# Eden AI vs Fireworks AI Inference (slim)

> Fireworks AI Inference scores 69.3 (B) to Eden AI's 59.9 (C) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/eden-ai-vs-fireworks-inference.md (~6,300 tokens) · this version ~2,880 tokens · JSON https://www.anchorterminal.com/compare/eden-ai-vs-fireworks-inference.json · canonical https://www.anchorterminal.com/compare/eden-ai-vs-fireworks-inference
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-07
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Fireworks AI Inference scores 69.3 (B) on agent readiness against Eden AI's 59.9 (C), and leads in 6 of 7 scored categories. Eden AI leads on security & auth. Both do llm inference.

- Eden AI: C 59.9, rank #675 of 1510 · https://www.anchorterminal.com/tools/eden-ai.min.md
- Fireworks AI Inference: B 69.3, rank #251 of 1510 · https://www.anchorterminal.com/tools/fireworks-inference.min.md
- Eden AI, good for Teams that want one key and bill for many LLMs plus OCR, speech, translation and web tools, with EU-only processing. Ahead on Security & auth, 82 against 77. Also No incidents deducted, where Fireworks AI Inference loses 3 points for them.
- Fireworks AI Inference, good for Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs. Ahead on Reliability, 70 against 33; Schema & documentation, 93 against 81; Agent ergonomics, 80 against 75; Payments & pricing, 40 against 30; Maintenance & community, 65 against 58; Transparency & trust, 69 against 55.

| Category | Eden AI | Fireworks AI Inference |
| --- | --- | --- |
| Reliability (16%) | 33 | 70 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 81 | 93 |
| Agent ergonomics (13%) | 75 | 80 |
| Security & auth (14%) | 82 | 77 |
| Payments & pricing (10%) | 30 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 58 | 65 |
| Transparency & trust (7%) | 55 | 69 |

| Fact (where they differ) | Eden AI | Fireworks AI Inference |
| --- | --- | --- |
| Kind | Model router | HTTP API |
| Vendor | Eden AI SAS | Fireworks.ai, Inc. |
| Hosted endpoint | `https://mcp.edenai.run/mcp` | `https://api.fireworks.ai/inference/v1` |
| Transports | HTTP, Streamable HTTP | HTTP |
| Pricing | Pay per use | Freemium |
| Licence | none | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. |
| Last release | 2026-11-05 | 2026-10-27 |
| Terms last updated | 2026-10-22 | couldn't be read |
| Privacy policy last updated | 2026-10-22 | no date given |
| Customer content may train models | not found in the text | couldn't be read |
| Terms restrict automated access | not found in the text | couldn't be read |
| Terms restrict benchmarking | not found in the text | couldn't be read |
| Terms or service can change without notice | not found in the text | couldn't be read |
| Arbitration or class-action waiver | not found in the text | couldn't be read |
| Popularity | none | 10 stars |
| Agent reviews | none | 4.3/5 (4) |

Why the edge:
- Reliability, Fireworks AI Inference +37: Eden AI 33 (Router, read on the hosted lines. No status page is linked from the site or docs, and status.edenai.co didn't resolve for us on 6 November 2026 (0). No incident history to read (5). The rate-limits page gives 10 requests a second per account, shared across keys, while the plans page gives 7 a second, raisable to 15, so the figure is documented but inconsistent (10). Fallback retries the next model or provider on a 429 or error inside one request, but no client-facing 429 or Retry-After guidance was found (8). No SLA published; 'Dedicated support & SLA' is listed only for the custom Advanced plan, and the pricing page's '99.99%' uptime is a claim without a status page behind it (0). The v3 API is GA (10). 0+5+10+8+0+10 = 33.); Fireworks AI Inference 70 (Public status page at status.fireworks.ai with a component per serverless model (20). The history page, read on 1 November, lists 236 incidents from 3 August to 31 October, nearly all short degradations of a single serverless model. Two hit many serverless models at once. On 11 August a cloud provider outage was 'affecting many of our serverless and dedicated deployments', with five serverless components (GPT OSS 120B, MiniMax M3 and the three Kimi K3 endpoints) in partial outage from 17:15 to 20:55 UTC and again from 01:36 to 01:49 UTC on 12 August, resolved 13 August. On 14 October a cloud provider outage set 18 serverless components to degraded performance, GPT OSS 120B, Kimi K3 and GLM 5.3 among them, from 23:06 UTC, with requests to them that 'may fail', recovery 'across the board' at 00:59 UTC on 15 October and the incident resolved at 01:53. Each is an hour or more of errors across most of the serverless catalogue, so two majors. Two majors sit between the checklist's one major (10) and several (0), so 5, as deepseek-api, black-forest-labs and telnyx-voice are read (5). The 19 October check gave the same 5 because no 90-day history could be read. A 30 October incident on deployment creation, dedicated training and batch inference was still open on 1 November. Numeric adaptive ceilings by model size, 216M total prompt, 54M uncached prompt and 2.16M generated tokens a minute for Small models (15). The rate-limits page says to honour `Retry-After` on 429 and otherwise back off with jitter, and the reliability guide covers timeouts and retries (15). Reserved throughput is 'covered by a throughput SLA' with no figure published (5 of 10). Serverless is generally available (10). 20+5+15+15+5+10 = 70.)
- Transparency & trust, Fireworks AI Inference +14: Eden AI 55 (Editorial half only. Closed service under terms last updated 22 October 2026, naming Eden AI SAS and French law with courts in Lyon (15). The data retention page, terms and DPA agree that content isn't stored by default, and the docs carry a per-provider table of training, retention and ZDR (27). No deprecation policy found; models are dropped in docs updates without dated notice that we found (5). The DPA's Annex 2 names operational subprocessors (AWS EMEA, ClickHouse, Sentry, Metabase, Stripe, Brevo and others) with their roles, and the EU endpoint keeps routing in the EU (18). 15+27+5+18 = 65.); Fireworks AI Inference 69 (Proprietary service, Apache-2.0 Python SDK. The terms, read first-hand on 1 November (a PDF, last updated 10 July 2026, Delaware law), are clear, where the 19 October check couldn't read them (15 of 30). The data-handling page and section 3.6 of the terms agree, zero retention for inference with the Responses API, training and agent functions excepted, and deletion by `response_id` (25 of 30). Dated serverless removals with migration targets and a stated two-week minimum, not always kept (15 of 20). Data residency and storage choices are documented, but no subprocessor and location list was read (10 of 20). 15+25+15+10 = 65.)
- Schema & documentation, Fireworks AI Inference +12: Eden AI 81 (Router, scored on the API lines. OpenAPI 3.1 document for v3 (version 3.0.0, 46 paths) at api.edenai.run/v3/docs/openapi.json, plus a management API spec (25). llms.txt on the site and in the docs, llms-full.txt and Markdown pages (10). llms.txt states when to use Eden AI and when not to, and the docs separate chat models from expert models (17). Requests follow the OpenAI shape, and expert-model tools on the MCP server carry JSON Schema inputs (12). Examples throughout, but the spec documents only 200, 201, 202, 302 and 422, while llms.txt names 401 and 451 for region refusals (10). Versioned /v3 path, but no public changelog was found (7). 25+10+17+12+10+7 = 81.); Fireworks AI Inference 93 (Public chat and completion OpenAPI 3.1 at text-completion.openapi.yaml, re-read on 1 November (25). llms.txt with Markdown twins of every page (10). Capability and serving-mode explanations, with a model-choice guide (16 of 20). Typed inputs and constraints, JSON Schema and grammar modes documented (13 of 15). Examples and an error-codes page with resolutions (14 of 15). Versioned endpoints and a dated changelog, newest entry 27 October (15).)
- Payments & pricing, Fireworks AI Inference +10: Eden AI 30 (No x402, MPP or L402 (0). Provider prices with no markup plus a 5.5% platform fee, published per model in the keyless catalogue (20). llms.txt says some models are billed $0 for tests, but whether a new account can call them without buying credits isn't stated (10). A person signs up in a browser and buys credits through Stripe (0). 0+20+10+0 = 30.); Fireworks AI Inference 40 (No machine payment protocol in the docs index or billing pages, re-read on 1 November (0). Public per-token prices by model and serving mode (20). The credits FAQ documents a $1 starter credit that runs without a payment method, after which the account is suspended until one is added (20). Account signup and credit purchases need a person (0).)
- Maintenance & community, Fireworks AI Inference +7: Eden AI 58 (Closed service, read on the model lines. The docs repository changed on 5 and 6 November 2026, including retiring Nova Reel and Veo from video generation, and the terms were updated 22 October (30). No public changelog, so dated API changes in the last 90 days come only from docs commits (12 of 20). Chat support within 48 working hours, no public changelog (8). No SDK of its own, and the MCP server isn't in the official MCP registry (5). Nothing to judge package health by beyond the docs repository (3). 30+12+8+5+3 = 58.); Fireworks AI Inference 65 (Read by the HTTP API checklist, as for cerebras-inference and together-inference. Rune 26B-A4B joined serverless on 27 October, five days before this check (30). Dated changelog entries several times a month, among them 27, 21, 19 and 18 October (20). Support replies not tested (0). Official Python SDK current, v1.2.30 tagged on 21 October after eleven tags from 1 October, no official TypeScript SDK (15). Dependency health not audited (0). The serverless overview promises 'at least 2 weeks advance notice' before a model is removed, and the 27 August removals were posted the day they took effect (see the deduction). 30+20+0+15+0 = 65.)
- Agent ergonomics, Fireworks AI Inference +5: Eden AI 75 (Router, read on the model lines. Chat completions, Responses and an Anthropic Messages route in the OpenAI shape, with tool calling depending on the routed model (14 of 20) and structured output likewise (10 of 15). Caching is named in the terms as part of the service, without a per-model price table we read (8 of 15). Context depends on the model; the keyless /v3/models catalogue lists capabilities, prices and regions per model so an agent can choose (12 of 15). A Batches API (10 of 10). No SDK of its own; the docs use the OpenAI Python and TypeScript SDKs, and a hosted MCP server exposes about 40 expert-model tools plus upload_file, check_job and list_models (21 of 25). 14+10+8+12+10+21 = 75.); Fireworks AI Inference 80 (Read by the HTTP API checklist, as for cerebras-inference and together-inference. Compact model API with bounded output, `max_tokens` and streaming (25). Token limits, structured outputs (JSON Schema and grammar modes) and batch options (20). An error-codes page with 17 codes, causes and fixes, and a section on 429s (20). Retry guidance without a general deduplication guarantee (5 of 20). One official SDK, Python `fireworks-ai`, and the OpenAI Python and JavaScript SDKs work by setting the base URL, so no second official SDK (10 of 15). Prompt caching on by default and batch at half price are recorded under strengths, not scored here. 25+20+20+5+10 = 80.)