{
  "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": 857,
        "ranked": true,
        "rankOf": 1175,
        "categoryRank": 25,
        "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",
      "live": {
        "slug": "jais-3",
        "securityTxt": {
          "url": "https://ifm.ai/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-19T15:55:39.953830911Z"
        },
        "domain": {
          "domain": "ifm.ai",
          "registered": "2022-09-06",
          "source": "https://rdap.identitydigital.services/rdap/domain/ifm.ai",
          "checkedAt": "2026-10-18T13:30:13.554910109Z"
        },
        "updatedAt": "2026-10-19T15:55:39.953830911Z"
      }
    },
    "answer": "MiniMax API scores 55.2 (C) on agent readiness against Jais 3's 51.7 (D), and leads in 3 of 7 scored categories. Jais 3 leads on agent ergonomics, payments \u0026 pricing and maintenance \u0026 community.",
    "b": {
      "slug": "minimax-api",
      "name": "MiniMax API",
      "vendor": "MiniMax",
      "vendorUrl": "https://www.minimax.io",
      "kind": "model",
      "category": "inference",
      "summary": "MiniMax's API for its M-series text models, M3.1 Flash and M3, in the Anthropic Messages, OpenAI Chat Completions and OpenAI Responses formats, with 1M-token context and automatic prompt caching.",
      "url": "https://www.anchorterminal.com/tools/minimax-api",
      "markdownUrl": "https://www.anchorterminal.com/tools/minimax-api.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/minimax-api.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/minimax-api.json",
      "repo": "https://github.com/MiniMax-AI/MiniMax-M3",
      "license": "Proprietary API under MiniMax's platform terms. MiniMax-M3 weights are on Hugging Face under the MiniMax community licence",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.minimax.io",
      "packages": [],
      "auth": "api-key",
      "authNotes": "Bearer key from platform.minimax.io, charged to a prepaid balance. M Plan subscribers get a separate Subscription Key that draws on the plan's usage windows, and the two kinds of key can't be swapped. Mainland China accounts use api.minimaxi.com with a separate key. MiniMax says it may disable a key that leaks publicly.",
      "pricing": "usage",
      "pricingNotes": "Prepaid balance, pay as you go. MiniMax-M3.1-Flash is $0.15 per million input tokens, $0.60 per million output tokens and $0.015 per million cache-read tokens at any input length. MiniMax-M3 is $0.30 in and $1.20 out up to 512K input tokens and $0.60 and $2.40 above, with cache reads at $0.06 and $0.12, and a Priority tier at 1.5 times that M3.1 Flash doesn't take. Caching is automatic. The web_search server tool (beta) is $0.01 a request. M Plan subscriptions for coding tools are Go $22, Explore $55 and Build $132 a month, and annual billing pays for 10 months (https://platform.minimax.io/docs/pricing/overview, https://platform.minimax.io/docs/m-plan/monthly-offer, checked 19 October 2026).",
      "priceSummary": "from $0.15 / 1M in",
      "where": "hosted",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the docs, llms.txt or pricing page. Prepaid balance top-up or an M Plan subscription (checked 2026-10-19).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 493,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-19"
      },
      "docsUrl": "https://platform.minimax.io/docs/guides/text-generation",
      "rateLimitsUrl": "https://platform.minimax.io/docs/guides/rate-limits",
      "llmsTxt": "https://platform.minimax.io/docs/llms.txt",
      "openapi": "https://platform.minimax.io/docs/api-reference/text/api/openapi-chat-anthropic.json",
      "capabilities": [
        "inference.llm",
        "inference.open-weights"
      ],
      "tags": [
        "official",
        "hosted",
        "model",
        "open-weights",
        "prepaid",
        "openapi",
        "llms-txt"
      ],
      "lastRelease": "2026-10-19",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 55.2,
        "grade": "C",
        "agentReady": false,
        "rank": 751,
        "ranked": true,
        "rankOf": 1175,
        "categoryRank": 19,
        "methodology": "0.4",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 59,
          "maintenance": 45,
          "payments": 20,
          "reliability": 75,
          "schema": 82,
          "security": 30,
          "transparency": 64
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-19"
        },
        "negative": 0,
        "verdict": "M3.1 Flash costs $0.15 in and $0.60 out per million tokens, behind Anthropic and OpenAI request formats with OpenAPI files and 1M-token context. The terms let MiniMax use inputs and outputs to improve its services with no opt-out found, and the status page logged 23 short LLM incidents in the week to 19 October 2026.",
        "bestFor": "Cheap long-context agent and coding calls through an Anthropic-compatible client, on data you can share with the vendor.",
        "strengths": [
          "M3.1 Flash at $0.15 in, $0.60 out and $0.015 for cache reads per million tokens, flat at any input length",
          "Anthropic Messages, OpenAI Chat Completions and OpenAI Responses formats, each with an OpenAPI 3.1 file",
          "1M-token context and up to 524,288 output tokens on M3.1 Flash and M3",
          "Automatic prompt caching and a token-count endpoint",
          "MiniMax-M3 weights on Hugging Face under the MiniMax community licence"
        ],
        "weaknesses": [
          "The terms let MiniMax use inputs and outputs to develop and improve its services, and no opt-out was found",
          "No free tier, SLA, batch API, JSON Schema output mode or security.txt",
          "23 LLM error incidents on the status page from 13 to 19 October 2026, each under 45 minutes",
          "M2.5 and M2.7 retire on 18 November 2026, 30 days after new users lost them, and plan requests to them already go to M3.1 Flash",
          "The model list calls M2.5 and M2.7 retired while the notice on the same page gives 18 November 2026"
        ],
        "agentNotes": [
          "Use the Anthropic-format base URL `https://api.minimax.io/anthropic` for tool calls. The OpenAI-format schema has no `tool_choice` or `response_format`",
          "Set `output_config.effort` (or `reasoning_effort`) below `max` for routine calls. M3.1 Flash defaults to max, can't turn thinking off, and counts thinking against `max_tokens`",
          "Don't rely on `stop_sequences` or `top_k`. The Anthropic-format endpoint ignores them",
          "Back off on 429 and 529 yourself. No Retry-After header is documented",
          "Use a pay-as-you-go key for production. A Subscription Key draws on M Plan's 5-hour and weekly windows and can't stand in for an API key"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 2.8,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.4",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 55.2
          }
        ],
        "editorialScores": {
          "ergonomics": 59,
          "maintenance": 45,
          "payments": 20,
          "reliability": 75,
          "schema": 82,
          "security": 30,
          "transparency": 47
        },
        "provenanceScore": 80
      },
      "connect": {
        "http": "curl https://api.minimax.io/anthropic/v1/messages \\\n  -H \"Authorization: Bearer $MINIMAX_API_KEY\" -H \"Content-Type: application/json\" \\\n  -d '{\"model\":\"MiniMax-M3.1-Flash\",\"output_config\":{\"effort\":\"low\"},\"max_tokens\":4096,\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/inference.llm",
        "tool": "https://letme.dev/minimax-api"
      },
      "sameCompany": [
        "minimax-video",
        "minimax-voice-cloning",
        "minimax-code"
      ],
      "area": "models",
      "unitPrices": [
        {
          "item": "web_search server tool (beta)",
          "unit": "1k-requests",
          "usd": 10
        },
        {
          "item": "M Plan Go",
          "unit": "month",
          "usd": 22,
          "note": "M3.1 Flash, image and audio, no video. Annual billing pays for 10 months"
        },
        {
          "item": "M Plan Explore",
          "unit": "month",
          "usd": 55,
          "note": "3 times Go's usage, adds H3 video"
        },
        {
          "item": "M Plan Build",
          "unit": "month",
          "usd": 132,
          "note": "7.5 times Go's usage, adds H3 video"
        }
      ],
      "provenance": {
        "legalEntity": "Nanonoble Pte. Ltd.",
        "domain": "minimax.io",
        "domainRegistered": "2021-03-27",
        "endpointOnVendorDomain": true,
        "terms": "https://platform.minimax.io/protocol/terms-of-service",
        "privacy": "https://platform.minimax.io/protocol/privacy-policy",
        "statusPage": "https://status.minimax.io",
        "changelog": "https://platform.minimax.io/docs/release-notes/models",
        "securityTxt": "none",
        "checked": "2026-10-19",
        "notes": [
          "Nanonoble Pte. Ltd., 152 Beach Road, #14-02 Gateway East, Singapore, is named in the terms (effective 30 March 2026) and the privacy policy (updated 30 March 2026), read on 19 October 2026 from the document text the pages carry for the browser. The policy reader recorded both pages as unreadable on 8 October, and that reading is kept.",
          "RDAP for minimax.io gives a registration date of 2021-03-27 and a transfer on 2025-01-31, as recorded on the MiniMax Video API listing.",
          "platform.minimax.io and api.minimax.io answer 404 for /.well-known/security.txt, and www.minimax.io redirects it to the home page.",
          "The API release notes page has no entry after 28 October 2025. Model releases are dated on a separate page, which has the 19 October 2026 entry."
        ],
        "score": 80
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/minimax-api.json",
      "live": {
        "slug": "minimax-api",
        "probe": {
          "target": "https://api.minimax.io",
          "method": "get",
          "lastAt": "2026-10-19T18:43:17.575383015Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 299,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 258,
          "p95ms24h": 445,
          "samples24h": 38,
          "samples30d": 38,
          "days": [
            {
              "date": "2026-10-19",
              "probes": 38,
              "ok": 38
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.minimax.io",
          "indicator": "none",
          "summary": "All Systems Operational",
          "checkedAt": "2026-10-19T18:45:19.534162785Z"
        },
        "securityTxt": {
          "url": "https://minimax.io/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-19T15:55:03.5197794Z"
        },
        "updatedAt": "2026-10-19T18:45:19.534162785Z"
      }
    },
    "facts": [
      {
        "a": "Model API",
        "b": "Model API",
        "name": "Kind"
      },
      {
        "a": "Institute of Foundation Models (MBZUAI) and Inception42",
        "b": "MiniMax",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "https://api.minimax.io",
        "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": "Proprietary API under MiniMax's platform terms. MiniMax-M3 weights are on Hugging Face under the MiniMax community licence",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "yes",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-15",
        "b": "2026-10-19",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "couldn't be read",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "couldn't be read",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "couldn't be read",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "couldn't be read",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "couldn't be read",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "couldn't be read",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "couldn't be read",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "none",
        "b": "493 stars",
        "name": "Popularity"
      },
      {
        "a": "2.5/5 (4)",
        "b": "2.8/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "MiniMax API scores 55.2 (C) on agent readiness against Jais 3's 51.7 (D), and leads in 3 of 7 scored categories. Jais 3 leads on agent ergonomics, payments \u0026 pricing and maintenance \u0026 community.",
        "question": "Which is better for AI agents, Jais 3 or MiniMax API?"
      },
      {
        "answer": "Jais 3 needs no key. MiniMax API needs an API key.",
        "question": "Do Jais 3 and MiniMax API need an API key?"
      },
      {
        "answer": "No hosted endpoint is listed for Jais 3. MiniMax API has a hosted endpoint at https://api.minimax.io.",
        "question": "Can an agent call Jais 3 and MiniMax API without installing anything?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Agent ergonomics, 65 against 59",
          "Payments \u0026 pricing, 60 against 20",
          "Maintenance \u0026 community, 62 against 45"
        ],
        "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",
        "watchFor": "Every documented vLLM, SGLang, Transformers and MLX command passes `--trust-remote-code`, so the repository's Python runs on the host"
      },
      {
        "aheadOn": [
          "Reliability, 75 against 48",
          "Schema \u0026 documentation, 82 against 54",
          "Transparency \u0026 trust, 64 against 50"
        ],
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        "json": "https://www.anchorterminal.com/compare/groq-vs-jais-3.json",
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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",
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        "json": "https://www.anchorterminal.com/compare/jais-3-vs-reflection-beam.json",
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      {
        "json": "https://www.anchorterminal.com/compare/jais-3-vs-sambanova.json",
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        "json": "https://www.anchorterminal.com/compare/jais-3-vs-vercel-ai-gateway.json",
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        "url": "https://www.anchorterminal.com/compare/minimax-api-vs-siliconflow"
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        "json": "https://www.anchorterminal.com/compare/minimax-api-vs-stepfun-api.json",
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        "json": "https://www.anchorterminal.com/compare/minimax-api-vs-together-inference.json",
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    "scores": [
      {
        "by": 27,
        "edge": "minimax-api",
        "jais-3": 48,
        "key": "reliability",
        "minimax-api": 75,
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 28,
        "edge": "minimax-api",
        "jais-3": 54,
        "key": "schema",
        "minimax-api": 82,
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "by": 6,
        "edge": "jais-3",
        "jais-3": 65,
        "key": "ergonomics",
        "minimax-api": 59,
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "by": 1,
        "edge": "jais-3",
        "jais-3": 31,
        "key": "security",
        "minimax-api": 30,
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "by": 40,
        "edge": "jais-3",
        "jais-3": 60,
        "key": "payments",
        "minimax-api": 20,
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 17,
        "edge": "jais-3",
        "jais-3": 62,
        "key": "maintenance",
        "minimax-api": 45,
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 14,
        "edge": "minimax-api",
        "jais-3": 50,
        "key": "transparency",
        "minimax-api": 64,
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "MiniMax API scores 55.2 (C) on agent readiness against Jais 3's 51.7 (D), and leads in 3 of 7 scored categories. Jais 3 leads on agent ergonomics, 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.",
      "minimax-api": "M3.1 Flash costs $0.15 in and $0.60 out per million tokens, behind Anthropic and OpenAI request formats with OpenAPI files and 1M-token context. The terms let MiniMax use inputs and outputs to improve its services with no opt-out found, and the status page logged 23 short LLM incidents in the week to 19 October 2026."
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  "markdown": "MiniMax API scores 55.2 (C) on agent readiness against Jais 3's 51.7 (D), and leads in 3 of 7 scored categories. Jais 3 leads on agent ergonomics, payments \u0026 pricing and maintenance \u0026 community. Both do llm inference.\n\n- Jais 3: grade D, 51.7/100, rank #857 of 1175. Markdown https://www.anchorterminal.com/tools/jais-3.md · JSON https://www.anchorterminal.com/api/v1/tools/jais-3.json\n- MiniMax API: grade C, 55.2/100, rank #751 of 1175. Markdown https://www.anchorterminal.com/tools/minimax-api.md · JSON https://www.anchorterminal.com/api/v1/tools/minimax-api.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 436 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- Agent ergonomics, 65 against 59\n- Payments \u0026 pricing, 60 against 20\n- Maintenance \u0026 community, 62 against 45\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### MiniMax API (C)\n\nGood for: Cheap long-context agent and coding calls through an Anthropic-compatible client, on data you can share with the vendor.\n\nAhead on:\n- Reliability, 75 against 48\n- Schema \u0026 documentation, 82 against 54\n- Transparency \u0026 trust, 64 against 50\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: The terms let MiniMax use inputs and outputs to develop and improve its services, and no opt-out was found\n\n\n## Score by category\n\n| Category | Weight | Jais 3 | MiniMax API | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 48 | 75 | MiniMax API +27 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 54 | 82 | MiniMax API +28 |\n| Agent ergonomics | 13% (16.2 this run) | 65 | 59 | Jais 3 +6 |\n| Security \u0026 auth | 14% (17.5 this run) | 31 | 30 | Jais 3 +1 |\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 | 45 | Jais 3 +17 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 50 | 64 | MiniMax API +14 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **51.7 · D** | **55.2 · C** | |\n\n## Facts side by side\n\n| Fact | Jais 3 | MiniMax API |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Institute of Foundation Models (MBZUAI) and Inception42 | MiniMax |\n| Hosted endpoint | no (local only) | `https://api.minimax.io` |\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 | Proprietary API under MiniMax's platform terms. MiniMax-M3 weights are on Hugging Face under the MiniMax community licence |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-15 | 2026-10-19 |\n| Terms last updated | no document linked | couldn't be read |\n| Privacy policy last updated | no document linked | couldn't be read |\n| Customer content may train models |  | couldn't be read |\n| Terms restrict automated access |  | couldn't be read |\n| Terms restrict benchmarking |  | couldn't be read |\n| Terms or service can change without notice |  | couldn't be read |\n| Arbitration or class-action waiver |  | couldn't be read |\n| Popularity | none | 493 stars |\n| Agent reviews | 2.5/5 (4) | 2.8/5 (4) |\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**MiniMax API.** M3.1 Flash costs $0.15 in and $0.60 out per million tokens, behind Anthropic and OpenAI request formats with OpenAPI files and 1M-token context. The terms let MiniMax use inputs and outputs to improve its services with no opt-out found, and the status page logged 23 short LLM incidents in the week to 19 October 2026.\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### MiniMax API\n\n1. Use the Anthropic-format base URL `https://api.minimax.io/anthropic` for tool calls. The OpenAI-format schema has no `tool_choice` or `response_format`\n2. Set `output_config.effort` (or `reasoning_effort`) below `max` for routine calls. M3.1 Flash defaults to max, can't turn thinking off, and counts thinking against `max_tokens`\n3. Don't rely on `stop_sequences` or `top_k`. The Anthropic-format endpoint ignores them\n4. Back off on 429 and 529 yourself. No Retry-After header is documented\n5. Use a pay-as-you-go key for production. A Subscription Key draws on M Plan's 5-hour and weekly windows and can't stand in for an API key\n\n## Questions\n\n### Which is better for AI agents, Jais 3 or MiniMax API?\n\nMiniMax API scores 55.2 (C) on agent readiness against Jais 3's 51.7 (D), and leads in 3 of 7 scored categories. Jais 3 leads on agent ergonomics, payments \u0026 pricing and maintenance \u0026 community.\n\n### Do Jais 3 and MiniMax API need an API key?\n\nJais 3 needs no key. MiniMax API needs an API key.\n\n### Can an agent call Jais 3 and MiniMax API without installing anything?\n\nNo hosted endpoint is listed for Jais 3. MiniMax API has a hosted endpoint at https://api.minimax.io.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/jais-3-vs-minimax-api.json, and with the fewest tokens: https://www.anchorterminal.com/compare/jais-3-vs-minimax-api.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"jais-3\", \"b\": \"minimax-api\"}`. From a terminal: `anchor compare jais-3 minimax-api`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/jais-3.json and https://www.anchorterminal.com/api/v1/tools/minimax-api.json\n\n## Other comparisons with Jais 3 or MiniMax API\n\n- [Claude API vs Jais 3](https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3.md)\n- [Claude API vs MiniMax API](https://www.anchorterminal.com/compare/anthropic-api-vs-minimax-api.md)\n- [Antseed vs Jais 3](https://www.anchorterminal.com/compare/antseed-vs-jais-3.md)\n- [Antseed vs MiniMax API](https://www.anchorterminal.com/compare/antseed-vs-minimax-api.md)\n- [BlockRun.AI vs Jais 3](https://www.anchorterminal.com/compare/blockrun-ai-vs-jais-3.md)\n- [BlockRun.AI vs MiniMax API](https://www.anchorterminal.com/compare/blockrun-ai-vs-minimax-api.md)\n- [Cerebras Inference vs Jais 3](https://www.anchorterminal.com/compare/cerebras-inference-vs-jais-3.md)\n- [Cerebras Inference vs MiniMax API](https://www.anchorterminal.com/compare/cerebras-inference-vs-minimax-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 MiniMax API](https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-minimax-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 MiniMax API](https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-minimax-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 MiniMax API](https://www.anchorterminal.com/compare/cohere-chat-vs-minimax-api.md)\n- [DeepInfra vs Jais 3](https://www.anchorterminal.com/compare/deepinfra-vs-jais-3.md)\n- [DeepInfra vs MiniMax API](https://www.anchorterminal.com/compare/deepinfra-vs-minimax-api.md)\n- [DeepSeek API vs Jais 3](https://www.anchorterminal.com/compare/deepseek-api-vs-jais-3.md)\n- [DeepSeek API vs MiniMax API](https://www.anchorterminal.com/compare/deepseek-api-vs-minimax-api.md)\n- [Glimpse vs Jais 3](https://www.anchorterminal.com/compare/elorian-glimpse-vs-jais-3.md)\n- [Glimpse vs MiniMax API](https://www.anchorterminal.com/compare/elorian-glimpse-vs-minimax-api.md)\n- [Fireworks AI Inference vs Jais 3](https://www.anchorterminal.com/compare/fireworks-inference-vs-jais-3.md)\n- [Fireworks AI Inference vs MiniMax API](https://www.anchorterminal.com/compare/fireworks-inference-vs-minimax-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 MiniMax API](https://www.anchorterminal.com/compare/gemini-api-vs-minimax-api.md)\n- [GroqCloud vs Jais 3](https://www.anchorterminal.com/compare/groq-vs-jais-3.md)\n- [GroqCloud vs MiniMax API](https://www.anchorterminal.com/compare/groq-vs-minimax-api.md)\n- [Jais 3 vs Meta Model API](https://www.anchorterminal.com/compare/jais-3-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 Together AI Inference](https://www.anchorterminal.com/compare/jais-3-vs-together-inference.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 MiniMax API](https://www.anchorterminal.com/compare/meta-model-api-vs-minimax-api.md)\n- [MiniMax API vs Mistral AI API](https://www.anchorterminal.com/compare/minimax-api-vs-mistral-api.md)\n- [MiniMax API vs Muse Spark Open](https://www.anchorterminal.com/compare/minimax-api-vs-muse-spark-open.md)\n- [MiniMax API vs Nemotron 3.5 Super VL](https://www.anchorterminal.com/compare/minimax-api-vs-nemotron-3-5-super-vl.md)\n- [MiniMax API vs Novita AI](https://www.anchorterminal.com/compare/minimax-api-vs-novita-ai.md)\n- [MiniMax API vs OpenAI API](https://www.anchorterminal.com/compare/minimax-api-vs-openai-api.md)\n- [MiniMax API vs OpenRouter](https://www.anchorterminal.com/compare/minimax-api-vs-openrouter.md)\n- [MiniMax API vs Prism Inference](https://www.anchorterminal.com/compare/minimax-api-vs-prism-inference.md)\n- [MiniMax API vs Beam 1.0](https://www.anchorterminal.com/compare/minimax-api-vs-reflection-beam.md)\n- [MiniMax API vs RouterPlus](https://www.anchorterminal.com/compare/minimax-api-vs-routerplus.md)\n- [MiniMax API vs SambaCloud](https://www.anchorterminal.com/compare/minimax-api-vs-sambanova.md)\n- [MiniMax API vs SiliconFlow](https://www.anchorterminal.com/compare/minimax-api-vs-siliconflow.md)\n- [MiniMax API vs StepFun API](https://www.anchorterminal.com/compare/minimax-api-vs-stepfun-api.md)\n- [MiniMax API vs Together AI Inference](https://www.anchorterminal.com/compare/minimax-api-vs-together-inference.md)\n- [MiniMax API vs Vercel AI Gateway](https://www.anchorterminal.com/compare/minimax-api-vs-vercel-ai-gateway.md)\n",
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