Product

Fireworks Inference

by Fireworks AI

Product website
https://fireworks.ai
Documentation
https://docs.fireworks.ai
Pricing
https://docs.fireworks.ai/serverless/pricing
Categories
AI Inference / Model Serving ML Model Hosting / Deployment

Description

Inference and fine-tuning platform for open models, with developer documentation at docs.fireworks.ai.

AI-native score

How ready this product is for agents to use, on a 0–100 scale across four weighted dimensions. Security is one of them, so a high score is not a substitute for your own security or vendor-risk review. How is this scored?

Unrated. Only 35% of the scored decision fields are researched, so the grade is held until more are confirmed. The breakdown below shows what's been scored.

Integration3/10Trust3/6Portability2/4Security2/4Tier C43/100
Component Raw Weight Contribution
Integration 3/10 35% 10.5
Trust 3/6 30% 15.0
Portability 2/4 20% 10.0
Security 2/4 15% 7.5
Signals that fired
  • Integration: MCP server (+2) ; Command-line interface (+1)
  • Trust: Zero data retention (available, +1) ; No generative AI training (available, +1) ; Verified trust center (+1)
  • Portability: Standard protocol access (+1) ; No proprietary-SDK lock-in (+1)
  • Security: Compliance certifications (+1) ; Access controls — RBAC / ABAC (+1)
Signals not researched

These gaps cover the fields used in the AI-native score.

  • Integration surfaces: llms.txt, WebMCP, Headless signup, Agent2Agent (A2A) servers, Native connectors, API specs, Agent skills, Developer kits
  • Trust & data policy: Multi-factor authentication, Hard budget caps, Sandbox environment, Data export, Data import, Open standards, Documented provider swap, Self-hostable, Open source

Trust & data policy

Trust center
Vendor trust center
Zero data retention
Available
No generative AI training
Available
Standard protocol access
Yes
No proprietary-SDK lock-in
Yes

Not yet researched Multi-factor authentication, Hard budget caps, Sandbox environment, Data export, Data import, Open standards, Documented provider swap, Self-hostable, Open source

Security & compliance

Certifications and access controls this product reports on its own pages. We confirm the vendor lists each one; for certifications we don't audit the underlying report. Part of the 15% security score.

A shared trust or security page can support several certifications. We do not require separate public report links because reports may require login, vendor approval, or a nondisclosure agreement. Ask the vendor for reports and applicable coverage before a procurement decision. These listings expose no per-claim check date; the entry's updated date does not date the supporting evidence.

Compliance certifications

Access controls

RBAC

What it does

Jobs to be done

  • Deploy a model for inference

    Deploy a machine learning model as a hosted endpoint for inference requests.

    View 6 products

Integration surfaces

How an agent connects to this product and finds its documentation. The largest dimension of the AI-native score (35%).

MCP servers

Model Context Protocol endpoints an AI agent can connect to for this product's tools and data.

Command-line interfaces

Not yet researched llms.txt, WebMCP, Headless signup, Agent2Agent (A2A) servers, Native connectors, API specs, Agent skills, Developer kits

GPT OSS 120B Standard

Rate Unit price
GPT OSS 120B Standard $0.15 per 1,000,000 input tokens
GPT OSS 120B Standard $0.015 per 1,000,000 cached input tokens
GPT OSS 120B Standard $0.60 per 1,000,000 output tokens

Qwen3 8B embeddings

Rate Unit price
Qwen3 8B embeddings $0.10 per 1,000,000 input_tokens

Reviews

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RSS: approved reviews

Catalog activity

Track how this entry changes as proposals are opened and merged.

RSS: merged changes · RSS: open proposals

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Ready to decide?

Unrated · 35% researched. Grade withheld until more fields are verified.

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