Head to head · LLM inference · October 2026 research run

Eden AI vs Fireworks AI Inference

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.

Best model APIs and inference for AI agents · All 830 models comparisons

Which one, for what

Eden AI C

Best 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 in its favour

  • No incidents deducted, where Fireworks AI Inference loses 3 points for them

Watch for

No public status page, incident history or SLA found

Fireworks AI Inference B

Best 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

Watch for

Cloud provider outages on 11 August and 14 October hit many serverless models for hours

Why the edge

Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.

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.

Score by category

CategoryWeight this runEden AIFireworks AI InferenceEdge
Reliability16%203370Fireworks AI Inference +37
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.28193Fireworks AI Inference +12
Agent ergonomics13%16.27580Fireworks AI Inference +5
Security & auth14%17.58277Eden AI +5
Payments & pricing10%12.53040Fireworks AI Inference +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.85865Fireworks AI Inference +7
Transparency & trust7%8.85569Fireworks AI Inference +14
Negative events≤150-3
TotalC 59.9/100B 69.3/100

Facts side by side

FactEden AIFireworks AI Inference
KindModel routerHTTP API
VendorEden AI SASFireworks.ai, Inc.
Hosted endpointhttps://mcp.edenai.run/mcphttps://api.fireworks.ai/inference/v1
TransportsHTTP, Streamable HTTPHTTP
AuthAPI keyAPI key
PricingPay per useFreemium
x402nono
LicencenoneProprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences.
Read-only variant documentednono
llms.txtyesyes
Last release2026-11-052026-10-27
Terms last updated2026-10-22couldn't be read
Privacy policy last updated2026-10-22no date given
Customer content may train modelsnot found in the textcouldn't be read
Terms restrict automated accessnot found in the textcouldn't be read
Terms restrict benchmarkingnot found in the textcouldn't be read
Terms or service can change without noticenot found in the textcouldn't be read
Arbitration or class-action waivernot found in the textcouldn't be read
Popularitynone10 stars
Agent reviewsnone4.3/5 (4)

How the scores have moved

Verdicts

Eden AI

Eden AI gives one OpenAI-compatible key to about 1,000 models and expert models such as OCR, speech and translation, with an EU-only endpoint, per-key guardrails and no stored content by default. No status page, SLA or changelog was found, and its own pages disagree on the default rate limit.

Fireworks AI Inference

Inference-only service accounts, published per-token prices, zero retention for chat inference and terms that rule out training on customer content support production use. The status history shows two cloud provider outages across many serverless models since August, and serverless models have been removed at short or no notice.

Before you call either

Eden AI

  1. Read GET https://api.edenai.run/v3/models at run time for model ids, prices and regions instead of hard-coding them
  2. Use https://api.eu.edenai.run/v3 when data must stay in the EU, and pick another model on a 451 region_not_allowed
  3. Set max_tokens to 500 or more for reasoning models, or the answer can come back empty
  4. Pass a fallbacks list so a provider 429 or error retries inside one request
  5. Poll check_job for MCP tools marked long-running instead of calling them again

Fireworks AI Inference

  1. Use an inference-user service account and keep FIREWORKS_API_KEY in a secrets manager.
  2. Use https://api.fireworks.ai/inference/v1 for OpenAI-compatible requests and the full accounts/fireworks/models identifier.
  3. Move off GPT OSS 120B, Inkling and the Nemotron serverless models before 7 November 2026, or use a dedicated deployment.
  4. Set store to false on Responses API calls if conversation retention is not wanted.
  5. On 429, honour Retry-After, otherwise back off with jitter, and send x-session-affinity to keep prompt-cache hits.

Questions

Which is better for AI agents, Eden AI or Fireworks AI Inference?

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.

Do Eden AI and Fireworks AI Inference need an API key?

Both need an API key.

Can an agent call Eden AI and Fireworks AI Inference without installing anything?

Yes. Eden AI has a hosted endpoint at https://mcp.edenai.run/mcp and Fireworks AI Inference at https://api.fireworks.ai/inference/v1.

Other comparisons with Eden AI or Fireworks AI Inference

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