{
  "data": {
    "a": {
      "slug": "meta-model-api",
      "name": "Meta Model API",
      "vendor": "Meta",
      "vendorUrl": "https://dev.meta.ai",
      "kind": "model",
      "category": "inference",
      "summary": "Meta Model API is Meta's pay-as-you-go API for its hosted Muse models, including Muse Wonder and Muse Spark, through OpenAI-style Responses and Chat Completions endpoints and an Anthropic-style Messages endpoint, plus image, speech and segmentation routes.",
      "url": "https://www.anchorterminal.com/tools/meta-model-api",
      "markdownUrl": "https://www.anchorterminal.com/tools/meta-model-api.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/meta-model-api.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/meta-model-api.json",
      "license": "Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party.",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.meta.ai/v1",
      "packages": [],
      "auth": "api-key",
      "authNotes": "A bearer API key created on the API keys tab of the Model API dashboard after a browser sign-up with email, mobile number, Facebook, Google or GitHub. Keys belong to a team, are shown once and are revoked by deletion. No key scopes were found, and every key on a team shares the team's rate limits.",
      "pricing": "usage",
      "pricingNotes": "Muse Wonder is $4.00 per million input tokens, $0.20 cached and $20.00 per million output tokens, Standard mode only (checked 2026-10-12). Muse Spark is $1.25, $0.15 and $4.25, or $0.10, $0.002 and $0.20 in Contributor mode, where Meta may train on the content. Billed in arrears to a card. No free allowance was found.",
      "priceSummary": "$2.50 / 1k req",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in dev.meta.ai/llms.txt, the pricing page, the API reference or the billing help pages, checked 12 October 2026. Usage is charged to a card at a payment threshold or on the 1st of each month.",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-12"
      },
      "docsUrl": "https://dev.meta.ai/docs/overview",
      "llmsTxt": "https://dev.meta.ai/llms.txt",
      "capabilities": [
        "inference.llm",
        "image.generate",
        "image.edit",
        "speech.stt",
        "speech.streaming"
      ],
      "tags": [
        "official",
        "hosted",
        "model",
        "usage-priced",
        "closed-source",
        "llms-txt",
        "multimodal",
        "streaming",
        "openai-compatible",
        "anthropic-compatible",
        "card-required"
      ],
      "lastRelease": "2026-10-12",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 52.2,
        "grade": "D",
        "agentReady": false,
        "rank": 757,
        "ranked": true,
        "rankOf": 993,
        "categoryRank": 16,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 75,
          "maintenance": 46,
          "payments": 20,
          "reliability": 40,
          "schema": 60,
          "security": 64,
          "transparency": 52
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-12"
        },
        "negative": 0,
        "verdict": "Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.",
        "bestFor": "Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.",
        "strengths": [
          "Muse Wonder and Muse Spark take text, image, video, audio and PDF input with a 1,048,576-token context window",
          "Per-token prices, per-model rate limits and rate-limit headers published without a login",
          "Content sent in Standard mode is not used to train Meta models, and training use is opt-in through `-contributor` model IDs",
          "Responses, Chat Completions and Messages endpoints, so the OpenAI and Anthropic SDKs work with a base-URL change",
          "llms.txt and a Markdown copy of every docs page, with an error guide that gives the Retry-After value for each retryable error"
        ],
        "weaknesses": [
          "Muse Wonder is labelled a preview, and no deprecation policy or notice period was found",
          "No free API allowance found, and billing is set up with a card",
          "No status page with history. The docs' status link redirects to the home page, and `/v1/status` reports only the current state",
          "`tool_choice` accepts only `auto`, so a call can't be forced or ruled out",
          "No OpenAPI file, batch endpoint or Model API changelog found, and API keys have no scopes"
        ],
        "agentNotes": [
          "Use `muse-wonder-1.0` for long multi-step work and `muse-spark-1.3` for cheaper, high-volume calls. Both take the same requests",
          "Keep personal or confidential data away from `-contributor` model IDs. Meta may train on that content",
          "Honour Retry-After on 429 and 503, which is 60 seconds for `service_overloaded`, and check `GET https://api.meta.ai/v1/status`, which needs no key",
          "Pass the key to the OpenAI SDK explicitly or set `OPENAI_API_KEY`. The SDK doesn't read `MODEL_API_KEY`",
          "Leave `tool_choice` at `auto`. The docs say `none` and `required` are not supported"
        ],
        "metrics": {
          "kind": "remote",
          "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": 52.2
          }
        ],
        "editorialScores": {
          "ergonomics": 75,
          "maintenance": 46,
          "payments": 20,
          "reliability": 40,
          "schema": 60,
          "security": 64,
          "transparency": 41
        },
        "provenanceScore": 63
      },
      "connect": {
        "http": "curl -X POST \"https://api.meta.ai/v1/responses\" \\\n  -H \"Authorization: Bearer $MODEL_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\"model\": \"muse-spark-1.3\", \"input\": \"What is the capital of France?\"}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/meta-model-api"
      },
      "sameCompany": [
        "muse-code"
      ],
      "area": "models",
      "unitPrices": [
        {
          "item": "Muse Wonder input",
          "unit": "1m-tokens",
          "usd": 4,
          "note": "Standard mode, muse-wonder-1.0. No long-context premium."
        },
        {
          "item": "Muse Wonder cached input",
          "unit": "1m-tokens",
          "usd": 0.2
        },
        {
          "item": "Muse Wonder output",
          "unit": "1m-tokens",
          "usd": 20
        },
        {
          "item": "Muse Spark input",
          "unit": "1m-tokens",
          "usd": 1.25,
          "note": "Standard mode, muse-spark-1.3, 1.2 and 1.1."
        },
        {
          "item": "Muse Spark cached input",
          "unit": "1m-tokens",
          "usd": 0.15
        },
        {
          "item": "Muse Spark output",
          "unit": "1m-tokens",
          "usd": 4.25
        },
        {
          "item": "Muse Spark input, Contributor mode",
          "unit": "1m-tokens",
          "usd": 0.1,
          "note": "Meta may use the content to train its models."
        },
        {
          "item": "Muse Spark output, Contributor mode",
          "unit": "1m-tokens",
          "usd": 0.2,
          "note": "Cached input is $0.002 per million tokens."
        },
        {
          "item": "Web search grounding",
          "unit": "1k-requests",
          "usd": 2.5,
          "note": "Per 1,000 search queries, on top of token cost."
        },
        {
          "item": "Muse Image generated image",
          "unit": "image",
          "usd": 0.01
        }
      ],
      "provenance": {
        "legalEntity": "Meta Platforms, Inc.",
        "domain": "meta.ai",
        "domainRegistered": "2017-12-16",
        "endpointOnVendorDomain": true,
        "terms": "https://dev.meta.ai/legal/terms-of-service",
        "privacy": "https://www.facebook.com/privacy/policy/",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-12",
        "notes": [
          "The terms (last updated 9 October 2026) are an agreement with Meta Platforms, Inc., or Meta Platforms Ireland Limited for users in the European Region. The model card names the same two.",
          "The privacy field is the Meta Privacy Policy, which the terms link. www.facebook.com's robots.txt asks readers like ours not to fetch it, as the 8 October policy reading records, so it wasn't read. The terms also link a subprocessor list at forwork.meta.com/legal/mfw-subprocessor-list/ and the Meta Global Processor Terms, neither of which was read.",
          "RDAP for meta.ai gives a registration date of 16 December 2017. The API answers at api.meta.ai.",
          "No status page. The error guide links dev.meta.ai/status, which redirects to the home page. `GET /v1/status` is an unauthenticated health endpoint with no history.",
          "No Model API changelog was found. The only changelog on dev.meta.ai is Muse Code's.",
          "dev.meta.ai/.well-known/security.txt returns 404. www.meta.ai's robots.txt disallows ClaudeBot, so its security.txt wasn't requested. www.facebook.com/.well-known/security.txt is valid until 11 November 2026 and points to bugbounty.meta.com.",
          "developer.meta.com/ai/ redirects to dev.meta.ai."
        ],
        "score": 63
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/meta-model-api.json",
      "live": {
        "slug": "meta-model-api",
        "probe": {
          "target": "https://api.meta.ai/v1",
          "method": "get",
          "lastAt": "2026-10-12T22:35:32.230718004Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 115,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 87,
          "p95ms24h": 166,
          "samples24h": 19,
          "samples30d": 19,
          "days": [
            {
              "date": "2026-10-12",
              "probes": 19,
              "ok": 19
            }
          ]
        },
        "updatedAt": "2026-10-12T22:35:32.230718004Z"
      }
    },
    "answer": "SambaCloud scores 66.4 (B) on agent readiness against Meta Model API's 52.2 (D), and leads in 5 of 7 scored categories. Meta Model API leads on agent ergonomics and security \u0026 auth.",
    "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": 302,
        "ranked": true,
        "rankOf": 993,
        "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": "2026-10-12T22:35:39.126321844Z",
          "lastOk": true,
          "lastStatus": 405,
          "lastMs": 392,
          "authRequired": false,
          "uptime24h": 98.79,
          "uptime30d": 99.67,
          "p50ms24h": 385,
          "p95ms24h": 1397,
          "samples24h": 248,
          "samples30d": 896,
          "days": [
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              "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": 233,
              "ok": 230
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.sambanova.ai",
          "indicator": "none",
          "summary": "All Systems Operational",
          "checkedAt": "2026-10-12T22:30:30.358085391Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "sambanova/sambanova-python",
            "version": "v1.13.0",
            "released": "2026-09-17",
            "seenAt": "2026-10-12T22:27:12.537557405Z"
          },
          {
            "registry": "npm",
            "name": "sambanova",
            "version": "1.10.0",
            "seenAt": "2026-10-12T22:27:10.722025299Z"
          },
          {
            "registry": "pypi",
            "name": "sambanova",
            "version": "1.13.0",
            "released": "2026-09-17",
            "seenAt": "2026-10-12T22:27:10.534704013Z"
          }
        ],
        "githubStars": 2,
        "npmWeekly": 139,
        "pypiWeekly": 5767,
        "securityTxt": {
          "url": "https://sambanova.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-12T15:43:30.579270022Z"
        },
        "llmsTxt": {
          "url": "https://docs.sambanova.ai/docs/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-12T14:10:01.708681453Z"
        },
        "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": 200,
            "checkedAt": "2026-10-12T19:51:03.43472292Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "2a7de663bfad"
          },
          {
            "url": "https://docs.sambanova.ai/docs/en/models/deprecations",
            "kind": "deprecations",
            "status": 200,
            "checkedAt": "2026-10-12T19:51:00.592981976Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "a16b6d139f6c"
          },
          {
            "url": "https://cloud.sambanova.ai/plans/pricing",
            "kind": "pricing",
            "status": 200,
            "checkedAt": "2026-10-12T19:46:44.897845316Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "71a596d0bd9a"
          },
          {
            "url": "https://sambanova.ai/privacy-policy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-10-12T19:57:52.284189469Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "dcd17eb3af4c"
          },
          {
            "url": "https://sambanova.ai/cloud-end-user-license-agreement",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-12T19:57:50.046990815Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "e1f8368edf9b"
          }
        ],
        "updatedAt": "2026-10-12T22:35:39.126321844Z"
      }
    },
    "facts": [
      {
        "a": "Model API",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Meta",
        "b": "SambaNova Systems, Inc.",
        "name": "Vendor"
      },
      {
        "a": "https://api.meta.ai/v1",
        "b": "https://api.sambanova.ai/v1",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "API key",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Pay per use",
        "b": "Freemium",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party.",
        "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"
      },
      {
        "a": "yes",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-12",
        "b": "2026-09-17",
        "name": "Last release"
      },
      {
        "a": "",
        "b": "no date given",
        "name": "Terms last updated"
      },
      {
        "a": "couldn't be read",
        "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 Meta Model API's 52.2 (D), and leads in 5 of 7 scored categories. Meta Model API leads on agent ergonomics and security \u0026 auth.",
        "question": "Which is better for AI agents, Meta Model API or SambaCloud?"
      },
      {
        "answer": "Both need an API key.",
        "question": "Do Meta Model API and SambaCloud need an API key?"
      },
      {
        "answer": "Yes. Meta Model API has a hosted endpoint at https://api.meta.ai/v1 and SambaCloud at https://api.sambanova.ai/v1.",
        "question": "Can an agent call Meta Model API and SambaCloud without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Agent ergonomics, 75 against 67",
          "Security \u0026 auth, 64 against 58"
        ],
        "also": null,
        "goodFor": "Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.",
        "slug": "meta-model-api",
        "watchFor": "Muse Wonder is labelled a preview, and no deprecation policy or notice period was found"
      },
      {
        "aheadOn": [
          "Reliability, 85 against 40",
          "Schema \u0026 documentation, 81 against 60",
          "Payments \u0026 pricing, 40 against 20",
          "Maintenance \u0026 community, 77 against 46",
          "Transparency \u0026 trust, 63 against 52"
        ],
        "also": [
          "Free to start without a card"
        ],
        "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",
        "watchFor": "Production models get a notice of two to three weeks, and 13 model ids were removed between 9 March and 9 June 2026"
      }
    ],
    "job": {
      "capability": "inference.llm",
      "name": "LLM inference"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.json",
        "title": "Claude API vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova.json",
        "title": "Claude API vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.json",
        "title": "Antseed vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/antseed-vs-sambanova.json",
        "title": "Antseed vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.json",
        "title": "BlockRun.AI vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-sambanova.json",
        "title": "BlockRun.AI vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-meta-model-api.json",
        "title": "Cloudflare AI Gateway vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-sambanova.json",
        "title": "Cloudflare AI Gateway vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api.json",
        "title": "Cloudflare Workers AI vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-sambanova.json",
        "title": "Cloudflare Workers AI vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api.json",
        "title": "Cohere Chat API (Command models) vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-sambanova.json",
        "title": "Cohere Chat API (Command models) vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api.json",
        "title": "DeepInfra vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-sambanova.json",
        "title": "DeepInfra vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.json",
        "title": "DeepSeek API vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova.json",
        "title": "DeepSeek API vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.json",
        "title": "Gemini Developer API vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api"
      },
      {
        "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"
      },
      {
        "json": "https://www.anchorterminal.com/compare/groq-vs-meta-model-api.json",
        "title": "GroqCloud vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/groq-vs-meta-model-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/groq-vs-sambanova.json",
        "title": "GroqCloud vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/groq-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.json",
        "title": "Meta Model API vs Mistral AI API",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai.json",
        "title": "Meta Model API vs Novita AI",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.json",
        "title": "Meta Model API vs OpenAI API",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter.json",
        "title": "Meta Model API vs OpenRouter",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter"
      },
      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-prism-inference.json",
        "title": "Meta Model API vs Prism Inference",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-prism-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.json",
        "title": "Meta Model API vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.json",
        "title": "Meta Model API vs StepFun API",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.json",
        "title": "Mistral AI API vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/mistral-api-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/novita-ai-vs-sambanova.json",
        "title": "Novita AI vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/novita-ai-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/openai-api-vs-sambanova.json",
        "title": "OpenAI API vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/openai-api-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/openrouter-vs-sambanova.json",
        "title": "OpenRouter vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/openrouter-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/sambanova-vs-siliconflow.json",
        "title": "SambaCloud vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/sambanova-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/sambanova-vs-stepfun-api.json",
        "title": "SambaCloud vs StepFun API",
        "url": "https://www.anchorterminal.com/compare/sambanova-vs-stepfun-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/prism-inference-vs-sambanova.json",
        "title": "Prism Inference vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/prism-inference-vs-sambanova"
      }
    ],
    "scores": [
      {
        "by": 45,
        "edge": "sambanova",
        "key": "reliability",
        "meta-model-api": 40,
        "name": "Reliability",
        "sambanova": 85,
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 21,
        "edge": "sambanova",
        "key": "schema",
        "meta-model-api": 60,
        "name": "Schema \u0026 documentation",
        "sambanova": 81,
        "weight": 13
      },
      {
        "by": 8,
        "edge": "meta-model-api",
        "key": "ergonomics",
        "meta-model-api": 75,
        "name": "Agent ergonomics",
        "sambanova": 67,
        "weight": 13
      },
      {
        "by": 6,
        "edge": "meta-model-api",
        "key": "security",
        "meta-model-api": 64,
        "name": "Security \u0026 auth",
        "sambanova": 58,
        "weight": 14
      },
      {
        "by": 20,
        "edge": "sambanova",
        "key": "payments",
        "meta-model-api": 20,
        "name": "Payments \u0026 pricing",
        "sambanova": 40,
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 31,
        "edge": "sambanova",
        "key": "maintenance",
        "meta-model-api": 46,
        "name": "Maintenance \u0026 community",
        "sambanova": 77,
        "weight": 7
      },
      {
        "by": 11,
        "edge": "sambanova",
        "key": "transparency",
        "meta-model-api": 52,
        "name": "Transparency \u0026 trust",
        "sambanova": 63,
        "weight": 7
      }
    ],
    "summary": "SambaCloud scores 66.4 (B) on agent readiness against Meta Model API's 52.2 (D), and leads in 5 of 7 scored categories. Meta Model API leads on agent ergonomics and security \u0026 auth. Both do llm inference.",
    "verdicts": {
      "meta-model-api": "Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.",
      "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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  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova",
    "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.md",
    "slim": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.min.md"
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  "markdown": "SambaCloud scores 66.4 (B) on agent readiness against Meta Model API's 52.2 (D), and leads in 5 of 7 scored categories. Meta Model API leads on agent ergonomics and security \u0026 auth. Both do llm inference.\n\n- Meta Model API: grade D, 52.2/100, rank #757 of 993. Markdown https://www.anchorterminal.com/tools/meta-model-api.md · JSON https://www.anchorterminal.com/api/v1/tools/meta-model-api.json\n- SambaCloud: grade B, 66.4/100, rank #302 of 993. 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 171 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Meta Model API (D)\n\nGood for: Long-running agent and coding work over text, images, video, audio and PDFs with a 1M-token context, where training must stay off by default.\n\nAhead on:\n- Agent ergonomics, 75 against 67\n- Security \u0026 auth, 64 against 58\n\nWatch for: Muse Wonder is labelled a preview, and no deprecation policy or notice period was found\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 40\n- Schema \u0026 documentation, 81 against 60\n- Payments \u0026 pricing, 40 against 20\n- Maintenance \u0026 community, 77 against 46\n- Transparency \u0026 trust, 63 against 52\n\nAlso in its favour:\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 | Meta Model API | SambaCloud | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 40 | 85 | SambaCloud +45 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 60 | 81 | SambaCloud +21 |\n| Agent ergonomics | 13% (16.2 this run) | 75 | 67 | Meta Model API +8 |\n| Security \u0026 auth | 14% (17.5 this run) | 64 | 58 | Meta Model API +6 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 40 | SambaCloud +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 46 | 77 | SambaCloud +31 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 52 | 63 | SambaCloud +11 |\n| Negative events | ≤15 | 0 | -2 | |\n| **Total** | | **52.2 · D** | **66.4 · B** | |\n\n## Facts side by side\n\n| Fact | Meta Model API | SambaCloud |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Meta | SambaNova Systems, Inc. |\n| Hosted endpoint | `https://api.meta.ai/v1` | `https://api.sambanova.ai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | API key | API key |\n| Pricing | Pay per use | Freemium |\n| x402 | no | no |\n| Licence | Closed service under the Meta Model API Terms of Service (last updated 9 October 2026), with Meta Platforms, Inc., or Meta Platforms Ireland Limited in the European Region, as the contracting party. | 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 | 2026-10-12 | 2026-09-17 |\n| Terms last updated |  | no date given |\n| Privacy policy last updated | couldn't be read | 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**Meta Model API.** Meta Model API serves Muse Wonder, in preview since 12 October 2026, and Muse Spark with 1M-token context, constrained JSON Schema output, automatic prompt caching and per-token prices published without a login. Standard-mode content is not used for training. There's no free allowance, status history, OpenAPI file, deprecation policy or way to force a tool call.\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### Meta Model API\n\n1. Use `muse-wonder-1.0` for long multi-step work and `muse-spark-1.3` for cheaper, high-volume calls. Both take the same requests\n2. Keep personal or confidential data away from `-contributor` model IDs. Meta may train on that content\n3. Honour Retry-After on 429 and 503, which is 60 seconds for `service_overloaded`, and check `GET https://api.meta.ai/v1/status`, which needs no key\n4. Pass the key to the OpenAI SDK explicitly or set `OPENAI_API_KEY`. The SDK doesn't read `MODEL_API_KEY`\n5. Leave `tool_choice` at `auto`. The docs say `none` and `required` are not supported\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, Meta Model API or SambaCloud?\n\nSambaCloud scores 66.4 (B) on agent readiness against Meta Model API's 52.2 (D), and leads in 5 of 7 scored categories. Meta Model API leads on agent ergonomics and security \u0026 auth.\n\n### Do Meta Model API and SambaCloud need an API key?\n\nBoth need an API key.\n\n### Can an agent call Meta Model API and SambaCloud without installing anything?\n\nYes. Meta Model API has a hosted endpoint at https://api.meta.ai/v1 and SambaCloud at https://api.sambanova.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.json, and with the fewest tokens: https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"meta-model-api\", \"b\": \"sambanova\"}`. From a terminal: `anchor compare meta-model-api sambanova`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/meta-model-api.json and https://www.anchorterminal.com/api/v1/tools/sambanova.json\n\n## Other comparisons with Meta Model API or SambaCloud\n\n- [Claude API vs Meta Model API](https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.md)\n- [Claude API vs SambaCloud](https://www.anchorterminal.com/compare/anthropic-api-vs-sambanova.md)\n- [Antseed vs Meta Model API](https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.md)\n- [Antseed vs SambaCloud](https://www.anchorterminal.com/compare/antseed-vs-sambanova.md)\n- [BlockRun.AI vs Meta Model API](https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.md)\n- [BlockRun.AI vs SambaCloud](https://www.anchorterminal.com/compare/blockrun-ai-vs-sambanova.md)\n- [Cloudflare AI Gateway vs Meta Model API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-meta-model-api.md)\n- [Cloudflare AI Gateway vs SambaCloud](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-sambanova.md)\n- [Cloudflare Workers AI vs Meta Model API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api.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 Meta Model API](https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api.md)\n- [Cohere Chat API (Command models) vs SambaCloud](https://www.anchorterminal.com/compare/cohere-chat-vs-sambanova.md)\n- [DeepInfra vs Meta Model API](https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api.md)\n- [DeepInfra vs SambaCloud](https://www.anchorterminal.com/compare/deepinfra-vs-sambanova.md)\n- [DeepSeek API vs Meta Model API](https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.md)\n- [DeepSeek API vs SambaCloud](https://www.anchorterminal.com/compare/deepseek-api-vs-sambanova.md)\n- [Gemini Developer API vs Meta Model API](https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.md)\n- [Gemini Developer API vs SambaCloud](https://www.anchorterminal.com/compare/gemini-api-vs-sambanova.md)\n- [GroqCloud vs Meta Model API](https://www.anchorterminal.com/compare/groq-vs-meta-model-api.md)\n- [GroqCloud vs SambaCloud](https://www.anchorterminal.com/compare/groq-vs-sambanova.md)\n- [Meta Model API vs Mistral AI API](https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.md)\n- [Meta Model API vs Novita AI](https://www.anchorterminal.com/compare/meta-model-api-vs-novita-ai.md)\n- [Meta Model API vs OpenAI API](https://www.anchorterminal.com/compare/meta-model-api-vs-openai-api.md)\n- [Meta Model API vs OpenRouter](https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter.md)\n- [Meta Model API vs Prism Inference](https://www.anchorterminal.com/compare/meta-model-api-vs-prism-inference.md)\n- [Meta Model API vs SiliconFlow](https://www.anchorterminal.com/compare/meta-model-api-vs-siliconflow.md)\n- [Meta Model API vs StepFun API](https://www.anchorterminal.com/compare/meta-model-api-vs-stepfun-api.md)\n- [Mistral AI API vs SambaCloud](https://www.anchorterminal.com/compare/mistral-api-vs-sambanova.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- [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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