52
        },
        "provenanceScore": 73,
        "checked": {
          "categories": {
            "interface": "2026-11-10",
            "reach": "2026-11-10",
            "risk": "2026-11-10",
            "upkeep": "2026-11-10"
          },
          "last": "2026-11-10",
          "oldest": "2026-11-10",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "llama-server -hf LiquidAI/LFM3-Audio-2B-GGUF:Q4_K_M --jinja\n# or\nollama run lfm3-audio",
        "http": "curl http://localhost:8080/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/lfm3-audio-2b"
      },
      "sameCompany": [
        "liquid-d1",
        "lfm2-5-2-6b",
        "lfm3-1-7b",
        "lfm3-omni-2b",
        "lfm3-vl-2b"
      ],
      "weights": {
        "trainedBy": "Liquid AI",
        "builtOn": "The LFM3 backbone (Liquid's own; the metadata names no base model)",
        "params": "2.00B",
        "context": 32000,
        "goodFor": "Small on-device audio model for voice chat, transcription, speech synthesis and translation in 19 languages and locales, questions about recordings and tool calls from spoken requests. Voice chat is English only.",
        "runtimes": [
          "llama.cpp",
          "Ollama"
        ],
        "builds": [
          {
            "name": "LFM3-Audio-2B",
            "url": "https://huggingface.co/LiquidAI/LFM3-Audio-2B",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 4.16,
            "memoryGB": 8,
            "format": "safetensors",
            "runsOn": [
              "Transformers"
            ],
            "note": "Loads in Transformers with the repository's own code. Liquid also publishes an ONNX repository. It has no FP8 or NVFP4 build of this model"
          },
          {
            "name": "LFM3-Audio-2B-GGUF Q8_0",
            "url": "https://huggingface.co/LiquidAI/LFM3-Audio-2B-GGUF",
            "who": "publisher",
            "precision": "q8_0",
            "sizeGB": 2.15,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "LFM3-Audio-2B-Q8_0.gguf (1.85 GB) plus mmproj-LFM3-Audio-2B-Q8_0.gguf (0.30 GB)"
          },
          {
            "name": "LFM3-Audio-2B-GGUF Q4_K_M",
            "url": "https://huggingface.co/LiquidAI/LFM3-Audio-2B-GGUF",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 1.27,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "llama.cpp"
            ],
            "note": "LFM3-Audio-2B-Q4_K_M.gguf (1.10 GB) plus Liquid's projector file mmproj-LFM3-Audio-2B-Q4_K_M.gguf (0.17 GB), from the Hub's file list. The repository also holds Q4_0, Q8_0, F16 and BF16 files"
          },
          {
            "name": "LFM3-Audio-2B-MLX-4bit",
            "url": "https://huggingface.co/LiquidAI/LFM3-Audio-2B-MLX-4bit",
            "who": "publisher",
            "precision": "4bit",
            "sizeGB": 1.73,
            "memoryGB": 8,
            "format": "mlx",
            "runsOn": [
              "MLX-VLM"
            ],
            "note": "Liquid also publishes 8-bit and BF16 MLX builds"
          },
          {
            "name": "ollama lfm3-audio",
            "url": "https://ollama.com/library/lfm3-audio",
            "who": "ollama",
            "precision": "q4_k_m",
            "sizeGB": 1.7,
            "memoryGB": 8,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "Ollama's library build, size as its tags page shows it on 10 November 2026. The library also has q8_0, bf16, mxfp8 and nvfp4 tags"
          }
        ],
        "run": "llama-server -hf LiquidAI/LFM3-Audio-2B-GGUF:Q4_K_M --jinja",
        "runBuild": "LFM3-Audio-2B-GGUF Q4_K_M",
        "checked": "2026-11-10",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "Liquid AI",
        "family": "LFM3",
        "url": "https://www.anchorterminal.com/open-weights/#liquid",
        "others": [
          {
            "name": "LFM3-1.7B-Base",
            "url": "https://huggingface.co/LiquidAI/LFM3-1.7B-Base",
            "params": "1.73B"
          },
          {
            "name": "LFM3-1.7B",
            "url": "https://huggingface.co/LiquidAI/LFM3-1.7B",
            "params": "1.73B",
            "listing": "https://www.anchorterminal.com/tools/lfm3-1-7b"
          },
          {
            "name": "LFM3-VL-2B",
            "url": "https://huggingface.co/LiquidAI/LFM3-VL-2B",
            "params": "1.92B",
            "listing": "https://www.anchorterminal.com/tools/lfm3-vl-2b"
          },
          {
            "name": "LFM3-Omni-2B",
            "url": "https://huggingface.co/LiquidAI/LFM3-Omni-2B",
            "params": "2.17B",
            "listing": "https://www.anchorterminal.com/tools/lfm3-omni-2b"
          }
        ]
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Liquid AI, Inc. (the licensor named in the LFM Open License)",
        "domain": "liquid.ai",
        "domainRegistered": "2017-12-16",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/LiquidAI/LFM3-Audio-2B/commits/main",
        "securityTxt": "none",
        "checked": "2026-11-10",
        "notes": [
          "The licence names Liquid AI, Inc. as licensor. The domain's registration date is as recorded on the liquid-d1 listing on 8 October 2026",
          "www.liquid.ai/.well-known/security.txt answered 404 on 10 November 2026"
        ],
        "score": 73
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/lfm3-audio-2b.json"
    },
    "edges": [
      {
        "by": 15,
        "category": "risk",
        "leads": "laguna-s-2-1",
        "name": "Risk",
        "reasons": {
          "a": "File safety 15 of 25, safetensors and GGUF only, but the repository ships model code behind auto_map and the card's SGLang and TensorRT-LLM commands use trust_remote_code. Provenance 15, the verified poolside organisation, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 5, general cautions only. Licence risk 15, OpenMDW-1.1 has no use policy, threshold or revocation clause. Security programme 5, a signed security.txt and a security contact on the card, with no public advisories found.",
          "b": "File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, files in the LiquidAI organisation, which Liquid's docs page for the model and its blog post link to (10). Safety evaluation 0, no safety results on the card or in Liquid's blog post for the LFM3 family, neither of which mentions safety testing. Agent guidance 0, Nothing on prompt injection, an instruction hierarchy, what refusals cover or safeguards to add. Licence risk 10, 15 less 5 for the $10M annual revenue threshold on commercial use. Security programme 0, no way to report a flaw found. 15 + 15 + 0 + 0 + 10 + 0 = 40."
        },
        "scores": {
          "a": 55,
          "b": 40
        }
      },
      {
        "by": 11,
        "category": "upkeep",
        "leads": "lfm3-audio-2b",
        "name": "Documentation and upkeep",
        "reasons": {
          "a": "Model card 11 of 20, intended use, architecture, parameters and context are on the card, limitations, languages and a cut-off aren't. Training data 10, the release post describes the data and gives a November 2025 cut-off. Last change 15, 25 August 2026, 70 days back. Responsiveness 0, Poolside answered none of the 34 discussions. Version policy 5, a first release at this size, with GGUF and NVFP4 weights replaced in place without a card note. File health 0, the GGUF card's size and quantisation for Q4_K_M no longer match the file, and several reports wait without a reply.",
          "b": "Model card 17, Intended use (local agents, tool calling, structured outputs, fine-tuning), limitations (not recommended for agentic coding or complex multi-step reasoning, voice chat in English only), an architecture section, parameters (2B), context (32K) and 19 speech languages and locales. Training data 5, the card has no training section. Last change 20, the last commit, on 3 November 2026, changed the card's navigation icons, seven days before this check, and the one before it, on 31 October, edited the card. Responsiveness 0, Neither of the 2 discussions that aren't pull requests (27 and 31 October 2026) has a reply from a LiquidAI member. Version policy 5, LFM3 came out in new repositories and the LFM2.5 models stay in theirs. File health 5, the card gives a 32K context while config.json gives the language model 128,000 positions and Liquid's API lists 128,000 for the hosted model, so the card and the files don't agree on context. 17 + 5 + 20 + 0 + 5 + 5 = 52."
        },
        "scores": {
          "a": 41,
          "b": 52
        }
      },
      {
        "by": 5,
        "category": "reach",
        "leads": "lfm3-audio-2b",
        "name": "Reach",
        "reasons": {
          "a": "Memory 10 of 30, the smallest 4-bit build is Ollama's 66 GB MLX nvfp4, which needs 96 GB with a fifth added and fits our 128 GB reference machine. Runtimes 25, released llama.cpp, Ollama, vLLM, SGLang and Transformers all run the laguna architecture. Builds 15, Poolside publishes FP8, INT4, NVFP4, MLX and GGUF builds. Terms 10, OpenMDW-1.1 is permissive but not OSI-approved. Download 10, nothing is gated. Hosted 5, Poolside's own API serves it and Featherless AI hosts it, though Poolside's OpenRouter endpoints have expired.",
          "b": "Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB with its 0.17 GB projector file, and 1.27 GB × 1.2 = 1.5 GB, which fits 8 GB, well inside the 16 GB line. Runtimes 10, Released llama.cpp has the lfm3 architecture with the LFM3 audio projector and speech output (src/models/lfm3.cpp and tools/mtmd at b12242, with a realtime client example that starts this model), and Ollama's library has an lfm3-audio entry. Builds 15, Liquid's GGUF repository holds Q4_0, Q4_K_M, Q8_0, F16 and BF16 files, and Liquid publishes 4-bit and 8-bit MLX builds and an ONNX repository, all in the LiquidAI organisation. Terms 10, the LFM Open License v1.0, a custom licence that lets anyone use it commercially for free below a threshold of $10M annual revenue. Download 10, the Hub API reports gated false for the model and its GGUF, MLX and ONNX repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, Liquid's own API lists lfm3-audio-2b among its models, so the publisher hosts it. 30 + 10 + 15 + 10 + 10 + 5 = 80."
        },
        "scores": {
          "a": 75,
          "b": 80
        }
      }
    ],
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Poolside",
        "b": "Liquid AI",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "OpenMDW-1.1",
        "b": "LFM Open License v1.0 (free commercial use below $10M annual revenue)",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-08-19",
        "b": "2026-11-03",
        "name": "Last release"
      },
      {
        "a": "2026-07-21",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "2026-07-21",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "yes, with an opt-out",
        "b": "not read yet",
        "name": "Customer content may train models"
      },
      {
        "a": "not found in the text",
        "b": "not read yet",
        "name": "Terms restrict automated access"
      },
      {
        "a": "not found in the text",
        "b": "not read yet",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "yes",
        "b": "not read yet",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "yes",
        "b": "not read yet",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "2.3/5 (4)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Laguna S 2.1 and LFM3-Audio-2B score within a point of each other on agent readiness, 61 (C) and 61 (C). LFM3-Audio-2B leads on reach and documentation and upkeep.",
        "question": "Which is better for AI agents, Laguna S 2.1 or LFM3-Audio-2B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 55 against 40"
        ],
        "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"
      },
      {
        "aheadOn": [
          "Reach, 80 against 75",
          "Documentation and upkeep, 52 against 41"
        ],
        "also": null,
        "goodFor": "Voice agents on a laptop or phone that need speech in, speech out and tool calls from one small model",
        "slug": "lfm3-audio-2b",
        "watchFor": "Only llama.cpp and Ollama run it in a release, though the card lists vLLM and SGLang"
      }
    ],
    "history": null,
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
    "others": [
      {
        "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/agents-a1-4b-vs-lfm3-audio-2b.json",
        "title": "Agents-A1-4B vs LFM3-Audio-2B",
        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-lfm3-audio-2b"
      },
      {
        "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/apertus-v1-5-8b-vs-lfm3-audio-2b.json",
        "title": "Apertus v1.5 8B vs LFM3-Audio-2B",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lfm3-audio-2b"
      },
      {
        "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/apodex-1-1-mini-vs-lfm3-audio-2b.json",
        "title": "Apodex-1.1-mini vs LFM3-Audio-2B",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lfm3-audio-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-s-2-1.json",
        "title": "Arete-27B vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-s-2-1"
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        "json": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-audio-2b.json",
        "title": "Arete-27B vs LFM3-Audio-2B",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-audio-2b"
      },
      {
        "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/bigbang-v1-vs-lfm3-audio-2b.json",
        "title": "BigBang-v1 vs LFM3-Audio-2B",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-audio-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-s-2-1.json",
        "title": "Carbon-X vs Laguna S 2.1",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-s-2-1"
      },
      {
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        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-lfm3-audio-2b"
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      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-laguna-s-2-1.json",
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        "url": "https://www.anchorterminal.com/compare/cola2-vs-laguna-s-2-1"
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      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-lfm3-audio-2b.json",
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        "url": "https://www.anchorterminal.com/compare/cola2-vs-lfm3-audio-2b"
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        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lfm3-audio-2b"
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        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-s-2-1"
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        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-nemotron-3-nano-omni-30b-a3b-reasoning.json",
        "title": "LFM3-Audio-2B vs Nemotron 3 Nano Omni 30B A3B Reasoning",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-nemotron-3-nano-omni-30b-a3b-reasoning"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-nemotron-3-super-120b-a12b.json",
        "title": "LFM3-Audio-2B vs Nemotron 3 Super 120B A12B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-nemotron-3-super-120b-a12b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-nemotron-3-ultra-550b-a55b.json",
        "title": "LFM3-Audio-2B vs Nemotron 3 Ultra 550B A55B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-nemotron-3-ultra-550b-a55b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-north-mini-code-1-0.json",
        "title": "LFM3-Audio-2B vs North Mini Code 1.0",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-north-mini-code-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-occamy-1-0.json",
        "title": "LFM3-Audio-2B vs occamy-1.0",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-occamy-1-0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-olmo-3-7b-think.json",
        "title": "LFM3-Audio-2B vs Olmo 3 7B Think",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-olmo-3-7b-think"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-122b.json",
        "title": "LFM3-Audio-2B vs Ornith-1.5-122B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-122b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-35b-a3b.json",
        "title": "LFM3-Audio-2B vs Ornith-1.5-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-397b.json",
        "title": "LFM3-Audio-2B vs Ornith-1.5-397B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-397b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-9b.json",
        "title": "LFM3-Audio-2B vs Ornith-1.5-9B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-otel-2-0-llm-31b-it.json",
        "title": "LFM3-Audio-2B vs OTel-2.0-LLM-31B-IT",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-otel-2-0-llm-31b-it"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen-agentworld-35b-a3b.json",
        "title": "LFM3-Audio-2B vs Qwen-AgentWorld-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen-agentworld-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-30b-a3b-instruct-2507.json",
        "title": "LFM3-Audio-2B vs Qwen3-30B-A3B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-30b-a3b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-4b-instruct-2507.json",
        "title": "LFM3-Audio-2B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-4b-instruct-2507"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-0-8b.json",
        "title": "LFM3-Audio-2B vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-0-8b"
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      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-122b-a10b.json",
        "title": "LFM3-Audio-2B vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-122b-a10b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-2b.json",
        "title": "LFM3-Audio-2B vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-397b-a17b.json",
        "title": "LFM3-Audio-2B vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-397b-a17b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-4b.json",
        "title": "LFM3-Audio-2B vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-9b.json",
        "title": "LFM3-Audio-2B vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-9b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-6-27b.json",
        "title": "LFM3-Audio-2B vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-6-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-6-35b-a3b.json",
        "title": "LFM3-Audio-2B vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-6-35b-a3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-8-27b.json",
        "title": "LFM3-Audio-2B vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-8-flash-next.json",
        "title": "LFM3-Audio-2B vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "LFM3-Audio-2B vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-coder-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-coder-next.json",
        "title": "LFM3-Audio-2B vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-coder-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "LFM3-Audio-2B vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-omni-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-vl-2b-instruct.json",
        "title": "LFM3-Audio-2B vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-vl-2b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "LFM3-Audio-2B vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-vl-30b-a3b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-vl-32b-instruct.json",
        "title": "LFM3-Audio-2B vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-vl-32b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-vl-4b-instruct.json",
        "title": "LFM3-Audio-2B vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-vl-4b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-vl-8b-instruct.json",
        "title": "LFM3-Audio-2B vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwopus3-8-27b-flash-v2.json",
        "title": "LFM3-Audio-2B vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-recursive-flint.json",
        "title": "LFM3-Audio-2B vs Recursive Flint",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-recursive-flint"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ripple-65b-preview.json",
        "title": "LFM3-Audio-2B vs Ripple-65B Preview",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ripple-65b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-sensenova-loop-9b-preview.json",
        "title": "LFM3-Audio-2B vs SenseNova-Loop-9B-Preview",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-sensenova-loop-9b-preview"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-smollm3-3b.json",
        "title": "LFM3-Audio-2B vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-spark-x2-6-4b.json",
        "title": "LFM3-Audio-2B vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-step-3-7-flash.json",
        "title": "LFM3-Audio-2B vs Step 3.7 Flash",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-step-3-7-flash"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-swift-1-5-qwen3-8-27b.json",
        "title": "LFM3-Audio-2B vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "LFM3-Audio-2B vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-thinkingcap-qwen3-8-27b.json",
        "title": "LFM3-Audio-2B vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-thinkingcap-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-unlimited-ocr-2.json",
        "title": "LFM3-Audio-2B vs Baidu Unlimited-OCR-2",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-unlimited-ocr-2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-wevisone-vl-2b.json",
        "title": "LFM3-Audio-2B vs WeVisOne-VL-2B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-wevisone-vl-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-wevisone-vl-4b.json",
        "title": "LFM3-Audio-2B vs WeVisOne-VL-4B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-wevisone-vl-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-zaya1-8b.json",
        "title": "LFM3-Audio-2B vs ZAYA1-8B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-zaya1-8b"
      }
    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 5,
        "edge": "lfm3-audio-2b",
        "key": "reach",
        "laguna-s-2-1": 75,
        "lfm3-audio-2b": 80,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 15,
        "edge": "laguna-s-2-1",
        "key": "risk",
        "laguna-s-2-1": 55,
        "lfm3-audio-2b": 40,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 0,
        "edge": "",
        "key": "interface",
        "laguna-s-2-1": 85,
        "lfm3-audio-2b": 85,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 11,
        "edge": "lfm3-audio-2b",
        "key": "upkeep",
        "laguna-s-2-1": 41,
        "lfm3-audio-2b": 52,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Laguna S 2.1 and LFM3-Audio-2B score within a point of each other on agent readiness, 61 (C) and 61 (C). LFM3-Audio-2B leads on reach and documentation and upkeep. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "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.",
      "lfm3-audio-2b": "A 2B model that listens and speaks on an 8 GB machine, transcribes and translates 19 languages and turns spoken requests into tool calls. Only llama.cpp and Ollama run it in a release. The context is 32K, voice chat is English only, Liquid hasn't answered the repository's questions, and there are no safety results or data sources."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm3-audio-2b",
    "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm3-audio-2b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm3-audio-2b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm3-audio-2b.min.md"
  },
  "markdown": "Laguna S 2.1 and LFM3-Audio-2B score within a point of each other on agent readiness, 61 (C) and 61 (C). LFM3-Audio-2B leads on reach and documentation and upkeep. Both do open-weight models you run yourself.\n\n- Laguna S 2.1: grade C, 61/100, rank #45 of 160 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- LFM3-Audio-2B: grade C, 61/100, rank #70 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/lfm3-audio-2b.md · JSON https://www.anchorterminal.com/api/v1/tools/lfm3-audio-2b.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 6359 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### 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- Risk, 55 against 40\n\nWatch for: No reply from Poolside to any of 34 discussions, many of them reports about thinking and tool calls\n\n### LFM3-Audio-2B (C)\n\nGood for: Voice agents on a laptop or phone that need speech in, speech out and tool calls from one small model\n\nAhead on:\n- Reach, 80 against 75\n- Documentation and upkeep, 52 against 41\n\nWatch for: Only llama.cpp and Ollama run it in a release, though the card lists vLLM and SGLang\n\n\n## Why the edge\n\n### Risk: Laguna S 2.1 +15\n\n- Laguna S 2.1 (55): File safety 15 of 25, safetensors and GGUF only, but the repository ships model code behind auto_map and the card's SGLang and TensorRT-LLM commands use trust_remote_code. Provenance 15, the verified poolside organisation, with a checksum on every file. Safety evaluation 0, none published. Agent guidance 5, general cautions only. Licence risk 15, OpenMDW-1.1 has no use policy, threshold or revocation clause. Security programme 5, a signed security.txt and a security contact on the card, with no public advisories found.\n- LFM3-Audio-2B (40): File safety 15, safetensors only, no .bin, .pt or .pth files (25). Provenance 15, files in the LiquidAI organisation, which Liquid's docs page for the model and its blog post link to (10). Safety evaluation 0, no safety results on the card or in Liquid's blog post for the LFM3 family, neither of which mentions safety testing. Agent guidance 0, Nothing on prompt injection, an instruction hierarchy, what refusals cover or safeguards to add. Licence risk 10, 15 less 5 for the $10M annual revenue threshold on commercial use. Security programme 0, no way to report a flaw found. 15 + 15 + 0 + 0 + 10 + 0 = 40.\n\n### Documentation and upkeep: LFM3-Audio-2B +11\n\n- Laguna S 2.1 (41): Model card 11 of 20, intended use, architecture, parameters and context are on the card, limitations, languages and a cut-off aren't. Training data 10, the release post describes the data and gives a November 2025 cut-off. Last change 15, 25 August 2026, 70 days back. Responsiveness 0, Poolside answered none of the 34 discussions. Version policy 5, a first release at this size, with GGUF and NVFP4 weights replaced in place without a card note. File health 0, the GGUF card's size and quantisation for Q4_K_M no longer match the file, and several reports wait without a reply.\n- LFM3-Audio-2B (52): Model card 17, Intended use (local agents, tool calling, structured outputs, fine-tuning), limitations (not recommended for agentic coding or complex multi-step reasoning, voice chat in English only), an architecture section, parameters (2B), context (32K) and 19 speech languages and locales. Training data 5, the card has no training section. Last change 20, the last commit, on 3 November 2026, changed the card's navigation icons, seven days before this check, and the one before it, on 31 October, edited the card. Responsiveness 0, Neither of the 2 discussions that aren't pull requests (27 and 31 October 2026) has a reply from a LiquidAI member. Version policy 5, LFM3 came out in new repositories and the LFM2.5 models stay in theirs. File health 5, the card gives a 32K context while config.json gives the language model 128,000 positions and Liquid's API lists 128,000 for the hosted model, so the card and the files don't agree on context. 17 + 5 + 20 + 0 + 5 + 5 = 52.\n\n### Reach: LFM3-Audio-2B +5\n\n- Laguna S 2.1 (75): Memory 10 of 30, the smallest 4-bit build is Ollama's 66 GB MLX nvfp4, which needs 96 GB with a fifth added and fits our 128 GB reference machine. Runtimes 25, released llama.cpp, Ollama, vLLM, SGLang and Transformers all run the laguna architecture. Builds 15, Poolside publishes FP8, INT4, NVFP4, MLX and GGUF builds. Terms 10, OpenMDW-1.1 is permissive but not OSI-approved. Download 10, nothing is gated. Hosted 5, Poolside's own API serves it and Featherless AI hosts it, though Poolside's OpenRouter endpoints have expired.\n- LFM3-Audio-2B (80): Memory 30, Liquid's Q4_K_M GGUF is 1.10 GB with its 0.17 GB projector file, and 1.27 GB × 1.2 = 1.5 GB, which fits 8 GB, well inside the 16 GB line. Runtimes 10, Released llama.cpp has the lfm3 architecture with the LFM3 audio projector and speech output (src/models/lfm3.cpp and tools/mtmd at b12242, with a realtime client example that starts this model), and Ollama's library has an lfm3-audio entry. Builds 15, Liquid's GGUF repository holds Q4_0, Q4_K_M, Q8_0, F16 and BF16 files, and Liquid publishes 4-bit and 8-bit MLX builds and an ONNX repository, all in the LiquidAI organisation. Terms 10, the LFM Open License v1.0, a custom licence that lets anyone use it commercially for free below a threshold of $10M annual revenue. Download 10, the Hub API reports gated false for the model and its GGUF, MLX and ONNX repositories on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, Liquid's own API lists lfm3-audio-2b among its models, so the publisher hosts it. 30 + 10 + 15 + 10 + 10 + 5 = 80.\n\n## Score by category\n\n| Category | Weight | Laguna S 2.1 | LFM3-Audio-2B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 75 | 80 | LFM3-Audio-2B +5 |\n| Risk | 20% (20 this run) | 55 | 40 | Laguna S 2.1 +15 |\n| Agent interface | 10% (10 this run) | 85 | 85 | even |\n| Documentation and upkeep | 10% (10 this run) | 41 | 52 | LFM3-Audio-2B +11 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Laguna S 2.1 | LFM3-Audio-2B |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Poolside | Liquid AI |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports |  |  |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | OpenMDW-1.1 | LFM Open License v1.0 (free commercial use below $10M annual revenue) |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-08-19 | 2026-11-03 |\n| Terms last updated | 2026-07-21 | no document linked |\n| Privacy policy last updated | 2026-07-21 | no document linked |\n| Customer content may train models | yes, with an opt-out | not read yet |\n| Terms restrict automated access | not found in the text | not read yet |\n| Terms restrict benchmarking | not found in the text | not read yet |\n| Terms or service can change without notice | yes | not read yet |\n| Arbitration or class-action waiver | yes | not read yet |\n| Agent reviews | 2.3/5 (4) | none |\n\n## Verdicts\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**LFM3-Audio-2B.** A 2B model that listens and speaks on an 8 GB machine, transcribes and translates 19 languages and turns spoken requests into tool calls. Only llama.cpp and Ollama run it in a release. The context is 32K, voice chat is English only, Liquid hasn't answered the repository's questions, and there are no safety results or data sources.\n\n## Before you call either\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### LFM3-Audio-2B\n\n1. Start it with `llama-server -hf LiquidAI/LFM3-Audio-2B-GGUF:Q4_K_M --jinja` or `ollama run lfm3-audio`\n2. llama.cpp ships examples/realtime_client.py for live speech with this model\n3. Prefill the assistant turn with an open think tag to let it reason before a text reply\n4. The context is 32K\n5. Voice chat is English only, while transcription, synthesis and translation cover 19 languages and locales\n6. Liquid doesn't recommend it for agentic coding or complex multi-step reasoning\n\n## Questions\n\n### Which is better for AI agents, Laguna S 2.1 or LFM3-Audio-2B?\n\nLaguna S 2.1 and LFM3-Audio-2B score within a point of each other on agent readiness, 61 (C) and 61 (C). LFM3-Audio-2B leads on reach and documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm3-audio-2b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm3-audio-2b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"laguna-s-2-1\", \"b\": \"lfm3-audio-2b\"}`. From a terminal: `anchor compare laguna-s-2-1 lfm3-audio-2b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/laguna-s-2-1.json and https://www.anchorterminal.com/api/v1/tools/lfm3-audio-2b.json\n\n## Other comparisons with Laguna S 2.1 or LFM3-Audio-2B\n\n- [Agents-A1-4B vs Laguna S 2.1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-s-2-1.md)\n- [Agents-A1-4B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/agents-a1-4b-vs-lfm3-audio-2b.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- [Apertus v1.5 8B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-lfm3-audio-2b.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- [Apodex-1.1-mini vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-lfm3-audio-2b.md)\n- [Arete-27B vs Laguna S 2.1](https://www.anchorterminal.com/compare/arete-27b-vs-laguna-s-2-1.md)\n- [Arete-27B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/arete-27b-vs-lfm3-audio-2b.md)\n- [BigBang-v1 vs Laguna S 2.1](https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-s-2-1.md)\n- [BigBang-v1 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/bigbang-v1-vs-lfm3-audio-2b.md)\n- [Carbon-X vs Laguna S 2.1](https://www.anchorterminal.com/compare/carbon-x-vs-laguna-s-2-1.md)\n- [Carbon-X vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/carbon-x-vs-lfm3-audio-2b.md)\n- [Cola2 vs Laguna S 2.1](https://www.anchorterminal.com/compare/cola2-vs-laguna-s-2-1.md)\n- [Cola2 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/cola2-vs-lfm3-audio-2b.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- [Cosmos-Reason2-2B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lfm3-audio-2b.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- [Darwin-36B-Opus vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-audio-2b.md)\n- [DeepSeek-V3.2 vs Laguna S 2.1](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-s-2-1.md)\n- [DeepSeek-V3.2 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-lfm3-audio-2b.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 V4.1 Flash vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-lfm3-audio-2b.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- [DeepSeek-V4-Flash-0731 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-lfm3-audio-2b.md)\n- [Devstral Small 2 vs Laguna S 2.1](https://www.anchorterminal.com/compare/devstral-small-2-vs-laguna-s-2-1.md)\n- [Devstral Small 2 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/devstral-small-2-vs-lfm3-audio-2b.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- [DiffusionGemma 26B A4B IT vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-lfm3-audio-2b.md)\n- [EXAONE 4.5 33B vs Laguna S 2.1](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-s-2-1.md)\n- [EXAONE 4.5 33B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-lfm3-audio-2b.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 12B IT vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-lfm3-audio-2b.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 26B A4B IT vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-lfm3-audio-2b.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 31B IT vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-lfm3-audio-2b.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 E2B IT vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-lfm3-audio-2b.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- [Gemma 4 E4B IT vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-lfm3-audio-2b.md)\n- 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LFM3-Audio-2B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-audio-2b.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- [gpt-oss-20b vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-lfm3-audio-2b.md)\n- [Granite 4.2 30B vs Laguna S 2.1](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-s-2-1.md)\n- [Granite 4.2 30B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-lfm3-audio-2b.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- [Granite 4.2 3B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-lfm3-audio-2b.md)\n- [Granite 4.2 8B vs Laguna S 2.1](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-laguna-s-2-1.md)\n- [Granite 4.2 8B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-lfm3-audio-2b.md)\n- [Hy-Memory-30B-A3B vs Laguna S 2.1](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-laguna-s-2-1.md)\n- [Hy-Memory-30B-A3B vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-lfm3-audio-2b.md)\n- [Hy3 vs Laguna S 2.1](https://www.anchorterminal.com/compare/hy3-vs-laguna-s-2-1.md)\n- [Hy3 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/hy3-vs-lfm3-audio-2b.md)\n- [Inkling-Small vs Laguna S 2.1](https://www.anchorterminal.com/compare/inkling-small-vs-laguna-s-2-1.md)\n- [Inkling-Small vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/inkling-small-vs-lfm3-audio-2b.md)\n- [Inkling vs Laguna S 2.1](https://www.anchorterminal.com/compare/inkling-vs-laguna-s-2-1.md)\n- [Inkling vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/inkling-vs-lfm3-audio-2b.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- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs 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    "description": "Laguna S 2.1 and LFM3-Audio-2B score within a point of each other for open-weight models you run yourself, 61 and 61 out of 100. Prices, MCP, x402, uptime and agent notes side by side.",
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    "h1": "Laguna S 2.1 vs LFM3-Audio-2B",
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    "published": "2026-10-01",
    "section": "tools",
    "title": "Laguna S 2.1 vs LFM3-Audio-2B for AI agents in 2026: scores and prices",
    "toc": null,
    "updated": "2026-11-10",
    "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm3-audio-2b"
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