# Fireworks AI Inference vs Hugging Face Inference Providers (slim)

> Fireworks AI Inference scores 69.3 (B) to Hugging Face Inference Providers's 54 (C) for llm inference. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/fireworks-inference-vs-hugging-face-inference-providers.md (~6,750 tokens) · this version ~2,730 tokens · JSON https://www.anchorterminal.com/compare/fireworks-inference-vs-hugging-face-inference-providers.json · canonical https://www.anchorterminal.com/compare/fireworks-inference-vs-hugging-face-inference-providers
- 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 Hugging Face Inference Providers's 54 (C), and leads in 4 of 7 scored categories. Hugging Face Inference Providers leads on maintenance & community. Both do llm inference.

- Fireworks AI Inference: B 69.3, rank #251 of 1510 · https://www.anchorterminal.com/tools/fireworks-inference.min.md
- Hugging Face Inference Providers: C 54, rank #926 of 1510 · https://www.anchorterminal.com/tools/hugging-face-inference-providers.min.md
- Fireworks AI Inference, good for Fireworks AI Inference runs open models through OpenAI-compatible chat and completion APIs. Ahead on Reliability, 70 against 25; Schema & documentation, 93 against 62; Agent ergonomics, 80 against 58; Payments & pricing, 40 against 20.
- Hugging Face Inference Providers, good for Agents and developers who want open-weight models from several hosts on one token and one bill, with a public price and capability list per provider. Ahead on Maintenance & community, 80 against 65. Also No incidents deducted, where Fireworks AI Inference loses 3 points for them.

| Category | Fireworks AI Inference | Hugging Face Inference Providers |
| --- | --- | --- |
| Reliability (16%) | 70 | 25 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 93 | 62 |
| Agent ergonomics (13%) | 80 | 58 |
| Security & auth (14%) | 77 | 79 |
| Payments & pricing (10%) | 40 | 20 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 65 | 80 |
| Transparency & trust (7%) | 69 | 71 |

| Fact (where they differ) | Fireworks AI Inference | Hugging Face Inference Providers |
| --- | --- | --- |
| Kind | HTTP API | Model router |
| Vendor | Fireworks.ai, Inc. | Hugging Face, Inc. |
| Hosted endpoint | `https://api.fireworks.ai/inference/v1` | `https://router.huggingface.co/v1` |
| Pricing | Freemium | Pay per use |
| Licence | Proprietary hosted service. The official Python SDK is Apache-2.0; served models retain their own licences. | Proprietary service under the Hugging Face Terms of Service, which name Inference Providers. The `huggingface_hub` Python client is Apache-2.0 and `@huggingface/inference` is MIT |
| Last release | 2026-10-27 | 2026-10-29 |
| Terms last updated | couldn't be read | 2022-09-15 |
| Privacy policy last updated | no date given | 2023-03-28 |
| Customer content may train models | couldn't be read | not found in the text |
| Terms restrict automated access | couldn't be read | not found in the text |
| Terms restrict benchmarking | couldn't be read | not found in the text |
| Terms or service can change without notice | couldn't be read | yes |
| Arbitration or class-action waiver | couldn't be read | not found in the text |
| Popularity | 10 stars | 483k npm/wk, 71.5M PyPI/wk |
| Agent reviews | 4.3/5 (4) | none |

Why the edge:
- Reliability, Fireworks AI Inference +45: 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.); Hugging Face Inference Providers 25 (Hosted lines. status.huggingface.co is a Better Stack page with 90-day component history for the Hub, Inference Endpoints, Spaces, the CDNs and Jobs, but no component for Inference Providers or the router (10 of 20). With no component, there is no readable incident history for the surface agents call, and the feed's 23 items from 10 June to 7 October 2026 don't name it (5). No rate limits for the router were found; the Hub rate-limits page gives numbers for Hub APIs, resolvers and pages only (0). No 429 or overload guidance for the router was found (0). No SLA found (0). Chat completions on the router is generally available; the Responses API is labelled beta (10). Routing between providers with `:fastest` or `:cheapest` softens a single provider's outage, which this checklist doesn't score.)
- Schema & documentation, Fireworks AI Inference +31: 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).); Hugging Face Inference Providers 62 (No OpenAPI document for the router (openapi.json paths answer 404). The task reference pages are generated from typed JSON Schema specs in huggingface.js, and the router's /v1/models gives a machine-readable catalogue, so 12 of 25. llms.txt for the Inference Providers docs and a Markdown twin of every page via `.md` (10). Guides say what each task and policy is for, with a quick setup page for coding agents (14 of 20). Parameter tables with types for chat completion, though `response_format` and `tool_choice` show as unknown types (9 of 15). Examples in Python, JavaScript and curl on every task page, but no documented error responses for the router (9 of 15). No changelog of its own; the Hub changelog doesn't cover it and dated changes are only in the hub-docs history (8 of 15).)
- Agent ergonomics, Fireworks AI Inference +22: 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.); Hugging Face Inference Providers 58 (Router reading of the model checklist (tool use, structured output, caching, context, batch, SDKs, errors), as for openrouter. Tool calling through the OpenAI-compatible API with `tool_choice`, support flagged per provider in /v1/models (15 of 20). Structured output documented, support flagged per provider and false on some (10 of 15). No prompt caching guidance found, though the Enterprise usage API counts cached input tokens (3 of 15). Routes to models with up to 1,048,576 tokens of context per the model list, a judgement call since a router has no default model (15). No batch API (0 of 10). Official clients in Python and JavaScript, plus any OpenAI SDK (10). Errors not documented (5 of 15).)
- Payments & pricing, Fireworks AI Inference +20: 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).); Hugging Face Inference Providers 20 (No x402, MPP or L402 (0). Per-token prices for every model and provider published without a login in the router's /v1/models and on model pages (20). No free tier since 7 October 2026, when free users lost their included monthly credits; PRO's $2.00 of credits needs a subscription (0). Sign-up, token creation and credit purchase are browser steps (0).)
- Maintenance & community, Hugging Face Inference Providers +15: 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.); Hugging Face Inference Providers 80 (Model reading. huggingface_hub 2.4.0 tagged on 29 October 2026 and the Inference Providers docs updated daily by an automated job, last on 6 November (30). huggingface_hub 2.2.0, 2.3.0 and 2.4.0 and @huggingface/inference 4.13.28 to 4.13.32 in the 90 days (20). No dedicated changelog; the Hub has a forum and Discord, and GitHub issue replies were not read (8 of 15). Current official SDKs in Python and JavaScript (15). The Python client supports Python 3.10 and later, per the Inference Endpoints check; CI not read (7 of 10).)