{
  "data": {
    "a": {
      "slug": "laguna-xs-2-1",
      "name": "Laguna XS 2.1",
      "vendor": "Poolside",
      "vendorUrl": "https://poolside.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Laguna XS 2.1 is Poolside's open-weight Mixture-of-Experts coding model, 33B total and 3B active parameters, with switchable reasoning and a 262,144-token context, published on Hugging Face under OpenMDW-1.1.",
      "url": "https://www.anchorterminal.com/tools/laguna-xs-2-1",
      "markdownUrl": "https://www.anchorterminal.com/tools/laguna-xs-2-1.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/laguna-xs-2-1.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/laguna-xs-2-1.json",
      "dns": "laguna-xs-2-1.grade.anchorterminal.com",
      "repo": "https://huggingface.co/poolside/Laguna-XS-2.1",
      "license": "OpenMDW-1.1",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-XS-2.1"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-XS-2.1-FP8"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-XS-2.1-INT4"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-XS-2.1-NVFP4"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-XS-2.1-NVFP4-mlx"
        },
        {
          "registry": "huggingface",
          "name": "poolside/Laguna-XS-2.1-GGUF"
        },
        {
          "registry": "ollama",
          "name": "laguna-xs-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, 66.9 GB for the BF16 files and 20.3 GB for Poolside's Q4_K_M GGUF, which is also Ollama's default build. Poolside's OpenRouter endpoints expired on 31 October 2026 and no other host was found (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-XS-2.1",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "coding",
        "reasoning",
        "tool-calling",
        "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": 36,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "interface": 85,
          "reach": 80,
          "risk": 55,
          "upkeep": 46
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "low",
          "date": "2026-11-03"
        },
        "negative": 0,
        "verdict": "A small coding and agent cousin with 3B active parameters, so it's quick on modest hardware. Poolside's 4-bit GGUF, also Ollama's default, needs about 24 GB, and every major runtime runs it. The main risks are that nobody at Poolside answers its discussions, there are no safety results, and the SGLang route runs repository code.",
        "bestFor": "Agents that want a fast local coding model on a 32 GB GPU or Mac, with tool calling and a permissive licence.",
        "strengths": [
          "Released support in llama.cpp, Ollama, vLLM, SGLang, Transformers and mlx-lm",
          "Poolside's own Q4_K_M, FP8, INT4, NVFP4 and MLX builds, the Q4_K_M at 20.3 GB",
          "Permissive OpenMDW-1.1 licence with no gate, account or use policy",
          "Tool calling and the poolside_v1 parser documented on the card, several calls a turn",
          "Thinking on or off per request, with the reasoning returned in reasoning_content"
        ],
        "weaknesses": [
          "No reply from Poolside to any discussion, including reports about the tokenizer and remote code",
          "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",
          "The template defaults thinking off while generation_config.json turns it on",
          "No structured output documentation, and no limitations, languages or cut-off on the card",
          "No hosted endpoint since Poolside's OpenRouter endpoints expired on 31 October 2026, so an agent without the hardware can't call it"
        ],
        "agentNotes": [
          "Quickest start is `ollama run laguna-xs-2.1`, 20 GB of files, the same Q4_K_M as Poolside's GGUF",
          "On our reference machine use `llama-server -hf poolside/Laguna-XS-2.1-GGUF:Q4_K_M --jinja -c 131072`, from a llama.cpp release with the laguna architecture (b11772 has it), or BF16 with vLLM (66.9 GB)",
          "With vLLM use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on a build with vllm-project/vllm#47311, or `--tool-call-parser glm47` on older builds",
          "Thinking is off in the template unless you pass `enable_thinking` true or start the server with `--default-chat-template-kwargs '{\"enable_thinking\": true}'`, which Poolside recommends for agentic coding",
          "Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped",
          "Sampling per the card is temperature 1.0 and top_k 20",
          "The card warns that Ollama on Apple Silicon may return empty output until llama.cpp#25389 ships",
          "Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.8,
        "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": 55,
          "upkeep": 46
        },
        "provenanceScore": 69,
        "checked": {
          "categories": {
            "interface": "2026-11-03",
            "reach": "2026-11-03",
            "risk": "2026-11-03",
            "upkeep": "2026-11-03"
          },
          "last": "2026-11-03",
          "lastMoved": "2026-11-03",
          "oldest": "2026-11-03",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run laguna-xs-2.1\n# or, with vLLM 0.21.0 or later (a build with vllm-project/vllm#47311):\nvllm serve poolside/Laguna-XS-2.1 --tool-call-parser poolside_v1 --reasoning-parser poolside_v1 \\\n  --enable-auto-tool-choice --default-chat-template-kwargs '{\"enable_thinking\": true}'",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"laguna-xs-2.1\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/laguna-xs-2-1"
      },
      "sameCompany": [
        "laguna-m-1",
        "laguna-s-2-1"
      ],
      "weights": {
        "trainedBy": "Poolside",
        "params": "33.4B total, 3B active",
        "context": 262144,
        "goodFor": "Agentic coding and long-horizon terminal work on one GPU or a 32 GB machine, with tool calling and reasoning that turns on or off per request.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "LM Studio",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Laguna-XS-2.1-INT4",
            "url": "https://huggingface.co/poolside/Laguna-XS-2.1-INT4",
            "who": "publisher",
            "precision": "int4 (w4a16)",
            "sizeGB": 23.9,
            "memoryGB": 32,
            "format": "safetensors"
          },
          {
            "name": "Laguna-XS-2.1-NVFP4",
            "url": "https://huggingface.co/poolside/Laguna-XS-2.1-NVFP4",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 21.6,
            "memoryGB": 32,
            "format": "safetensors",
            "note": "For NVIDIA Blackwell GPUs"
          },
          {
            "name": "Laguna-XS-2.1-NVFP4-mlx",
            "url": "https://huggingface.co/poolside/Laguna-XS-2.1-NVFP4-mlx",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 21.6,
            "memoryGB": 32,
            "format": "mlx",
            "runsOn": [
              "MLX"
            ]
          },
          {
            "name": "Laguna-XS-2.1-GGUF Q4_K_M",
            "url": "https://huggingface.co/poolside/Laguna-XS-2.1-GGUF",
            "who": "publisher",
            "precision": "q4_k_m",
            "sizeGB": 20.3,
            "memoryGB": 32,
            "format": "gguf",
            "runsOn": [
              "llama.cpp",
              "Ollama"
            ],
            "note": "Laguna-XS-2.1-Q4_K_M.gguf, 20,274,300,032 bytes. The repository also holds a BF16 GGUF of 66.9 GB (96 GB of memory)"
          },
          {
            "name": "ollama laguna-xs-2.1:latest",
            "url": "https://ollama.com/library/laguna-xs-2.1:latest",
            "who": "ollama",
            "precision": "q4_k_m",
            "sizeGB": 20.3,
            "memoryGB": 32,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "Ollama shows 20 GB. Its model blob (sha256 1ac7079101fc) is Poolside's Q4_K_M GGUF, so the exact size is Poolside's. The library also has q8_0 (36 GB), bf16 (67 GB) and MLX tags (nvfp4 shown as 20 GB, exact size unpublished, mxfp8 40 GB, mlx-bf16 68 GB). The card warns that ollama run may return empty output on Apple Silicon until llama.cpp#25389 ships"
          },
          {
            "name": "Laguna-XS-2.1-FP8",
            "url": "https://huggingface.co/poolside/Laguna-XS-2.1-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 35.3,
            "memoryGB": 48,
            "format": "safetensors"
          },
          {
            "name": "Laguna-XS-2.1",
            "url": "https://huggingface.co/poolside/Laguna-XS-2.1",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 66.9,
            "memoryGB": 96,
            "format": "safetensors",
            "runsOn": [
              "vLLM",
              "SGLang",
              "Transformers"
            ]
          }
        ],
        "run": "llama-server -hf poolside/Laguna-XS-2.1-GGUF:Q4_K_M --jinja -c 131072 --port 8000",
        "runBuild": "Laguna-XS-2.1-GGUF Q4_K_M",
        "checked": "2026-10-21",
        "minMemoryGB": 32
      },
      "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-S-2.1",
            "url": "https://huggingface.co/poolside/Laguna-S-2.1",
            "params": "117.56B (Hub safetensors count; the name gives only the size class S)",
            "listing": "https://www.anchorterminal.com/tools/laguna-s-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": 1
      },
      "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 blog post for this release links its collection there.",
          "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. The June 2026 entry calls XS 2.1 an incremental update to Laguna XS.2.",
          "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-xs-2-1.json",
      "live": {
        "slug": "laguna-xs-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 XS 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 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-xs-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 that Poolside's blog links, 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": 6,
        "category": "upkeep",
        "leads": "lfm3-audio-2b",
        "name": "Documentation and upkeep",
        "reasons": {
          "a": "Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 10, the linked report describes sources and filtering and Poolside's S 2.1 post gives the shared November 2025 cut-off. Last change 15, 19 August 2026, 76 days back. Responsiveness 0, Poolside answered none of the 6 discussions. Version policy 5, XS.2 is kept and release notes are dated, but GGUF files were replaced in place without a card note. File health 5, generation config and template disagree on the thinking default and two file 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": 46,
          "b": 52
        }
      }
    ],
    "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": "2.8/5 (4)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Laguna XS 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 documentation and upkeep.",
        "question": "Which is better for AI agents, Laguna XS 2.1 or LFM3-Audio-2B?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Risk, 55 against 40"
        ],
        "also": null,
        "goodFor": "Agents that want a fast local coding model on a 32 GB GPU or Mac, with tool calling and a permissive licence.",
        "slug": "laguna-xs-2-1",
        "watchFor": "No reply from Poolside to any discussion, including reports about the tokenizer and remote code"
      },
      {
        "aheadOn": [
          "Documentation and upkeep, 52 against 46"
        ],
        "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": {
      "laguna-xs-2-1": [
        {
          "causes": [
            "product"
          ],
          "date": "2026-11-03",
          "delta": 0,
          "from": 61,
          "fromGrade": "C",
          "to": 61,
          "toGrade": "C"
        }
      ],
      "lfm3-audio-2b": 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-xs-2-1.json",
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        "url": "https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-xs-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-xs-2-1.json",
        "title": "Apertus v1.5 8B vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-xs-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-xs-2-1.json",
        "title": "Apodex-1.1-mini vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-xs-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-xs-2-1.json",
        "title": "Arete-27B vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/arete-27b-vs-laguna-xs-2-1"
      },
      {
        "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-xs-2-1.json",
        "title": "BigBang-v1 vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-xs-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-xs-2-1.json",
        "title": "Carbon-X vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-laguna-xs-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/carbon-x-vs-lfm3-audio-2b.json",
        "title": "Carbon-X vs LFM3-Audio-2B",
        "url": "https://www.anchorterminal.com/compare/carbon-x-vs-lfm3-audio-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-laguna-xs-2-1.json",
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        "url": "https://www.anchorterminal.com/compare/cola2-vs-laguna-xs-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cola2-vs-lfm3-audio-2b.json",
        "title": "Cola2 vs LFM3-Audio-2B",
        "url": "https://www.anchorterminal.com/compare/cola2-vs-lfm3-audio-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-xs-2-1.json",
        "title": "Cosmos-Reason2-2B vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-xs-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lfm3-audio-2b.json",
        "title": "Cosmos-Reason2-2B vs LFM3-Audio-2B",
        "url": "https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-lfm3-audio-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-xs-2-1.json",
        "title": "Darwin-36B-Opus vs Laguna XS 2.1",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-xs-2-1"
      },
      {
        "json": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-audio-2b.json",
        "title": "Darwin-36B-Opus vs LFM3-Audio-2B",
        "url": "https://www.anchorterminal.com/compare/darwin-36b-opus-vs-lfm3-audio-2b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-xs-2-1.json",
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      {
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        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-35b-a3b"
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-397b"
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        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-9b.json",
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-ornith-1-5-9b"
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        "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"
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen-agentworld-35b-a3b"
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        "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"
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-0-8b"
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-2b"
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-397b-a17b"
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        "title": "LFM3-Audio-2B vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-4b"
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        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-5-9b.json",
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        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-6-27b.json",
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        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-6-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-6-35b-a3b"
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        "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"
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        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-coder-30b-a3b-instruct.json",
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        "json": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-coder-next.json",
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        "url": "https://www.anchorterminal.com/compare/lfm3-audio-2b-vs-qwen3-coder-next"
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        "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"
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        "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"
      },
      {
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        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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      {
        "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"
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    ],
    "panel": null,
    "scores": [
      {
        "key": "capability",
        "name": "Capability",
        "pending": true,
        "weight": 35
      },
      {
        "by": 0,
        "edge": "",
        "key": "reach",
        "laguna-xs-2-1": 80,
        "lfm3-audio-2b": 80,
        "name": "Reach",
        "weight": 25
      },
      {
        "by": 15,
        "edge": "laguna-xs-2-1",
        "key": "risk",
        "laguna-xs-2-1": 55,
        "lfm3-audio-2b": 40,
        "name": "Risk",
        "weight": 20
      },
      {
        "by": 0,
        "edge": "",
        "key": "interface",
        "laguna-xs-2-1": 85,
        "lfm3-audio-2b": 85,
        "name": "Agent interface",
        "weight": 10
      },
      {
        "by": 6,
        "edge": "lfm3-audio-2b",
        "key": "upkeep",
        "laguna-xs-2-1": 46,
        "lfm3-audio-2b": 52,
        "name": "Documentation and upkeep",
        "weight": 10
      }
    ],
    "summary": "Laguna XS 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 documentation and upkeep. Both do open-weight models you run yourself.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "laguna-xs-2-1": "A small coding and agent cousin with 3B active parameters, so it's quick on modest hardware. Poolside's 4-bit GGUF, also Ollama's default, needs about 24 GB, and every major runtime runs it. The main risks are that nobody at Poolside answers its discussions, there are no safety results, and the SGLang route runs repository code.",
      "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-xs-2-1-vs-lfm3-audio-2b",
    "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-audio-2b.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-audio-2b.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-audio-2b.min.md"
  },
  "markdown": "Laguna XS 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 documentation and upkeep. Both do open-weight models you run yourself.\n\n- Laguna XS 2.1: grade C, 61/100, rank #46 of 160 open-weight models. Markdown https://www.anchorterminal.com/tools/laguna-xs-2-1.md · JSON https://www.anchorterminal.com/api/v1/tools/laguna-xs-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 XS 2.1 (C)\n\nGood for: Agents that want a fast local coding model on a 32 GB GPU or Mac, with tool calling and a permissive licence.\n\nAhead on:\n- Risk, 55 against 40\n\nWatch for: No reply from Poolside to any discussion, including reports about the tokenizer and remote code\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- Documentation and upkeep, 52 against 46\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 XS 2.1 +15\n\n- Laguna XS 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 that Poolside's blog links, 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 +6\n\n- Laguna XS 2.1 (46): Model card 11 of 20, intended use, architecture, parameters and context are there, limitations, languages and a cut-off aren't. Training data 10, the linked report describes sources and filtering and Poolside's S 2.1 post gives the shared November 2025 cut-off. Last change 15, 19 August 2026, 76 days back. Responsiveness 0, Poolside answered none of the 6 discussions. Version policy 5, XS.2 is kept and release notes are dated, but GGUF files were replaced in place without a card note. File health 5, generation config and template disagree on the thinking default and two file 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## Score by category\n\n| Category | Weight | Laguna XS 2.1 | LFM3-Audio-2B | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35%, pending | pending | pending | not scored in this run |\n| Reach | 25% (25 this run) | 80 | 80 | even |\n| Risk | 20% (20 this run) | 55 | 40 | Laguna XS 2.1 +15 |\n| Agent interface | 10% (10 this run) | 85 | 85 | even |\n| Documentation and upkeep | 10% (10 this run) | 46 | 52 | LFM3-Audio-2B +6 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **61 · C** | **61 · C** | |\n\n## Facts side by side\n\n| Fact | Laguna XS 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 | 2.8/5 (4) | none |\n\n## How the scores have moved\n\n### Laguna XS 2.1\n\n- no change on 3 November 2026: product\n\n### LFM3-Audio-2B\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Laguna XS 2.1.** A small coding and agent cousin with 3B active parameters, so it's quick on modest hardware. Poolside's 4-bit GGUF, also Ollama's default, needs about 24 GB, and every major runtime runs it. The main risks are that nobody at Poolside answers its discussions, there are no safety results, and the SGLang route runs repository code.\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 XS 2.1\n\n1. Quickest start is `ollama run laguna-xs-2.1`, 20 GB of files, the same Q4_K_M as Poolside's GGUF\n2. On our reference machine use `llama-server -hf poolside/Laguna-XS-2.1-GGUF:Q4_K_M --jinja -c 131072`, from a llama.cpp release with the laguna architecture (b11772 has it), or BF16 with vLLM (66.9 GB)\n3. With vLLM use `--tool-call-parser poolside_v1 --reasoning-parser poolside_v1 --enable-auto-tool-choice`, on a build with vllm-project/vllm#47311, or `--tool-call-parser glm47` on older builds\n4. Thinking is off in the template unless you pass `enable_thinking` true or start the server with `--default-chat-template-kwargs '{\"enable_thinking\": true}'`, which Poolside recommends for agentic coding\n5. Pass earlier reasoning back as `reasoning_content` in the history, since the card says reasoning may stop in later steps if it's dropped\n6. Sampling per the card is temperature 1.0 and top_k 20\n7. The card warns that Ollama on Apple Silicon may return empty output until llama.cpp#25389 ships\n8. Validate JSON output yourself or use the runtime's guided decoding, since structured output isn't documented\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 XS 2.1 or LFM3-Audio-2B?\n\nLaguna XS 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 documentation and upkeep.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-audio-2b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-audio-2b.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"laguna-xs-2-1\", \"b\": \"lfm3-audio-2b\"}`. From a terminal: `anchor compare laguna-xs-2-1 lfm3-audio-2b`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/laguna-xs-2-1.json and https://www.anchorterminal.com/api/v1/tools/lfm3-audio-2b.json\n\n## Other comparisons with Laguna XS 2.1 or LFM3-Audio-2B\n\n- [Agents-A1-4B vs Laguna XS 2.1](https://www.anchorterminal.com/compare/agents-a1-4b-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/arete-27b-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/bigbang-v1-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/carbon-x-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/cola2-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/cosmos-reason2-2b-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/darwin-36b-opus-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/deepseek-v3-2-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/deepseek-v4-1-flash-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/deepseek-v4-flash-0731-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/devstral-small-2-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/diffusiongemma-26b-a4b-it-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/exaone-4-5-33b-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/gemma-4-12b-it-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/gemma-4-26b-a4b-it-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/gemma-4-31b-it-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/gemma-4-e2b-it-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/gemma-4-e4b-it-vs-laguna-xs-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- [GLM-4.5-Air vs Laguna XS 2.1](https://www.anchorterminal.com/compare/glm-4-5-air-vs-laguna-xs-2-1.md)\n- [GLM-4.5-Air vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/glm-4-5-air-vs-lfm3-audio-2b.md)\n- [GLM-4.7-Flash vs Laguna XS 2.1](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-laguna-xs-2-1.md)\n- [GLM-4.7-Flash vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/glm-4-7-flash-vs-lfm3-audio-2b.md)\n- [GLM-5.3-Flash vs Laguna XS 2.1](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-laguna-xs-2-1.md)\n- [GLM-5.3-Flash vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/glm-5-3-flash-vs-lfm3-audio-2b.md)\n- [GLM-5.3 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/glm-5-3-vs-laguna-xs-2-1.md)\n- [GLM-5.3 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/glm-5-3-vs-lfm3-audio-2b.md)\n- [gpt-oss-120b vs Laguna XS 2.1](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-laguna-xs-2-1.md)\n- [gpt-oss-120b vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/gpt-oss-120b-vs-lfm3-audio-2b.md)\n- [gpt-oss-20b vs Laguna XS 2.1](https://www.anchorterminal.com/compare/gpt-oss-20b-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/granite-4-2-30b-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/granite-4-2-3b-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/granite-4-2-8b-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/hy-memory-30b-a3b-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/hy3-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/inkling-small-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/inkling-vs-laguna-xs-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 XS 2.1](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-laguna-xs-2-1.md)\n- [InternVL3.5-GPT-OSS-20B-A4B-Preview vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-lfm3-audio-2b.md)\n- [Kimi K3.1 Pro vs Laguna XS 2.1](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-laguna-xs-2-1.md)\n- [Kimi K3.1 Pro vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/kimi-k3-1-pro-vs-lfm3-audio-2b.md)\n- [Kimi K3 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/kimi-k3-vs-laguna-xs-2-1.md)\n- [Kimi K3 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/kimi-k3-vs-lfm3-audio-2b.md)\n- [Kolibri-1 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/kolibri-1-vs-laguna-xs-2-1.md)\n- [Kolibri-1 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/kolibri-1-vs-lfm3-audio-2b.md)\n- [Kronos vs Laguna XS 2.1](https://www.anchorterminal.com/compare/kronos-vs-laguna-xs-2-1.md)\n- [Kronos vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/kronos-vs-lfm3-audio-2b.md)\n- [Laguna M.1 vs Laguna XS 2.1](https://www.anchorterminal.com/compare/laguna-m-1-vs-laguna-xs-2-1.md)\n- [Laguna M.1 vs LFM3-Audio-2B](https://www.anchorterminal.com/compare/laguna-m-1-vs-lfm3-audio-2b.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 LFM3-Audio-2B](https://www.anchorterminal.com/compare/laguna-s-2-1-vs-lfm3-audio-2b.md)\n- [Laguna XS 2.1 vs LBS-27B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lbs-27b.md)\n- [Laguna XS 2.1 vs LFM2.5-2.6B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm2-5-2-6b.md)\n- [Laguna XS 2.1 vs LFM3-1.7B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-1-7b.md)\n- [Laguna XS 2.1 vs LFM3-Omni-2B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-omni-2b.md)\n- [Laguna XS 2.1 vs LFM3-VL-2B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-vl-2b.md)\n- [Laguna XS 2.1 vs Ling-3.0-tiny](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ling-3-0-tiny.md)\n- [Laguna XS 2.1 vs Ling-3.1-flash-1019](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-ling-3-1-flash-1019.md)\n- [Laguna XS 2.1 vs LongCat-2.5](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-longcat-2-5.md)\n- [Laguna XS 2.1 vs MiMo-V2.6 Distill Qwen 9B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-mimo-v2-6-distill-qwen-9b.md)\n- [Laguna XS 2.1 vs MiMo-V2.6-Flash-RL](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-mimo-v2-6-flash-rl.md)\n- [Laguna XS 2.1 vs MiniCPM-o 4.5](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm-o-4-5.md)\n- [Laguna XS 2.1 vs MiniCPM-V 4.7 1B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm-v-4-7-1b.md)\n- [Laguna XS 2.1 vs MiniCPM-V 4.7 35B-A3B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm-v-4-7-35b-a3b.md)\n- [Laguna XS 2.1 vs MiniCPM5-2B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minicpm5-2b.md)\n- [Laguna XS 2.1 vs MiniMax-M2.5](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minimax-m2-5.md)\n- [Laguna XS 2.1 vs MiniMax-M2.7](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minimax-m2-7.md)\n- [Laguna XS 2.1 vs MiniMax-M3.1-Flash](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-minimax-m3-1-flash.md)\n- [Laguna XS 2.1 vs Mistral Large 4](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-mistral-large-4.md)\n- [Laguna XS 2.1 vs Muse Glimmer 30B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-muse-glimmer-30b.md)\n- [Laguna XS 2.1 vs Nanbeige4.2-3B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nanbeige-4-2-3b.md)\n- [Laguna XS 2.1 vs Nanbeige4.3-33B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nanbeige-4-3-33b.md)\n- [Laguna XS 2.1 vs NVIDIA Nemotron 3.5 Bolt E4B 4GB](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-5-bolt-e4b-4gb.md)\n- [Laguna XS 2.1 vs Nemotron 3.5 Lightning 30B A3B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-5-lightning-30b-a3b.md)\n- [Laguna XS 2.1 vs Nemotron 3 Nano 30B A3B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-nano-30b-a3b.md)\n- [Laguna XS 2.1 vs Nemotron 3 Nano 4B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-nano-4b.md)\n- [Laguna XS 2.1 vs Nemotron 3 Nano Omni 30B A3B Reasoning](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-nano-omni-30b-a3b-reasoning.md)\n- [Laguna XS 2.1 vs Nemotron 3 Super 120B A12B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-super-120b-a12b.md)\n- [Laguna XS 2.1 vs Nemotron 3 Ultra 550B A55B](https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-nemotron-3-ultra-550b-a55b.md)\n- [Laguna XS 2.1 vs North Mini Code 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    "description": "Laguna XS 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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    "section": "tools",
    "title": "Laguna XS 2.1 vs LFM3-Audio-2B for AI agents (2026) | Anchor Terminal",
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    "updated": "2026-11-10",
    "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-lfm3-audio-2b"
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