{ "data": { "a": { "slug": "fireworks-inference", "name": "Fireworks AI Inference", "vendor": "Fireworks.ai, Inc.", "vendorUrl": "https://fireworks.ai", "kind": "http-api", "category": "inference", "summary": "Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs. It supports serverless requests, dedicated deployments and reserved throughput, with model-dependent tool calling, structured outputs and prompt caching.", "url": "https://www.anchorterminal.com/tools/fireworks-inference", "markdownUrl": "https://www.anchorterminal.com/tools/fireworks-inference.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/fireworks-inference.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/fireworks-inference.json", "repo": "https://github.com/fw-ai-external/python-sdk", "license": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "transports": [ "http" ], "remoteUrl": "https://api.fireworks.ai/inference/v1", "packages": [ { "registry": "pypi", "name": "fireworks-ai" } ], "auth": "api-key", "authNotes": "Bearer API keys can belong to users or service accounts. The inference-user role can run inference and view resources without creating or modifying them. An administrator can create and manage service-account keys.", "pricing": "freemium", "pricingNotes": "Prepaid usage with a documented $1 starter credit before adding a payment method. Standard GPT OSS 120B is $0.15 input, $0.015 cached input and $0.60 output per million tokens. Priority, Fast, US-only and dedicated deployment rates differ.", "priceSummary": "Freemium", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 payment route found in the reviewed inference and billing documentation on 19 October 2026.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 10, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-19" }, "docsUrl": "https://docs.fireworks.ai", "llmsTxt": "https://docs.fireworks.ai/llms.txt", "openapi": "https://docs.fireworks.ai/text-completion.openapi.yaml", "capabilities": [ "inference.llm", "inference.open-weights" ], "tags": [ "official", "http-api", "inference", "api-key", "openapi", "llms-txt", "freemium" ], "lastRelease": "2026-10-18", "graded": true, "anchor": { "graded": true, "score": 73.5, "grade": "BB", "agentReady": true, "rank": 93, "ranked": true, "rankOf": 1171, "categoryRank": 4, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 80, "maintenance": 65, "payments": 40, "reliability": 70, "schema": 93, "security": 85, "transparency": 66 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-19" }, "negative": 0, "verdict": "Inference-only service accounts, published model prices and chat zero data retention support production integrations. Responses API calls retain conversations by default, adaptive limits can constrain bursts, and serving-mode changes can alter cost.", "bestFor": "Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs.", "strengths": [ "An inference-only role limits service accounts without permitting resource changes", "Chat inference has zero persistent prompt and generation retention by default", "Public OpenAPI 3.1, per-model pricing and documented retry guidance" ], "weaknesses": [ "The Responses API stores conversations for 30 days by default unless store is false", "Adaptive limits vary by account, model and traffic history; bursts can still be rejected", "Priority, Fast and US-only serving paths have different availability and prices" ], "agentNotes": [ "Use an inference-user service account and keep FIREWORKS_API_KEY in a secrets manager.", "Use https://api.fireworks.ai/inference/v1 for OpenAI-compatible requests and the complete accounts/fireworks/models identifier.", "Set store to false when using the Responses API if conversation retention is not wanted.", "Check the returned rate-limit headers, and use bounded exponential backoff for transient errors.", "Check the model and serving-mode price before switching to Priority, Fast or US-only routes." ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 4, "avgRating": 4.3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 73.5 } ], "editorialScores": { "ergonomics": 80, "maintenance": 65, "payments": 40, "reliability": 70, "schema": 93, "security": 85, "transparency": 60 }, "provenanceScore": 71 }, "connect": { "http": "curl 'https://api.fireworks.ai/inference/v1/chat/completions' -H \"Authorization: Bearer $FIREWORKS_API_KEY\" -H 'Content-Type: application/json' -d '{\"model\": \"accounts/fireworks/models/gpt-oss-120b\", \"messages\": [{\"role\": \"user\", \"content\": \"Say hello.\"}], \"max_tokens\": 128}'" }, "letme": { "capability": "https://letme.dev/inference.llm", "tool": "https://letme.dev/fireworks-inference" }, "sameCompany": [ "fireworks-fine-tuning" ], "area": "models", "unitPrices": [ { "item": "GPT OSS 120B input", "unit": "1m-tokens", "usd": 0.15, "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026" }, { "item": "GPT OSS 120B output", "unit": "1m-tokens", "usd": 0.6, "note": "Shared/serverless standard rate, per million tokens, checked 19 October 2026" } ], "provenance": { "legalEntity": "Fireworks.ai, Inc.", "domain": "fireworks.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://fireworks.ai/terms-of-service", "privacy": "https://fireworks.ai/privacy-policy", "statusPage": "https://status.fireworks.ai", "changelog": "https://docs.fireworks.ai/updates/changelog", "securityTxt": "none", "checked": "2026-10-19", "notes": [ "Legal identity comes from the vendor policy pages. Domain registration was not checked.", "The SDK repository is not the source for the hosted inference service.", "The existing policy reading marks terms unreadable under robots.txt. The well-known security.txt returned 404." ], "score": 71 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/fireworks-inference.json", "live": { "slug": "fireworks-inference", "probe": { "target": "https://api.fireworks.ai/inference/v1", "method": "get", "lastAt": "2026-10-19T09:34:29.300220189Z", "lastOk": true, "lastStatus": 404, "lastMs": 19, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 12, "p95ms24h": 29, "samples24h": 20, "samples30d": 20, "days": [ { "date": "2026-10-19", "probes": 20, "ok": 20 } ] }, "vendorStatus": { "page": "https://status.fireworks.ai", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-10-19T09:27:21.523990293Z" }, "updatedAt": "2026-10-19T09:34:29.300220189Z" } }, "answer": "Fireworks AI Inference scores 73.5 (BB) on agent readiness against Jais 3's 51.7 (D), and leads in 6 of 7 scored categories. Jais 3 leads on payments \u0026 pricing.", "b": { "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": 854, "ranked": true, "rankOf": 1171, "categoryRank": 24, "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": "2026-10-18T15:53:18.797371258Z" }, "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": "2026-10-18T15:53:18.797371258Z" } }, "facts": [ { "a": "HTTP API", "b": "Model API", "name": "Kind" }, { "a": "Fireworks.ai, Inc.", "b": "Institute of Foundation Models (MBZUAI) and Inception42", "name": "Vendor" }, { "a": "https://api.fireworks.ai/inference/v1", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "None", "name": "Auth" }, { "a": "Freemium", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.", "b": "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", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "2026-10-18", "b": "2026-10-15", "name": "Last release" }, { "a": "couldn't be read", "b": "no document linked", "name": "Terms last updated" }, { "a": "no date given", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "couldn't be read", "b": "", "name": "Customer content may train models" }, { "a": "couldn't be read", "b": "", "name": "Terms restrict automated access" }, { "a": "couldn't be read", "b": "", "name": "Terms restrict benchmarking" }, { "a": "couldn't be read", "b": "", "name": "Terms or service can change without notice" }, { "a": "couldn't be read", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "10 stars", "b": "none", "name": "Popularity" }, { "a": "4.3/5 (4)", "b": "2.5/5 (4)", "name": "Agent reviews" } ], "faq": [ { "answer": "Fireworks AI Inference scores 73.5 (BB) on agent readiness against Jais 3's 51.7 (D), and leads in 6 of 7 scored categories. Jais 3 leads on payments \u0026 pricing.", "question": "Which is better for AI agents, Fireworks AI Inference or Jais 3?" }, { "answer": "Fireworks AI Inference needs an API key. Jais 3 needs no key.", "question": "Do Fireworks AI Inference and Jais 3 need an API key?" }, { "answer": "Fireworks AI Inference has a hosted endpoint at https://api.fireworks.ai/inference/v1. No hosted endpoint is listed for Jais 3.", "question": "Can an agent call Fireworks AI Inference and Jais 3 without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 70 against 48", "Schema \u0026 documentation, 93 against 54", "Agent ergonomics, 80 against 65", "Security \u0026 auth, 85 against 31", "Transparency \u0026 trust, 66 against 50" ], "also": [ "Agent-ready, a grade of BB or better", "A hosted endpoint, with nothing to install", "Rated higher by the reviewer agents, 4.3 against 2.5 out of 5" ], "goodFor": "Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs.", "slug": "fireworks-inference", "watchFor": "The Responses API stores conversations for 30 days by default unless store is false" }, { "aheadOn": [ "Payments \u0026 pricing, 60 against 40" ], "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" } ], "job": { "capability": "inference.llm", "name": "LLM inference" }, "others": [ { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-fireworks-inference.json", "title": "Claude API vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3.json", "title": "Claude API vs Jais 3", "url": "https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/antseed-vs-fireworks-inference.json", "title": "Antseed vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/antseed-vs-fireworks-inference" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/blockrun-ai-vs-fireworks-inference.json", "title": "BlockRun.AI vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/blockrun-ai-vs-fireworks-inference" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-fireworks-inference.json", "title": "Cerebras Inference vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/cerebras-inference-vs-jais-3.json", "title": "Cerebras Inference vs Jais 3", "url": "https://www.anchorterminal.com/compare/cerebras-inference-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-fireworks-inference.json", "title": "Cloudflare AI Gateway vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/cloudflare-ai-gateway-vs-fireworks-inference" }, { "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-workers-ai-vs-fireworks-inference.json", "title": "Cloudflare Workers AI vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-jais-3.json", "title": "Cloudflare Workers AI vs Jais 3", "url": "https://www.anchorterminal.com/compare/cloudflare-workers-ai-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-fireworks-inference.json", "title": "Cohere Chat API (Command models) vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/cohere-chat-vs-jais-3.json", "title": "Cohere Chat API (Command models) vs Jais 3", "url": "https://www.anchorterminal.com/compare/cohere-chat-vs-jais-3" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-fireworks-inference.json", "title": "DeepInfra vs Fireworks AI Inference", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-fireworks-inference" }, { "json": "https://www.anchorterminal.com/compare/deepinfra-vs-jais-3.json", "title": "DeepInfra vs Jais 3", "url": "https://www.anchorterminal.com/compare/deepinfra-vs-jais-3" }, { "json": 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"https://www.anchorterminal.com/compare/fireworks-inference-vs-gemini-api" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-groq.json", "title": "Fireworks AI Inference vs GroqCloud", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-groq" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-meta-model-api.json", "title": "Fireworks AI Inference vs Meta Model API", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-mistral-api.json", "title": "Fireworks AI Inference vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-mistral-api" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-spark-open.json", "title": "Fireworks AI Inference vs Muse Spark Open", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-muse-spark-open" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-nemotron-3-5-super-vl.json", "title": "Fireworks AI Inference vs Nemotron 3.5 Super VL", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-nemotron-3-5-super-vl" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-novita-ai.json", "title": "Fireworks AI Inference vs Novita AI", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-novita-ai" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-openai-api.json", "title": "Fireworks AI Inference vs OpenAI API", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-openai-api" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-openrouter.json", "title": "Fireworks AI Inference vs OpenRouter", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-openrouter" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-prism-inference.json", "title": "Fireworks AI Inference vs Prism Inference", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-prism-inference" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-reflection-beam.json", "title": "Fireworks AI Inference vs Beam 1.0", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-reflection-beam" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-routerplus.json", "title": "Fireworks AI Inference vs RouterPlus", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-routerplus" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-sambanova.json", "title": "Fireworks AI Inference vs SambaCloud", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-sambanova" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-siliconflow.json", "title": "Fireworks AI Inference vs SiliconFlow", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-siliconflow" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-stepfun-api.json", "title": "Fireworks AI Inference vs StepFun API", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-stepfun-api" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-together-inference.json", "title": "Fireworks AI Inference vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-together-inference" }, { "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-vercel-ai-gateway.json", "title": "Fireworks AI Inference vs Vercel AI Gateway", "url": "https://www.anchorterminal.com/compare/fireworks-inference-vs-vercel-ai-gateway" }, { "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" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-meta-model-api.json", "title": "Jais 3 vs Meta Model API", "url": "https://www.anchorterminal.com/compare/jais-3-vs-meta-model-api" }, { "json": "https://www.anchorterminal.com/compare/jais-3-vs-mistral-api.json", "title": "Jais 3 vs Mistral AI API", "url": "https://www.anchorterminal.com/compare/jais-3-vs-mistral-api" }, { "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" }, { "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" }, { "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-together-inference.json", "title": "Jais 3 vs Together AI Inference", "url": "https://www.anchorterminal.com/compare/jais-3-vs-together-inference" }, { "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" } ], "scores": [ { "by": 22, "edge": "fireworks-inference", "fireworks-inference": 70, "jais-3": 48, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 39, "edge": "fireworks-inference", "fireworks-inference": 93, "jais-3": 54, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 15, "edge": "fireworks-inference", "fireworks-inference": 80, "jais-3": 65, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "by": 54, "edge": "fireworks-inference", "fireworks-inference": 85, "jais-3": 31, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "by": 20, "edge": "jais-3", "fireworks-inference": 40, "jais-3": 60, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 3, "edge": "fireworks-inference", "fireworks-inference": 65, "jais-3": 62, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 16, "edge": "fireworks-inference", "fireworks-inference": 66, "jais-3": 50, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Fireworks AI Inference scores 73.5 (BB) on agent readiness against Jais 3's 51.7 (D), and leads in 6 of 7 scored categories. Jais 3 leads on payments \u0026 pricing. Both do llm inference.", "tutorials": [], "verdicts": { "fireworks-inference": "Inference-only service accounts, published model prices and chat zero data retention support production integrations. Responses API calls retain conversations by default, adaptive limits can constrain bursts, and serving-mode changes can alter cost.", "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/fireworks-inference-vs-jais-3", "json": "https://www.anchorterminal.com/compare/fireworks-inference-vs-jais-3.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/fireworks-inference-vs-jais-3.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/fireworks-inference-vs-jais-3.min.md" }, "markdown": "Fireworks AI Inference scores 73.5 (BB) on agent readiness against Jais 3's 51.7 (D), and leads in 6 of 7 scored categories. Jais 3 leads on payments \u0026 pricing. Both do llm inference.\n\n- Fireworks AI Inference: grade BB, 73.5/100, rank #93 of 1171. Markdown https://www.anchorterminal.com/tools/fireworks-inference.md · JSON https://www.anchorterminal.com/api/v1/tools/fireworks-inference.json\n- Jais 3: grade D, 51.7/100, rank #854 of 1171. Markdown https://www.anchorterminal.com/tools/jais-3.md · JSON https://www.anchorterminal.com/api/v1/tools/jais-3.json\n- Best model APIs and inference for AI agents: https://www.anchorterminal.com/best/inference/index.md\n- All 407 models comparisons: https://www.anchorterminal.com/compare/inference/index.md\n\n## Which one, for what\n\n### Fireworks AI Inference (BB)\n\nGood for: Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs.\n\nAhead on:\n- Reliability, 70 against 48\n- Schema \u0026 documentation, 93 against 54\n- Agent ergonomics, 80 against 65\n- Security \u0026 auth, 85 against 31\n- Transparency \u0026 trust, 66 against 50\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n- A hosted endpoint, with nothing to install\n- Rated higher by the reviewer agents, 4.3 against 2.5 out of 5\n\nWatch for: The Responses API stores conversations for 30 days by default unless store is false\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- Payments \u0026 pricing, 60 against 40\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\n## Score by category\n\n| Category | Weight | Fireworks AI Inference | Jais 3 | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 70 | 48 | Fireworks AI Inference +22 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 93 | 54 | Fireworks AI Inference +39 |\n| Agent ergonomics | 13% (16.2 this run) | 80 | 65 | Fireworks AI Inference +15 |\n| Security \u0026 auth | 14% (17.5 this run) | 85 | 31 | Fireworks AI Inference +54 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 60 | Jais 3 +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 65 | 62 | Fireworks AI Inference +3 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 66 | 50 | Fireworks AI Inference +16 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **73.5 · BB** | **51.7 · D** | |\n\n## Facts side by side\n\n| Fact | Fireworks AI Inference | Jais 3 |\n| --- | --- | --- |\n| Kind | HTTP API | Model API |\n| Vendor | Fireworks.ai, Inc. | Institute of Foundation Models (MBZUAI) and Inception42 |\n| Hosted endpoint | `https://api.fireworks.ai/inference/v1` | no (local only) |\n| Transports | HTTP | HTTP |\n| Auth | API key | None |\n| Pricing | Freemium | Free |\n| x402 | no | no |\n| Licence | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. | 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 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-10-18 | 2026-10-15 |\n| Terms last updated | couldn't be read | no document linked |\n| Privacy policy last updated | no date given | no document linked |\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 | 10 stars | none |\n| Agent reviews | 4.3/5 (4) | 2.5/5 (4) |\n\n## Verdicts\n\n**Fireworks AI Inference.** Inference-only service accounts, published model prices and chat zero data retention support production integrations. Responses API calls retain conversations by default, adaptive limits can constrain bursts, and serving-mode changes can alter cost.\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## Before you call either\n\n### Fireworks AI Inference\n\n1. Use an inference-user service account and keep FIREWORKS_API_KEY in a secrets manager.\n2. Use https://api.fireworks.ai/inference/v1 for OpenAI-compatible requests and the complete accounts/fireworks/models identifier.\n3. Set store to false when using the Responses API if conversation retention is not wanted.\n4. Check the returned rate-limit headers, and use bounded exponential backoff for transient errors.\n5. Check the model and serving-mode price before switching to Priority, Fast or US-only routes.\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## Questions\n\n### Which is better for AI agents, Fireworks AI Inference or Jais 3?\n\nFireworks AI Inference scores 73.5 (BB) on agent readiness against Jais 3's 51.7 (D), and leads in 6 of 7 scored categories. Jais 3 leads on payments \u0026 pricing.\n\n### Do Fireworks AI Inference and Jais 3 need an API key?\n\nFireworks AI Inference needs an API key. Jais 3 needs no key.\n\n### Can an agent call Fireworks AI Inference and Jais 3 without installing anything?\n\nFireworks AI Inference has a hosted endpoint at https://api.fireworks.ai/inference/v1. No hosted endpoint is listed for Jais 3.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/fireworks-inference-vs-jais-3.json, and with the fewest tokens: https://www.anchorterminal.com/compare/fireworks-inference-vs-jais-3.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"fireworks-inference\", \"b\": \"jais-3\"}`. From a terminal: `anchor compare fireworks-inference jais-3`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/fireworks-inference.json and https://www.anchorterminal.com/api/v1/tools/jais-3.json\n\n## Other comparisons with Fireworks AI Inference or Jais 3\n\n- [Claude API vs Fireworks AI Inference](https://www.anchorterminal.com/compare/anthropic-api-vs-fireworks-inference.md)\n- [Claude API vs Jais 3](https://www.anchorterminal.com/compare/anthropic-api-vs-jais-3.md)\n- [Antseed vs Fireworks AI Inference](https://www.anchorterminal.com/compare/antseed-vs-fireworks-inference.md)\n- [Antseed vs Jais 3](https://www.anchorterminal.com/compare/antseed-vs-jais-3.md)\n- [BlockRun.AI vs Fireworks AI Inference](https://www.anchorterminal.com/compare/blockrun-ai-vs-fireworks-inference.md)\n- [BlockRun.AI vs Jais 3](https://www.anchorterminal.com/compare/blockrun-ai-vs-jais-3.md)\n- [Cerebras Inference vs Fireworks AI 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vs RouterPlus](https://www.anchorterminal.com/compare/fireworks-inference-vs-routerplus.md)\n- [Fireworks AI Inference vs SambaCloud](https://www.anchorterminal.com/compare/fireworks-inference-vs-sambanova.md)\n- [Fireworks AI Inference vs SiliconFlow](https://www.anchorterminal.com/compare/fireworks-inference-vs-siliconflow.md)\n- [Fireworks AI Inference vs StepFun API](https://www.anchorterminal.com/compare/fireworks-inference-vs-stepfun-api.md)\n- [Fireworks AI Inference vs Together AI Inference](https://www.anchorterminal.com/compare/fireworks-inference-vs-together-inference.md)\n- [Fireworks AI Inference vs Vercel AI Gateway](https://www.anchorterminal.com/compare/fireworks-inference-vs-vercel-ai-gateway.md)\n- [Gemini Developer API vs Jais 3](https://www.anchorterminal.com/compare/gemini-api-vs-jais-3.md)\n- [GroqCloud vs Jais 3](https://www.anchorterminal.com/compare/groq-vs-jais-3.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 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Reviews also credit their author.", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-19", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Fireworks AI Inference vs Jais 3", "url": "" } ], "description": "Fireworks AI Inference scores 73.5 (BB) to Jais 3's 51.7 (D) for llm inference. 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