{
  "data": {
    "a": {
      "slug": "jais-3",
      "name": "Jais 3",
      "vendor": "Institute of Foundation Models (MBZUAI) and Inception42",
      "vendorUrl": "https://ifm.ai/blog/jais3/",
      "kind": "model",
      "category": "inference",
      "summary": "Jais 3 is an open-weight family of Arabic and English reasoning models from MBZUAI's Institute of Foundation Models and Inception42, from 0.9B to 375B parameters with up to 512K tokens of context, released under Apache-2.0 for self-hosting.",
      "url": "https://www.anchorterminal.com/tools/jais-3",
      "markdownUrl": "https://www.anchorterminal.com/tools/jais-3.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/jais-3.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/jais-3.json",
      "repo": "https://huggingface.co/inception42/Jais-3-375B-A23B",
      "license": "Apache-2.0, declared in the metadata of every model card read. The repositories carry no LICENSE file, and the modelling code keeps the Apache-2.0 header of the Qwen3-MoE code it was generated from",
      "transports": [
        "http"
      ],
      "packages": [],
      "auth": "none",
      "authNotes": "No account or key. The inception42 and IFM repositories on Hugging Face are not gated and download anonymously. A local server has whatever authentication the owner adds, such as vLLM's `--api-key`. The cards' examples call the local server with `api_key=\"EMPTY\"`.",
      "pricing": "free",
      "pricingNotes": "Free to download and run under Apache-2.0, with the owner's GPUs as the cost. No hosted endpoint from IFM or Inception42 was found, OpenRouter lists no Jais model, and Hugging Face shows no inference provider for the main repositories (checked 2026-10-17).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402. Jais 3 is a set of weights the owner serves, with no payment route and no hosted API from the makers found (checked 2026-10-17).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-17"
      },
      "docsUrl": "https://huggingface.co/inception42/Jais-3-375B-A23B",
      "capabilities": [
        "inference.llm",
        "inference.open-weights",
        "inference.local"
      ],
      "tags": [
        "model",
        "open-weights",
        "self-hosted",
        "local",
        "free",
        "no-card",
        "apache-2.0",
        "openai-compatible",
        "gpu",
        "apple-silicon",
        "mlx",
        "new"
      ],
      "lastRelease": "2026-10-15",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 51.7,
        "grade": "D",
        "agentReady": false,
        "rank": 839,
        "ranked": true,
        "rankOf": 1133,
        "categoryRank": 21,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 65,
          "maintenance": 62,
          "payments": 60,
          "reliability": 48,
          "schema": 54,
          "security": 31,
          "transparency": 50
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-17"
        },
        "negative": 0,
        "verdict": "Jais 3 runs on the owner's hardware through OpenAI-compatible servers in vLLM and SGLang, with tool calls, three reasoning levels and a 512K context, from a 2.2 GB 0.9B model to a 758 GB 375B one. The weights download without sign-up under Apache-2.0, but every launch command trusts remote code, and no technical report or security contact is published.",
        "bestFor": "An agent or team that needs Arabic and English reasoning and tool use on its own hardware, from a laptop-sized 0.9B to a cluster-sized 375B, under Apache-2.0.",
        "strengths": [
          "Six checkpoints from 0.9B (2.2 GB) to 375B-A23B (758 GB), with FP8, GGUF and MLX builds from IFM",
          "Apache-2.0 on every card read, ungated downloads, and the CPT, Cooldown, SFT and FTPO training checkpoints published as branches",
          "With the `k2_horizon` parsers, reasoning returns in `reasoning_content` and tool calls as `tool_calls`, in JSON, XML or typed XML formats",
          "Launch recipes in the vLLM and SGLang projects' own docs, and K2 Horizon support merged into llama.cpp's master branch",
          "The chat template validates tool schemas and rejects unknown options with named errors, such as an unsupported `reasoning_effort`"
        ],
        "weaknesses": [
          "Every documented vLLM, SGLang, Transformers and MLX command passes `--trust-remote-code`, so the repository's Python runs on the host",
          "The 375B-A23B reference deployment is 16 H100 GPUs across two nodes, or one 8-GPU H200 node",
          "The technical report and code repository are marked 'coming soon', and IFM's own blog and press release sit behind a bot check",
          "No LICENSE file in the repositories, no changelog, no deprecation policy and no security contact or security.txt found",
          "Released on 15 October 2026, with template fixes on 14 and 15 October, and mlx-lm doesn't yet parse its reasoning or tool calls"
        ],
        "agentNotes": [
          "Start vLLM or SGLang with `--reasoning-parser k2_horizon`, and add `--tool-call-parser k2_horizon` (vLLM also `--enable-auto-tool-choice`) for tools, or tool calls come back as raw text",
          "Pass `reasoning_effort` (`high`, `medium` or `low`) and `tool_call_format` inside `chat_template_kwargs`. Other values return a template error",
          "Send each earlier assistant turn back with `reasoning_content` as a string, even an empty one. A missing or null thinking field makes the template raise an error",
          "Send your own system message, or set `default_system_prompt` to an empty string. Without one the template inserts an identity prompt naming IFM, Inception42 and Cerebras",
          "Budget at least 32,768 output tokens at `high` effort, which the cards recommend for every request"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "D",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 51.7
          }
        ],
        "editorialScores": {
          "ergonomics": 65,
          "maintenance": 62,
          "payments": 60,
          "reliability": 48,
          "schema": 54,
          "security": 31,
          "transparency": 51
        },
        "provenanceScore": 49
      },
      "connect": {
        "install": "vllm serve inception42/Jais-3-32B \\\n  --trust-remote-code \\\n  --dtype bfloat16 \\\n  --tensor-parallel-size 2 \\\n  --reasoning-parser k2_horizon \\\n  --enable-auto-tool-choice \\\n  --tool-call-parser k2_horizon",
        "http": "curl http://localhost:8000/v1/chat/completions \\\n  -H 'Content-Type: application/json' \\\n  -d '{\n    \"model\": \"inception42/Jais-3-32B\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Summarise this contract in Arabic.\"}],\n    \"max_tokens\": 32768,\n    \"chat_template_kwargs\": {\"reasoning_effort\": \"high\"}\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/jais-3"
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Mohamed bin Zayed University of Artificial Intelligence (Institute of Foundation Models), with Inception42 (a G42 company)",
        "domain": "ifm.ai",
        "domainRegistered": "2022-09-06",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-17",
        "notes": [
          "The chat template's default system prompt names the Institute of Foundation Models (IFM) at MBZUAI, with Inception42 (a G42 company) and Cerebras, and gives MBZUAI's Arabic name, Mohamed bin Zayed University of Artificial Intelligence. The citation names the IFM, Inception42 and Cerebras teams. No registered company name for Inception42 was read first-hand.",
          "RDAP gives a registration date of 6 September 2022 for ifm.ai. The weights are on huggingface.co under the inception42 and IFM organisations.",
          "The licence is Apache-2.0 in each card's metadata. There is no LICENSE file and no terms or privacy document governing the weights, and no input reaches the makers when the owner serves them.",
          "ifm.ai answered our reader with a Cloudflare bot check on the press release, the blog post and the sitemap, so they weren't read. inceptionai.ai and mbzuai.ac.ae answered with bot or firewall pages too. ifm.ai/.well-known/security.txt returned 404 on 17 October 2026.",
          "No hosted endpoint, so no status page. No changelog. The Hugging Face commit history is public and was read."
        ],
        "score": 49
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/jais-3.json"
    },
    "answer": "Meta Model API and Jais 3 score within a point of each other on agent readiness, 52.2 (D) and 51.7 (D). Jais 3 leads on reliability, payments \u0026 pricing and maintenance \u0026 community.",
    "b": {
      "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": 828,
        "ranked": true,
        "rankOf": 1133,
        "categoryRank": 20,
        "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-spark-open",
        "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": "2026-10-18T00:14:47.345322926Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 70,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 68,
          "p95ms24h": 157,
          "samples24h": 253,
          "samples30d": 1291,
          "days": [
            {
              "date": "2026-10-12",
              "probes": 33,
              "ok": 33
            },
            {
              "date": "2026-10-13",
              "probes": 248,
              "ok": 248
            },
            {
              "date": "2026-10-14",
              "probes": 249,
              "ok": 249
            },
            {
              "date": "2026-10-15",
              "probes": 253,
              "ok": 253
            },
            {
              "date": "2026-10-16",
              "probes": 252,
              "ok": 252
            },
            {
              "date": "2026-10-17",
              "probes": 253,
              "ok": 253
            },
            {
              "date": "2026-10-18",
              "probes": 3,
              "ok": 3
            }
          ]
        },
        "securityTxt": {
          "url": "https://meta.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-17T15:52:13.77313756Z"
        },
        "llmsTxt": {
          "url": "https://dev.meta.ai/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-17T14:22:33.598652002Z"
        },
        "pages": [
          {
            "url": "https://dev.meta.ai/legal/terms-of-service",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-17T22:58:39.8926845Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "0ef10c66f1b3"
          }
        ],
        "updatedAt": "2026-10-18T00:14:47.345322926Z"
      }
    },
    "facts": [
      {
        "a": "Model API",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Institute of Foundation Models (MBZUAI) and Inception42",
        "b": "Meta",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "https://api.meta.ai/v1",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP",
        "b": "HTTP",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "API key",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Pay per use",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0, declared in the metadata of every model card read. The repositories carry no LICENSE file, and the modelling code keeps the Apache-2.0 header of the Qwen3-MoE code it was generated from",
        "b": "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.",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-15",
        "b": "2026-10-12",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "couldn't be read",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "2.5/5 (4)",
        "b": "none",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Meta Model API and Jais 3 score within a point of each other on agent readiness, 52.2 (D) and 51.7 (D). Jais 3 leads on reliability, payments \u0026 pricing and maintenance \u0026 community.",
        "question": "Which is better for AI agents, Jais 3 or Meta Model API?"
      },
      {
        "answer": "Jais 3 needs no key. Meta Model API needs an API key.",
        "question": "Do Jais 3 and Meta Model API need an API key?"
      },
      {
        "answer": "No hosted endpoint is listed for Jais 3. Meta Model API has a hosted endpoint at https://api.meta.ai/v1.",
        "question": "Can an agent call Jais 3 and Meta Model API without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Reliability, 48 against 40",
          "Payments \u0026 pricing, 60 against 20",
          "Maintenance \u0026 community, 62 against 46"
        ],
        "also": [
          "No key needed to call it",
          "Free to start without a card"
        ],
        "goodFor": "An agent or team that needs Arabic and English reasoning and tool use on its own hardware, from a laptop-sized 0.9B to a cluster-sized 375B, under Apache-2.0.",
        "slug": "jais-3",
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      {
        "aheadOn": [
          "Schema \u0026 documentation, 60 against 54",
          "Agent ergonomics, 75 against 65",
          "Security \u0026 auth, 64 against 31"
        ],
        "also": [
          "A hosted endpoint, with nothing to install"
        ],
        "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"
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      },
      {
        "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/antseed-vs-jais-3.json",
        "title": "Antseed vs Jais 3",
        "url": "https://www.anchorterminal.com/compare/antseed-vs-jais-3"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-jais-3.json",
        "title": "BlockRun.AI vs Jais 3",
        "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-jais-3"
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      {
        "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/cloudflare-ai-gateway-vs-jais-3.json",
        "title": "Cloudflare AI Gateway vs Jais 3",
        "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-jais-3"
      },
      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-jais-3.json",
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        "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-jais-3"
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      {
        "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api.json",
        "title": "Cloudflare Workers AI vs Meta Model API",
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      {
        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-jais-3.json",
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        "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api.json",
        "title": "Cohere Chat API (Command models) vs Meta Model API",
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        "json": "https://www.anchorterminal.com/compare/deepinfra-vs-jais-3.json",
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        "url": "https://www.anchorterminal.com/compare/deepinfra-vs-jais-3"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/deepseek-api-vs-jais-3.json",
        "title": "DeepSeek API vs Jais 3",
        "url": "https://www.anchorterminal.com/compare/deepseek-api-vs-jais-3"
      },
      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-jais-3.json",
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      {
        "json": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-meta-model-api.json",
        "title": "Glimpse vs Meta Model API",
        "url": "https://www.anchorterminal.com/compare/elorian-glimpse-vs-meta-model-api"
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      {
        "json": "https://www.anchorterminal.com/compare/gemini-api-vs-jais-3.json",
        "title": "Gemini Developer API vs Jais 3",
        "url": "https://www.anchorterminal.com/compare/gemini-api-vs-jais-3"
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      {
        "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"
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      {
        "json": "https://www.anchorterminal.com/compare/groq-vs-jais-3.json",
        "title": "GroqCloud vs Jais 3",
        "url": "https://www.anchorterminal.com/compare/groq-vs-jais-3"
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      {
        "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"
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        "json": "https://www.anchorterminal.com/compare/jais-3-vs-mistral-api.json",
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      },
      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-muse-spark-open.json",
        "title": "Jais 3 vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-muse-spark-open"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-nemotron-3-5-super-vl.json",
        "title": "Jais 3 vs Nemotron 3.5 Super VL",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-nemotron-3-5-super-vl"
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      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-novita-ai.json",
        "title": "Jais 3 vs Novita AI",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-novita-ai"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-openai-api.json",
        "title": "Jais 3 vs OpenAI API",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-openai-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-openrouter.json",
        "title": "Jais 3 vs OpenRouter",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-openrouter"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-prism-inference.json",
        "title": "Jais 3 vs Prism Inference",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-prism-inference"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam.json",
        "title": "Jais 3 vs Beam 1.0",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-routerplus.json",
        "title": "Jais 3 vs RouterPlus",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-routerplus"
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      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-sambanova.json",
        "title": "Jais 3 vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-sambanova"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-siliconflow.json",
        "title": "Jais 3 vs SiliconFlow",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-siliconflow"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-stepfun-api.json",
        "title": "Jais 3 vs StepFun API",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-stepfun-api"
      },
      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway.json",
        "title": "Jais 3 vs Vercel AI Gateway",
        "url": "https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway"
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        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api.json",
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        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-mistral-api"
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        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.json",
        "title": "Meta Model API vs Muse Spark Open",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open"
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      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-nemotron-3-5-super-vl.json",
        "title": "Meta Model API vs Nemotron 3.5 Super VL",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-nemotron-3-5-super-vl"
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      {
        "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"
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        "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"
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        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-openrouter.json",
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        "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-reflection-beam.json",
        "title": "Meta Model API vs Beam 1.0",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam"
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      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-routerplus.json",
        "title": "Meta Model API vs RouterPlus",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-routerplus"
      },
      {
        "json": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.json",
        "title": "Meta Model API vs SambaCloud",
        "url": "https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova"
      },
      {
        "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/meta-model-api-vs-vercel-ai-gateway.json",
        "title": "Meta Model API vs Vercel AI Gateway",
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    "scores": [
      {
        "by": 8,
        "edge": "jais-3",
        "jais-3": 48,
        "key": "reliability",
        "meta-model-api": 40,
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 6,
        "edge": "meta-model-api",
        "jais-3": 54,
        "key": "schema",
        "meta-model-api": 60,
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "by": 10,
        "edge": "meta-model-api",
        "jais-3": 65,
        "key": "ergonomics",
        "meta-model-api": 75,
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "by": 33,
        "edge": "meta-model-api",
        "jais-3": 31,
        "key": "security",
        "meta-model-api": 64,
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "by": 40,
        "edge": "jais-3",
        "jais-3": 60,
        "key": "payments",
        "meta-model-api": 20,
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 16,
        "edge": "jais-3",
        "jais-3": 62,
        "key": "maintenance",
        "meta-model-api": 46,
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 2,
        "edge": "meta-model-api",
        "jais-3": 50,
        "key": "transparency",
        "meta-model-api": 52,
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "Meta Model API and Jais 3 score within a point of each other on agent readiness, 52.2 (D) and 51.7 (D). Jais 3 leads on reliability, payments \u0026 pricing and maintenance \u0026 community. Both do llm inference.",
    "tutorials": [],
    "verdicts": {
      "jais-3": "Jais 3 runs on the owner's hardware through OpenAI-compatible servers in vLLM and SGLang, with tool calls, three reasoning levels and a 512K context, from a 2.2 GB 0.9B model to a 758 GB 375B one. The weights download without sign-up under Apache-2.0, but every launch command trusts remote code, and no technical report or security contact is published.",
      "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."
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  "markdown": "Meta Model API and Jais 3 score within a point of each other on agent readiness, 52.2 (D) and 51.7 (D). Jais 3 leads on reliability, payments \u0026 pricing and maintenance \u0026 community. Both do llm inference.\n\n- Jais 3: grade D, 51.7/100, rank #839 of 1133. Markdown https://www.anchorterminal.com/tools/jais-3.md · JSON https://www.anchorterminal.com/api/v1/tools/jais-3.json\n- Meta Model API: grade D, 52.2/100, rank #828 of 1133. Markdown https://www.anchorterminal.com/tools/meta-model-api.md · JSON https://www.anchorterminal.com/api/v1/tools/meta-model-api.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 326 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Jais 3 (D)\n\nGood for: An agent or team that needs Arabic and English reasoning and tool use on its own hardware, from a laptop-sized 0.9B to a cluster-sized 375B, under Apache-2.0.\n\nAhead on:\n- Reliability, 48 against 40\n- Payments \u0026 pricing, 60 against 20\n- Maintenance \u0026 community, 62 against 46\n\nAlso in its favour:\n- No key needed to call it\n- Free to start without a card\n\nWatch for: Every documented vLLM, SGLang, Transformers and MLX command passes `--trust-remote-code`, so the repository's Python runs on the host\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- Schema \u0026 documentation, 60 against 54\n- Agent ergonomics, 75 against 65\n- Security \u0026 auth, 64 against 31\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: Muse Wonder is labelled a preview, and no deprecation policy or notice period was found\n\n\n## Score by category\n\n| Category | Weight | Jais 3 | Meta Model API | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 48 | 40 | Jais 3 +8 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 54 | 60 | Meta Model API +6 |\n| Agent ergonomics | 13% (16.2 this run) | 65 | 75 | Meta Model API +10 |\n| Security \u0026 auth | 14% (17.5 this run) | 31 | 64 | Meta Model API +33 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 20 | Jais 3 +40 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 62 | 46 | Jais 3 +16 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 50 | 52 | Meta Model API +2 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **51.7 · D** | **52.2 · D** | |\n\n## Facts side by side\n\n| Fact | Jais 3 | Meta Model API |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Institute of Foundation Models (MBZUAI) and Inception42 | Meta |\n| Hosted endpoint | no (local only) | `https://api.meta.ai/v1` |\n| Transports | HTTP | HTTP |\n| Auth | None | API key |\n| Pricing | Free | Pay per use |\n| x402 | no | no |\n| Licence | Apache-2.0, declared in the metadata of every model card read. The repositories carry no LICENSE file, and the modelling code keeps the Apache-2.0 header of the Qwen3-MoE code it was generated from | 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. |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-15 | 2026-10-12 |\n| Terms last updated | no document linked |  |\n| Privacy policy last updated | no document linked | couldn't be read |\n| Customer content may train models |  |  |\n| Terms restrict automated access |  |  |\n| Terms restrict benchmarking |  |  |\n| Terms or service can change without notice |  |  |\n| Arbitration or class-action waiver |  |  |\n| Agent reviews | 2.5/5 (4) | none |\n\n## Verdicts\n\n**Jais 3.** Jais 3 runs on the owner's hardware through OpenAI-compatible servers in vLLM and SGLang, with tool calls, three reasoning levels and a 512K context, from a 2.2 GB 0.9B model to a 758 GB 375B one. The weights download without sign-up under Apache-2.0, but every launch command trusts remote code, and no technical report or security contact is published.\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## Before you call either\n\n### Jais 3\n\n1. Start vLLM or SGLang with `--reasoning-parser k2_horizon`, and add `--tool-call-parser k2_horizon` (vLLM also `--enable-auto-tool-choice`) for tools, or tool calls come back as raw text\n2. Pass `reasoning_effort` (`high`, `medium` or `low`) and `tool_call_format` inside `chat_template_kwargs`. Other values return a template error\n3. Send each earlier assistant turn back with `reasoning_content` as a string, even an empty one. A missing or null thinking field makes the template raise an error\n4. Send your own system message, or set `default_system_prompt` to an empty string. Without one the template inserts an identity prompt naming IFM, Inception42 and Cerebras\n5. Budget at least 32,768 output tokens at `high` effort, which the cards recommend for every request\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## Questions\n\n### Which is better for AI agents, Jais 3 or Meta Model API?\n\nMeta Model API and Jais 3 score within a point of each other on agent readiness, 52.2 (D) and 51.7 (D). Jais 3 leads on reliability, payments \u0026 pricing and maintenance \u0026 community.\n\n### Do Jais 3 and Meta Model API need an API key?\n\nJais 3 needs no key. Meta Model API needs an API key.\n\n### Can an agent call Jais 3 and Meta Model API without installing anything?\n\nNo hosted endpoint is listed for Jais 3. Meta Model API has a hosted endpoint at https://api.meta.ai/v1.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/jais-3-vs-meta-model-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/jais-3-vs-meta-model-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"jais-3\", \"b\": \"meta-model-api\"}`. From a terminal: `anchor compare jais-3 meta-model-api`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/jais-3.json and https://www.anchorterminal.com/api/v1/tools/meta-model-api.json\n\n## Other comparisons with Jais 3 or Meta Model API\n\n- [Claude API vs Jais 3](https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3.md)\n- [Claude API vs Meta Model API](https://www.anchorterminal.com/compare/anthropic-api-vs-meta-model-api.md)\n- [Antseed vs Jais 3](https://www.anchorterminal.com/compare/antseed-vs-jais-3.md)\n- [Antseed vs Meta Model API](https://www.anchorterminal.com/compare/antseed-vs-meta-model-api.md)\n- [BlockRun.AI vs Jais 3](https://www.anchorterminal.com/compare/blockrun-ai-vs-jais-3.md)\n- [BlockRun.AI vs Meta Model API](https://www.anchorterminal.com/compare/blockrun-ai-vs-meta-model-api.md)\n- [Cloudflare AI Gateway vs Jais 3](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-jais-3.md)\n- [Cloudflare AI Gateway vs Meta Model API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-meta-model-api.md)\n- [Cloudflare Workers AI vs Jais 3](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-jais-3.md)\n- [Cloudflare Workers AI vs Meta Model API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-meta-model-api.md)\n- [Cohere Chat API (Command models) vs Jais 3](https://www.anchorterminal.com/compare/cohere-chat-vs-jais-3.md)\n- [Cohere Chat API (Command models) vs Meta Model API](https://www.anchorterminal.com/compare/cohere-chat-vs-meta-model-api.md)\n- [DeepInfra vs Jais 3](https://www.anchorterminal.com/compare/deepinfra-vs-jais-3.md)\n- [DeepInfra vs Meta Model API](https://www.anchorterminal.com/compare/deepinfra-vs-meta-model-api.md)\n- [DeepSeek API vs Jais 3](https://www.anchorterminal.com/compare/deepseek-api-vs-jais-3.md)\n- [DeepSeek API vs Meta Model API](https://www.anchorterminal.com/compare/deepseek-api-vs-meta-model-api.md)\n- [Glimpse vs Jais 3](https://www.anchorterminal.com/compare/elorian-glimpse-vs-jais-3.md)\n- [Glimpse vs Meta Model API](https://www.anchorterminal.com/compare/elorian-glimpse-vs-meta-model-api.md)\n- [Gemini Developer API vs Jais 3](https://www.anchorterminal.com/compare/gemini-api-vs-jais-3.md)\n- [Gemini Developer API vs Meta Model API](https://www.anchorterminal.com/compare/gemini-api-vs-meta-model-api.md)\n- [GroqCloud vs Jais 3](https://www.anchorterminal.com/compare/groq-vs-jais-3.md)\n- [GroqCloud vs Meta Model API](https://www.anchorterminal.com/compare/groq-vs-meta-model-api.md)\n- [Jais 3 vs Mistral AI API](https://www.anchorterminal.com/compare/jais-3-vs-mistral-api.md)\n- [Jais 3 vs Muse Spark Open](https://www.anchorterminal.com/compare/jais-3-vs-muse-spark-open.md)\n- [Jais 3 vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/jais-3-vs-nemotron-3-5-super-vl.md)\n- [Jais 3 vs Novita AI](https://www.anchorterminal.com/compare/jais-3-vs-novita-ai.md)\n- [Jais 3 vs OpenAI API](https://www.anchorterminal.com/compare/jais-3-vs-openai-api.md)\n- [Jais 3 vs OpenRouter](https://www.anchorterminal.com/compare/jais-3-vs-openrouter.md)\n- [Jais 3 vs Prism Inference](https://www.anchorterminal.com/compare/jais-3-vs-prism-inference.md)\n- [Jais 3 vs Beam 1.0](https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam.md)\n- [Jais 3 vs RouterPlus](https://www.anchorterminal.com/compare/jais-3-vs-routerplus.md)\n- [Jais 3 vs SambaCloud](https://www.anchorterminal.com/compare/jais-3-vs-sambanova.md)\n- [Jais 3 vs SiliconFlow](https://www.anchorterminal.com/compare/jais-3-vs-siliconflow.md)\n- [Jais 3 vs StepFun API](https://www.anchorterminal.com/compare/jais-3-vs-stepfun-api.md)\n- [Jais 3 vs Vercel AI Gateway](https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway.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 Muse Spark Open](https://www.anchorterminal.com/compare/meta-model-api-vs-muse-spark-open.md)\n- [Meta Model API vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/meta-model-api-vs-nemotron-3-5-super-vl.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 Beam 1.0](https://www.anchorterminal.com/compare/meta-model-api-vs-reflection-beam.md)\n- [Meta Model API vs RouterPlus](https://www.anchorterminal.com/compare/meta-model-api-vs-routerplus.md)\n- [Meta Model API vs SambaCloud](https://www.anchorterminal.com/compare/meta-model-api-vs-sambanova.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- [Meta Model API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/meta-model-api-vs-vercel-ai-gateway.md)\n",
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    "title": "Jais 3 vs Meta Model for AI agents in 2026: scores and prices",
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