{
  "data": {
    "a": {
      "slug": "muse-spark-open",
      "name": "Muse Spark Open",
      "vendor": "Meta",
      "vendorUrl": "https://dev.meta.ai/models/muse-spark-open",
      "kind": "model",
      "category": "inference",
      "summary": "Muse Spark Open is Meta's open-weight multimodal model for coding and agentic work, with 816B total and 42B active parameters and a 1M-token context, released on 15 October 2026 under the Muse Model Licence for self-hosting.",
      "url": "https://www.anchorterminal.com/tools/muse-spark-open",
      "markdownUrl": "https://www.anchorterminal.com/tools/muse-spark-open.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/muse-spark-open.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json",
      "repo": "https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B",
      "license": "Muse Model Licence (source-available weights, not an OSI licence), free of charge with an attribution notice, a separate agreement with Meta before Model as a Service by a licensee group above $20M gross revenue, and the Muse Spark Open Usage Policy",
      "transports": [
        "http"
      ],
      "packages": [],
      "auth": "none",
      "authNotes": "Running the model needs no account or key. Getting Meta's weights does. Both Hugging Face repositories (BF16 and NVFP4) are gated with manual review and ask for full legal name, date of birth, country, affiliation and job title, and downloads then use a Hugging Face access token. The GGUF quantisations from ggml-org and Unsloth that Meta's docs point to are not gated. A local server has whatever authentication the owner adds, such as llama.cpp's `--api-key`.",
      "pricing": "free",
      "pricingNotes": "Free to download and run under the Muse Model Licence, with the owner's GPUs as the cost. A licensee whose group has more than $20M gross revenue in any 12 months must notify Meta and sign a separate agreement before offering it as Model as a Service. Hosted copies cost $1.25 input, $0.15 cached input and $4.25 output per million tokens on Fireworks, Baseten, Modal and OpenRouter (checked 2026-10-15). Meta Model API does not serve it.",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402. Muse Spark Open is a model the owner runs, with no payment route from Meta, and Meta Model API does not serve it (checked 2026-10-15).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-15"
      },
      "docsUrl": "https://dev.meta.ai/docs/muse-spark-open",
      "llmsTxt": "https://dev.meta.ai/llms.txt",
      "capabilities": [
        "inference.llm",
        "inference.open-weights",
        "inference.local"
      ],
      "tags": [
        "model",
        "open-weights",
        "self-hosted",
        "local",
        "free",
        "gated",
        "multimodal",
        "openai-compatible",
        "llms-txt",
        "gpu",
        "new"
      ],
      "lastRelease": "2026-10-15",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 53.4,
        "grade": "D",
        "agentReady": false,
        "rank": 760,
        "ranked": true,
        "rankOf": 1095,
        "categoryRank": 16,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 69,
          "maintenance": 60,
          "payments": 50,
          "reliability": 42,
          "schema": 61,
          "security": 44,
          "transparency": 53
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-15"
        },
        "negative": 0,
        "verdict": "Muse Spark Open runs on the owner's hardware in seven runtimes, with OpenAI-compatible servers in vLLM and SGLang, standard tool calls, a 1M-token context and Meta's own serving docs. Serving the 537 GB NVFP4 checkpoint takes four B300 GPUs, Meta's download is gated by manual review, and the licence adds attribution and a revenue threshold for model resellers.",
        "bestFor": "A team with a four-GPU Blackwell node, or two to four Mac Studios, that wants a 1M-token multimodal coding and agent model on its own hardware with no prompts leaving it.",
        "strengths": [
          "816B total and 42B active parameters with a 1,048,576-token context, taking text, image, video and audio input",
          "Day-one support in vLLM, SGLang, TensorRT-LLM, Transformers, llama.cpp, MLX and Unsloth, with commands for each in Meta's docs",
          "With the `muse` parsers, reasoning comes back in its own field and tool calls as a standard `tool_calls` array",
          "The licence grants use, fine-tuning, distillation and resale free of charge, with no user cap and no regional exclusion",
          "llms.txt and Markdown docs cover checkpoints, prompting, stop tokens, recommended settings and post-training"
        ],
        "weaknesses": [
          "The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight",
          "Meta's Hugging Face repositories need manual approval with legal name and date of birth, which the Get the model page doesn't mention",
          "Products must display \"Built with Muse Spark Open\", and a company group with over $20M revenue needs Meta's agreement to offer it as Model as a Service",
          "The Usage Policy rules out military, nuclear, espionage, critical infrastructure and heavy machinery uses, and users under 18",
          "Released on 15 October 2026, with no changelog, deprecation policy or CI found, and the full evaluation report not yet published"
        ],
        "agentNotes": [
          "Start vLLM or SGLang with `--reasoning-parser muse --tool-call-parser muse` (vLLM also `--enable-auto-tool-choice`), or tool calls come back as raw text",
          "Set `reasoning_effort` to `low` or `medium` for short tasks. The default is `xhigh`, reasoning can't be turned off, and other values return an error",
          "Stop only on `\u003c|eot|\u003e` and end of text. Stopping on `\u003c|eom|\u003e` cuts off tool calls and final answers",
          "Stream long generations and leave `max_tokens` room for reasoning, or `content` can come back empty with `finish_reason` `length`",
          "Don't call Meta Model API for this model. Use a self-hosted server or a hosted provider's model string, such as `meta-models/muse-spark-open`"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "D",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 53.4
          }
        ],
        "editorialScores": {
          "ergonomics": 69,
          "maintenance": 60,
          "payments": 50,
          "reliability": 42,
          "schema": 61,
          "security": 44,
          "transparency": 50
        },
        "provenanceScore": 55
      },
      "connect": {
        "install": "hf download meta-models/Muse-Spark-Open-816B-A42B-NVFP4 --local-dir ./muse-spark-open-nvfp4\n\nexport VLLM_USE_RUST_FRONTEND=1\nvllm serve meta-models/Muse-Spark-Open-816B-A42B-NVFP4 \\\n    --tensor-parallel-size 4 \\\n    --enable-expert-parallel \\\n    --max-model-len 1048576 \\\n    --reasoning-parser muse \\\n    --tool-call-parser muse \\\n    --enable-auto-tool-choice",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\n    \"model\": \"meta-models/Muse-Spark-Open-816B-A42B-NVFP4\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Refactor this module.\"}],\n    \"reasoning_effort\": \"xhigh\"\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/muse-spark-open"
      },
      "sameCompany": [
        "meta-model-api",
        "muse-code"
      ],
      "area": "models",
      "provenance": {
        "legalEntity": "Meta Platforms, Inc.",
        "domain": "meta.ai",
        "domainRegistered": "2017-12-16",
        "endpointOnVendorDomain": null,
        "terms": "https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B/blob/main/LICENSE.md",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-15",
        "notes": [
          "The licence names Meta Platforms, Inc. as copyright holder, and defines Meta as Meta Platforms Ireland Limited for licensees in the European region and Meta Platforms, Inc. elsewhere. The model card names the same two as model provider.",
          "The licence is the document that governs use of the weights, so it is recorded as the terms. LICENSE.md matches the text shown on the gated access form word for word. The Usage Policy is its Exhibit A. The separate USE_POLICY.md that Meta's docs link answered 401 without access and wasn't read.",
          "No privacy policy governs the model, because the owner runs it and no input reaches Meta. The access form says its details are handled under the Meta Privacy Policy on www.facebook.com, whose robots.txt asks readers like ours not to fetch it, so it wasn't read.",
          "The domain is meta.ai, where Meta's developer docs (dev.meta.ai) and research post (research.meta.ai) sit, the same as the meta-model-api and muse-code listings. RDAP gives a registration date of 16 December 2017.",
          "No hosted endpoint from Meta, so no status page. No changelog for the model was found, and the Hugging Face commit history needs access to read.",
          "dev.meta.ai/.well-known/security.txt and research.meta.ai/.well-known/security.txt returned 404 on 15 October 2026.",
          "WebFetch read the research post. It refused the Hugging Face model card as outside its allowed set, so the card, LICENSE.md, the repository and collection metadata, the discussions, the evaluation methodology PDF, Meta's docs pages and the providers' model pages were read with curl."
        ],
        "score": 55
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/muse-spark-open.json",
      "live": {
        "slug": "muse-spark-open",
        "pages": [
          {
            "url": "https://huggingface.co/meta-models/Muse-Spark-Open-816B-A42B/blob/main/LICENSE.md",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-15T21:58:24.678553754Z",
            "changedAt": "2026-10-15T21:58:24.678553754Z",
            "fingerprint": "7ffd7a072112"
          }
        ],
        "updatedAt": "2026-10-15T21:58:24.678553754Z"
      }
    },
    "answer": "SambaCloud scores 66.4 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing.",
    "b": {
      "slug": "sambanova",
      "name": "SambaCloud",
      "vendor": "SambaNova Systems, Inc.",
      "vendorUrl": "https://sambanova.ai",
      "kind": "model",
      "category": "inference",
      "summary": "SambaCloud is SambaNova's hosted inference API for open-weight models running on its own RDU processors. It answers OpenAI-style chat, completions and Responses calls and Anthropic-style Messages calls, with Python and TypeScript SDKs.",
      "url": "https://www.anchorterminal.com/tools/sambanova",
      "markdownUrl": "https://www.anchorterminal.com/tools/sambanova.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/sambanova.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/sambanova.json",
      "repo": "https://github.com/sambanova/sambanova-python",
      "license": "Proprietary service under the SambaCloud Terms of Service. The SDKs and the OpenAPI document are Apache-2.0",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.sambanova.ai/v1",
      "packages": [
        {
          "registry": "pypi",
          "name": "sambanova"
        },
        {
          "registry": "npm",
          "name": "sambanova"
        }
      ],
      "auth": "api-key",
      "authNotes": "Self-serve Bearer key from the SambaCloud console at https://cloud.sambanova.ai/apis after a browser sign-up. The Messages routes also take the same key in `x-api-key`. Up to 25 keys per user, shown once, with no scopes.",
      "pricing": "freemium",
      "pricingNotes": "Free tier with no payment method, at 20 requests a minute, 20 requests a day and 200,000 tokens a day per model. Linking a card moves the account to the Developer tier, billed per token through Stripe, from $0.22 in and $0.59 out per 1M tokens on gpt-oss-120b (https://cloud.sambanova.ai/plans/pricing, checked 2026-10-08).",
      "priceSummary": "from $0.22 / 1M in",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs index, the OpenAPI document or the pricing page (checked 2026-10-08).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 2,
        "npmWeekly": 76,
        "pypiWeekly": 6129,
        "asOf": "2026-10-08"
      },
      "docsUrl": "https://docs.sambanova.ai/docs/en/get-started/overview",
      "rateLimitsUrl": "https://docs.sambanova.ai/docs/en/models/rate-limits",
      "llmsTxt": "https://docs.sambanova.ai/docs/llms.txt",
      "openapi": "https://raw.githubusercontent.com/sambanova/sambanova-inference-api-spec/refs/heads/main/openapi.documented.json",
      "capabilities": [
        "inference.llm",
        "inference.open-weights",
        "inference.fast"
      ],
      "tags": [
        "hosted",
        "model",
        "open-weights",
        "free-tier",
        "no-card",
        "openapi",
        "llms-txt",
        "openai-compatible",
        "anthropic-compatible",
        "python",
        "typescript",
        "status-page",
        "soc2"
      ],
      "lastRelease": "2026-09-17",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 66.4,
        "grade": "B",
        "agentReady": false,
        "rank": 313,
        "ranked": true,
        "rankOf": 1095,
        "categoryRank": 9,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 67,
          "maintenance": 77,
          "payments": 40,
          "reliability": 85,
          "schema": 81,
          "security": 58,
          "transparency": 63
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-08"
        },
        "negative": -2,
        "negativeNotes": [
          "2026-10-08. The models and rate-limit pages list `MiniMax-M2.7` as a production model, and the July 2026 release notes say `Mistral-Large-3-675B-Instruct-2512` was promoted to production. Neither is on the pricing page or in `/v1/models`, and the deprecations page records neither. Two points, since a keyed call was not made to confirm the ids fail (https://docs.sambanova.ai/docs/en/models/sambacloud-models, https://api.sambanova.ai/v1/models)."
        ],
        "verdict": "Per-token prices and the model list are readable without a key at `/v1/models`, and a free tier needs no card. Production models get two to three weeks' notice before removal, 13 model ids left between March and June 2026, and the docs disagree with the live catalogue on MiniMax-M2.7.",
        "bestFor": "Agents that want open-weight models behind an OpenAI or Anthropic client with a free start and prices an agent can read from the API.",
        "strengths": [
          "Public OpenAPI 3.1.1 document for all 10 operations, plus `llms.txt` and a Markdown copy of every docs page",
          "`GET /v1/models` answers without a key and returns context length, output cap and per-token prices for each model",
          "Free tier with no payment method at 20 requests a minute, 20 requests a day and 200,000 tokens a day per model",
          "One key works with the OpenAI client, the Anthropic client (`/v1/messages`, `x-api-key`) and SambaNova's own SDKs",
          "Status page with a component per model and no incident posted since 25 June 2026"
        ],
        "weaknesses": [
          "Production models get a notice of two to three weeks, and 13 model ids were removed between 9 March and 9 June 2026",
          "The docs list `MiniMax-M2.7` as a production model, while the pricing page and `/v1/models` did not list it on 8 October 2026",
          "`strict: true` on a JSON schema is accepted and has no effect, and the July 2026 notes record failing structured output on DeepSeek-V3.2",
          "Keys carry no scopes or project limits, and no key rotation guidance was found in the reviewed documentation",
          "The privacy policy is dated 27 May 2023, and no DPA, retention period or sub-processor list was found on the legal page"
        ],
        "agentNotes": [
          "Call `GET https://api.sambanova.ai/v1/models` at start-up and use only ids it returns. The docs name models the endpoint no longer lists",
          "Read `x-ratelimit-remaining-requests` and `x-ratelimit-remaining-requests-day` on every response. The free tier allows 20 requests a day per model",
          "Treat 429 `queue_full` and 503 `maintenance` as retryable after a delay, and 410 `model_deprecated` as a signal to change model",
          "Validate JSON output yourself. Schema enforcement is best effort and `strict: true` changes nothing",
          "Check `max_completion_tokens` per model. DeepSeek-V3.1 caps output at 7,168 tokens and Llama 3.3 70B at 3,072"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 66.4
          }
        ],
        "editorialScores": {
          "ergonomics": 67,
          "maintenance": 77,
          "payments": 40,
          "reliability": 85,
          "schema": 81,
          "security": 58,
          "transparency": 44
        },
        "provenanceScore": 81
      },
      "connect": {
        "install": "pip install sambanova   # or: npm install sambanova",
        "http": "curl https://api.sambanova.ai/v1/chat/completions \\\n  -H \"Authorization: Bearer $SAMBANOVA_API_KEY\" -H \"Content-Type: application/json\" \\\n  -d '{\"model\":\"gpt-oss-120b\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/sambanova"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "SambaNova Systems, Inc.",
        "domain": "sambanova.ai",
        "domainRegistered": "2017-12-18",
        "endpointOnVendorDomain": true,
        "terms": "https://sambanova.ai/cloud-end-user-license-agreement",
        "privacy": "https://sambanova.ai/privacy-policy",
        "statusPage": "https://status.sambanova.ai",
        "changelog": "https://docs.sambanova.ai/docs/en/release-notes/sambacloud",
        "securityTxt": "none",
        "checked": "2026-10-08",
        "notes": [
          "The SambaCloud Terms of Service name SambaNova Systems, Inc., a Delaware corporation at 2460 N. First St, Suite #100, San Jose, CA 95131, and define the Service as the SambaCloud platform. The page carries no date. The legal index says it was last updated on 5 February 2026.",
          "The privacy policy is the company's only one. Its last revision is dated 27 May 2023, it covers the website, communications and related services, and it does not name SambaCloud or API inputs.",
          "No DPA, SLA, acceptable use policy or sub-processor list is linked from https://sambanova.ai/legal-agreements.",
          "https://sambanova.ai/.well-known/security.txt returns 404.",
          "RDAP for sambanova.ai gives a registration date of 2017-12-18.",
          "The API answers at api.sambanova.ai and the console at cloud.sambanova.ai."
        ],
        "score": 81
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/sambanova.json",
      "live": {
        "slug": "sambanova",
        "probe": {
          "target": "https://api.sambanova.ai/v1",
          "method": "get",
          "lastAt": "2026-10-15T22:42:59.524498403Z",
          "lastOk": true,
          "lastStatus": 405,
          "lastMs": 412,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 99.76,
          "p50ms24h": 393,
          "p95ms24h": 881,
          "samples24h": 253,
          "samples30d": 1647,
          "days": [
            {
              "date": "2026-10-09",
              "probes": 169,
              "ok": 169
            },
            {
              "date": "2026-10-10",
              "probes": 247,
              "ok": 247
            },
            {
              "date": "2026-10-11",
              "probes": 247,
              "ok": 247
            },
            {
              "date": "2026-10-12",
              "probes": 247,
              "ok": 244
            },
            {
              "date": "2026-10-13",
              "probes": 248,
              "ok": 247
            },
            {
              "date": "2026-10-14",
              "probes": 249,
              "ok": 249
            },
            {
              "date": "2026-10-15",
              "probes": 240,
              "ok": 240
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.sambanova.ai",
          "indicator": "none",
          "summary": "All Systems Operational",
          "checkedAt": "2026-10-15T22:42:33.058652828Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "sambanova/sambanova-python",
            "version": "v1.13.0",
            "released": "2026-09-17",
            "seenAt": "2026-10-15T00:19:20.302517944Z"
          },
          {
            "registry": "npm",
            "name": "sambanova",
            "version": "1.10.0",
            "seenAt": "2026-10-15T00:19:18.127149399Z"
          },
          {
            "registry": "pypi",
            "name": "sambanova",
            "version": "1.13.0",
            "released": "2026-09-17",
            "seenAt": "2026-10-15T00:19:17.877918648Z"
          }
        ],
        "githubStars": 2,
        "npmWeekly": 190,
        "pypiWeekly": 5174,
        "securityTxt": {
          "url": "https://sambanova.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-15T15:48:25.781160745Z"
        },
        "llmsTxt": {
          "url": "https://docs.sambanova.ai/docs/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-15T14:17:40.296025176Z"
        },
        "domain": {
          "domain": "sambanova.ai",
          "registered": "2017-12-18",
          "source": "https://rdap.identitydigital.services/rdap/domain/sambanova.ai",
          "checkedAt": "2026-10-11T13:13:55.590571808Z"
        },
        "pages": [
          {
            "url": "https://docs.sambanova.ai/docs/en/release-notes/sambacloud",
            "kind": "changelog",
            "status": 304,
            "checkedAt": "2026-10-15T21:56:13.74936178Z",
            "changedAt": "2026-10-15T21:26:18.671309738Z",
            "fingerprint": "413a793f2292"
          },
          {
            "url": "https://docs.sambanova.ai/docs/en/models/deprecations",
            "kind": "deprecations",
            "status": 304,
            "checkedAt": "2026-10-15T21:56:11.552382601Z",
            "changedAt": "2026-10-15T21:26:16.17926249Z",
            "fingerprint": "4174e8539120"
          },
          {
            "url": "https://cloud.sambanova.ai/plans/pricing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-15T21:51:58.527517784Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "71a596d0bd9a"
          },
          {
            "url": "https://sambanova.ai/privacy-policy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-10-15T22:03:24.650295677Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "dcd17eb3af4c"
          },
          {
            "url": "https://sambanova.ai/cloud-end-user-license-agreement",
            "kind": "terms",
            "status": 200,
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            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "e1f8368edf9b"
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        ],
        "updatedAt": "2026-10-15T22:42:59.524498403Z"
      }
    },
    "facts": [
      {
        "a": "Model API",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Meta",
        "b": "SambaNova Systems, Inc.",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "https://api.sambanova.ai/v1",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Freemium",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Muse Model Licence (source-available weights, not an OSI licence), free of charge with an attribution notice, a separate agreement with Meta before Model as a Service by a licensee group above $20M gross revenue, and the Muse Spark Open Usage Policy",
        "b": "Proprietary service under the SambaCloud Terms of Service. The SDKs and the OpenAPI document are Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
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      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
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        "a": "no document linked",
        "b": "2023-05-27",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "yes",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "not found in the text",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "not found in the text",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "none",
        "b": "2 stars, 76 npm/wk, 6.1k PyPI/wk",
        "name": "Popularity"
      }
    ],
    "faq": [
      {
        "answer": "SambaCloud scores 66.4 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing.",
        "question": "Which is better for AI agents, Muse Spark Open or SambaCloud?"
      },
      {
        "answer": "Muse Spark Open needs no key. SambaCloud needs an API key.",
        "question": "Do Muse Spark Open and SambaCloud need an API key?"
      },
      {
        "answer": "No hosted endpoint is listed for Muse Spark Open. SambaCloud has a hosted endpoint at https://api.sambanova.ai/v1.",
        "question": "Can an agent call Muse Spark Open and SambaCloud without installing anything?"
      }
    ],
    "goodFor": [
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        "aheadOn": [
          "Payments \u0026 pricing, 50 against 40"
        ],
        "also": [
          "No key needed to call it"
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        "goodFor": "A team with a four-GPU Blackwell node, or two to four Mac Studios, that wants a 1M-token multimodal coding and agent model on its own hardware with no prompts leaving it.",
        "slug": "muse-spark-open",
        "watchFor": "The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight"
      },
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          "Schema \u0026 documentation, 81 against 61",
          "Security \u0026 auth, 58 against 44",
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          "Transparency \u0026 trust, 63 against 53"
        ],
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        "goodFor": "Agents that want open-weight models behind an OpenAI or Anthropic client with a free start and prices an agent can read from the API.",
        "slug": "sambanova",
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        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova.json",
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        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova"
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        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open"
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      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-sambanova.json",
        "title": "Gemini Developer API vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-sambanova"
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        "json": "https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.json",
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        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.json",
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        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova"
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        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api.json",
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        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api"
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        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openrouter.json",
        "title": "Muse Spark Open vs OpenRouter",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-openrouter"
      },
      {
        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-prism-inference.json",
        "title": "Muse Spark Open vs Prism Inference",
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        "title": "Muse Spark Open vs RouterPlus",
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        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.json",
        "title": "Muse Spark Open vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow"
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        "json": "https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api.json",
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        "url": "https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api"
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        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-sambanova.json",
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    "scores": [
      {
        "by": 43,
        "edge": "sambanova",
        "key": "reliability",
        "muse-spark-open": 42,
        "name": "Reliability",
        "sambanova": 85,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 20,
        "edge": "sambanova",
        "key": "schema",
        "muse-spark-open": 61,
        "name": "Schema \u0026 documentation",
        "sambanova": 81,
        "weight": 13
      },
      {
        "by": 2,
        "edge": "muse-spark-open",
        "key": "ergonomics",
        "muse-spark-open": 69,
        "name": "Agent ergonomics",
        "sambanova": 67,
        "weight": 13
      },
      {
        "by": 14,
        "edge": "sambanova",
        "key": "security",
        "muse-spark-open": 44,
        "name": "Security \u0026 auth",
        "sambanova": 58,
        "weight": 14
      },
      {
        "by": 10,
        "edge": "muse-spark-open",
        "key": "payments",
        "muse-spark-open": 50,
        "name": "Payments \u0026 pricing",
        "sambanova": 40,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 17,
        "edge": "sambanova",
        "key": "maintenance",
        "muse-spark-open": 60,
        "name": "Maintenance \u0026 community",
        "sambanova": 77,
        "weight": 7
      },
      {
        "by": 10,
        "edge": "sambanova",
        "key": "transparency",
        "muse-spark-open": 53,
        "name": "Transparency \u0026 trust",
        "sambanova": 63,
        "weight": 7
      }
    ],
    "summary": "SambaCloud scores 66.4 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing. Both do llm inference.",
    "verdicts": {
      "muse-spark-open": "Muse Spark Open runs on the owner's hardware in seven runtimes, with OpenAI-compatible servers in vLLM and SGLang, standard tool calls, a 1M-token context and Meta's own serving docs. Serving the 537 GB NVFP4 checkpoint takes four B300 GPUs, Meta's download is gated by manual review, and the licence adds attribution and a revenue threshold for model resellers.",
      "sambanova": "Per-token prices and the model list are readable without a key at `/v1/models`, and a free tier needs no card. Production models get two to three weeks' notice before removal, 13 model ids left between March and June 2026, and the docs disagree with the live catalogue on MiniMax-M2.7."
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  "markdown": "SambaCloud scores 66.4 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing. Both do llm inference.\n\n- Muse Spark Open: grade D, 53.4/100, rank #760 of 1095. Markdown https://www.anchorterminal.com/tools/muse-spark-open.md · JSON https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json\n- SambaCloud: grade B, 66.4/100, rank #313 of 1095. Markdown https://www.anchorterminal.com/tools/sambanova.md · JSON https://www.anchorterminal.com/api/v1/tools/sambanova.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 210 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Muse Spark Open (D)\n\nGood for: A team with a four-GPU Blackwell node, or two to four Mac Studios, that wants a 1M-token multimodal coding and agent model on its own hardware with no prompts leaving it.\n\nAhead on:\n- Payments \u0026 pricing, 50 against 40\n\nAlso in its favour:\n- No key needed to call it\n\nWatch for: The NVFP4 checkpoint (about 537 GB) serves on four B300 GPUs and the BF16 one (about 1.65 TB) on eight\n\n### SambaCloud (B)\n\nGood for: Agents that want open-weight models behind an OpenAI or Anthropic client with a free start and prices an agent can read from the API.\n\nAhead on:\n- Reliability, 85 against 42\n- Schema \u0026 documentation, 81 against 61\n- Security \u0026 auth, 58 against 44\n- Maintenance \u0026 community, 77 against 60\n- Transparency \u0026 trust, 63 against 53\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n- Free to start without a card\n\nWatch for: Production models get a notice of two to three weeks, and 13 model ids were removed between 9 March and 9 June 2026\n\n\n## Score by category\n\n| Category | Weight | Muse Spark Open | SambaCloud | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 42 | 85 | SambaCloud +43 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 61 | 81 | SambaCloud +20 |\n| Agent ergonomics | 13% (16.2 this run) | 69 | 67 | Muse Spark Open +2 |\n| Security \u0026 auth | 14% (17.5 this run) | 44 | 58 | SambaCloud +14 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 50 | 40 | Muse Spark Open +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 60 | 77 | SambaCloud +17 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 53 | 63 | SambaCloud +10 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **53.4 · D** | **66.4 · B** | |\n\n## Facts side by side\n\n| Fact | Muse Spark Open | SambaCloud |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Meta | SambaNova Systems, Inc. |\n| Hosted endpoint | no (local only) | `https://api.sambanova.ai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | None | API key |\n| Pricing | Free | Freemium |\n| x402 | no | no |\n| Licence | Muse Model Licence (source-available weights, not an OSI licence), free of charge with an attribution notice, a separate agreement with Meta before Model as a Service by a licensee group above $20M gross revenue, and the Muse Spark Open Usage Policy | Proprietary service under the SambaCloud Terms of Service. The SDKs and the OpenAPI document are Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-15 | 2026-09-17 |\n| Terms last updated |  | no date given |\n| Privacy policy last updated | no document linked | 2023-05-27 |\n| Customer content may train models |  | not found in the text |\n| Terms restrict automated access |  | not found in the text |\n| Terms restrict benchmarking |  | yes |\n| Terms or service can change without notice |  | not found in the text |\n| Arbitration or class-action waiver |  | not found in the text |\n| Popularity | none | 2 stars, 76 npm/wk, 6.1k PyPI/wk |\n\n## Verdicts\n\n**Muse Spark Open.** Muse Spark Open runs on the owner's hardware in seven runtimes, with OpenAI-compatible servers in vLLM and SGLang, standard tool calls, a 1M-token context and Meta's own serving docs. Serving the 537 GB NVFP4 checkpoint takes four B300 GPUs, Meta's download is gated by manual review, and the licence adds attribution and a revenue threshold for model resellers.\n\n**SambaCloud.** Per-token prices and the model list are readable without a key at `/v1/models`, and a free tier needs no card. Production models get two to three weeks' notice before removal, 13 model ids left between March and June 2026, and the docs disagree with the live catalogue on MiniMax-M2.7.\n\n## Before you call either\n\n### Muse Spark Open\n\n1. Start vLLM or SGLang with `--reasoning-parser muse --tool-call-parser muse` (vLLM also `--enable-auto-tool-choice`), or tool calls come back as raw text\n2. Set `reasoning_effort` to `low` or `medium` for short tasks. The default is `xhigh`, reasoning can't be turned off, and other values return an error\n3. Stop only on `\u003c|eot|\u003e` and end of text. Stopping on `\u003c|eom|\u003e` cuts off tool calls and final answers\n4. Stream long generations and leave `max_tokens` room for reasoning, or `content` can come back empty with `finish_reason` `length`\n5. Don't call Meta Model API for this model. Use a self-hosted server or a hosted provider's model string, such as `meta-models/muse-spark-open`\n\n### SambaCloud\n\n1. Call `GET https://api.sambanova.ai/v1/models` at start-up and use only ids it returns. The docs name models the endpoint no longer lists\n2. Read `x-ratelimit-remaining-requests` and `x-ratelimit-remaining-requests-day` on every response. The free tier allows 20 requests a day per model\n3. Treat 429 `queue_full` and 503 `maintenance` as retryable after a delay, and 410 `model_deprecated` as a signal to change model\n4. Validate JSON output yourself. Schema enforcement is best effort and `strict: true` changes nothing\n5. Check `max_completion_tokens` per model. DeepSeek-V3.1 caps output at 7,168 tokens and Llama 3.3 70B at 3,072\n\n## Questions\n\n### Which is better for AI agents, Muse Spark Open or SambaCloud?\n\nSambaCloud scores 66.4 (B) on agent readiness against Muse Spark Open's 53.4 (D), and leads in 5 of 7 scored categories. Muse Spark Open leads on payments \u0026 pricing.\n\n### Do Muse Spark Open and SambaCloud need an API key?\n\nMuse Spark Open needs no key. SambaCloud needs an API key.\n\n### Can an agent call Muse Spark Open and SambaCloud without installing anything?\n\nNo hosted endpoint is listed for Muse Spark Open. SambaCloud has a hosted endpoint at https://api.sambanova.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova.json, and with the fewest tokens: https://www.anchorterminal.com/compare/muse-spark-open-vs-sambanova.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"muse-spark-open\", \"b\": \"sambanova\"}`. From a terminal: `anchor compare muse-spark-open sambanova`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/muse-spark-open.json and https://www.anchorterminal.com/api/v1/tools/sambanova.json\n\n## Other comparisons with Muse Spark Open or SambaCloud\n\n- [Claude API vs Muse Spark Open](https://www.anchorterminal.com/compare/anthropic-api-vs-muse-spark-open.md)\n- [Claude API vs SambaCloud](https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova.md)\n- [Antseed vs Muse Spark Open](https://www.anchorterminal.com/compare/antseed-vs-muse-spark-open.md)\n- [Antseed vs SambaCloud](https://www.anchorterminal.com/compare/antseed-vs-sambanova.md)\n- [BlockRun.AI vs Muse Spark Open](https://www.anchorterminal.com/compare/blockrun-ai-vs-muse-spark-open.md)\n- [BlockRun.AI vs SambaCloud](https://www.anchorterminal.com/compare/blockrun-ai-vs-sambanova.md)\n- [Cloudflare AI Gateway vs Muse Spark Open](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-muse-spark-open.md)\n- [Cloudflare AI Gateway vs SambaCloud](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-sambanova.md)\n- [Cloudflare Workers AI vs Muse Spark Open](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-muse-spark-open.md)\n- [Cloudflare Workers AI vs SambaCloud](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-sambanova.md)\n- [Cohere Chat API (Command models) vs Muse Spark Open](https://www.anchorterminal.com/compare/cohere-chat-vs-muse-spark-open.md)\n- [Cohere Chat API (Command models) vs SambaCloud](https://www.anchorterminal.com/compare/cohere-chat-vs-sambanova.md)\n- [DeepInfra vs Muse Spark Open](https://www.anchorterminal.com/compare/deepinfra-vs-muse-spark-open.md)\n- [DeepInfra vs SambaCloud](https://www.anchorterminal.com/compare/deepinfra-vs-sambanova.md)\n- [DeepSeek API vs Muse Spark Open](https://www.anchorterminal.com/compare/deepseek-api-vs-muse-spark-open.md)\n- [DeepSeek API vs SambaCloud](https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova.md)\n- [Gemini Developer API vs Muse Spark Open](https://www.anchorterminal.com/compare/gemini-api-vs-muse-spark-open.md)\n- [Gemini Developer API vs SambaCloud](https://www.anchorterminal.com/compare/gemini-api-vs-sambanova.md)\n- [GroqCloud vs Muse Spark Open](https://www.anchorterminal.com/compare/groq-vs-muse-spark-open.md)\n- [GroqCloud vs SambaCloud](https://www.anchorterminal.com/compare/groq-vs-sambanova.md)\n- [Meta Model API vs Muse Spark Open](https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.md)\n- [Meta Model API vs SambaCloud](https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.md)\n- [Mistral AI API vs Muse Spark Open](https://www.anchorterminal.com/compare/mistral-api-vs-muse-spark-open.md)\n- [Mistral AI API vs SambaCloud](https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.md)\n- [Muse Spark Open vs Novita AI](https://www.anchorterminal.com/compare/muse-spark-open-vs-novita-ai.md)\n- [Muse Spark Open vs OpenAI API](https://www.anchorterminal.com/compare/muse-spark-open-vs-openai-api.md)\n- [Muse Spark Open vs OpenRouter](https://www.anchorterminal.com/compare/muse-spark-open-vs-openrouter.md)\n- [Muse Spark Open vs Prism Inference](https://www.anchorterminal.com/compare/muse-spark-open-vs-prism-inference.md)\n- [Muse Spark Open vs RouterPlus](https://www.anchorterminal.com/compare/muse-spark-open-vs-routerplus.md)\n- [Muse Spark Open vs SiliconFlow](https://www.anchorterminal.com/compare/muse-spark-open-vs-siliconflow.md)\n- [Muse Spark Open vs StepFun API](https://www.anchorterminal.com/compare/muse-spark-open-vs-stepfun-api.md)\n- [Novita AI vs SambaCloud](https://www.anchorterminal.com/compare/novita-ai-vs-sambanova.md)\n- [OpenAI API vs SambaCloud](https://www.anchorterminal.com/compare/openai-api-vs-sambanova.md)\n- [OpenRouter vs SambaCloud](https://www.anchorterminal.com/compare/openrouter-vs-sambanova.md)\n- [RouterPlus vs SambaCloud](https://www.anchorterminal.com/compare/routerplus-vs-sambanova.md)\n- [SambaCloud vs SiliconFlow](https://www.anchorterminal.com/compare/sambanova-vs-siliconflow.md)\n- [SambaCloud vs StepFun API](https://www.anchorterminal.com/compare/sambanova-vs-stepfun-api.md)\n- [Prism Inference vs SambaCloud](https://www.anchorterminal.com/compare/prism-inference-vs-sambanova.md)\n",
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