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Fireworks AI
Fireworks AI
Fireworks AI's pricing page did not render numeric tier data on the scoring date. No per-unit price was found on the page; an agent has no direct way to estimate the cost of a single task. All advertised paths route to a sales conversation rather than a self-serve checkout. Public API documentation is reachable without an auth wall.
Pricing to seamlessly scale from idea to enterprise — DeepSeek V4 Pro is Live → Try it now.
Contact sales
How Fireworks AI scores on the agent-ready dimensions
Public pricing
0 / 15
Usage-based / metered
0 / 25
Self-serve checkout
0 / 15
Public API
15 / 15
Low / no minimum
0 / 10
Unauth automated payment
0 / 10
Bonus (machine-readable pricing)On top of /100 base
0 / 5
Total
17 / 100
Six-step check: can an agent actually buy from Fireworks AI?
Discover price
https://fireworks.ai/pricing — three-section tableSelect a plan
Serverless, fine-tuning, on-demand all distinct sectionsPay per task
Per-token serverless ratesAvoid a sales call
Serverless self-serve; enterprise gatedAPI docs without auth
https://docs.fireworks.ai publicEstimate cost upfront
Per-MTok rates with parameter-band bucketsPros and cons for AI agents
Observational summary written by xpay from the signals captured on 2026-05-03. Not a review of the product — only of its current pricing posture for agent buyers.- Pricing is publicly visible on an indexable page — agents can read tiers without scraping past auth.
- Per-unit billing is published, so an agent can budget for a single task before committing.
- API documentation is reachable without a login — discovery and integration can happen in one session.
- Per-unit rate is concrete enough that an agent can model expected spend before issuing a request.
- Some tiers are sales-led; the highest-capacity surfaces are not self-serve.
- No /.well-known/ai-pricing.json or equivalent machine-readable pricing manifest is published — agents must rely on HTML scraping.
- The pricing URL did not render numeric tier data on the scoring date — possibly a router or sales-led landing page.
How Fireworks AI could lift its score
Add a per-unit price (e.g. $X / 1K calls) to the pricing page so an agent can compute its own cost before committing.
| pricing_visible | false |
| headline_phrasing | Pricing to seamlessly scale from idea to enterprise — DeepSeek V4 Pro is Live → Try it now. |
| tier_count | 0 |
| lowest_paid_entry_usd | null |
| free_tier | false |
| free_tier_terms | null |
| per_unit_price | null |
| annual_required | false |
| self_serve_paid_tiers | 0 |
| sales_only_tiers | 1 |
| public_api_docs_url | https://docs.fireworks.ai/getting-started/introduction |
| api_docs_auth_walled | false |
| ai_pricing_json_present | false |
| agents_txt_present | false |
| anonymous_purchase_path | false |
| per_unit_classification | null |
| usage_headline_present | true |
| custom_tier_present | true |
| agent_friendly | {"ai_pricing_json":false,"agents_txt":false,"llms_txt":false,"sitemap_xml":true,"mcp_server_card":false,"agent_skills_index":false,"x402_supported":false} |
View raw extracted page text →
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See agent-ready picksFireworks AI
17
/ 100 (rubric v1.1)AI Inference
Pricing to seamlessly scale from idea to enterprise — DeepSeek V4 Pro is Live → Try it now.
0
No
Sales-led
0 / 1
Public
No
Not published
2026-05-03
Discovery files and protocols
Side-channel signals — informational, not part of the score. Each protocol is independent; adoption signals the publisher is thinking about agent buyers.ai-pricing.json
agents.txt
llms.txt
sitemap.xml
MCP Server Card
Agent Skills
x402 / MPP
Compare Fireworks AI with peers
Highest-scoring companies in the same category that an AI agent might evaluate as an alternative.Groq
87
OpenAI
81
RunPod
79
Replicate
78
Anthropic
76
Modal
76
DeepInfra
76
Together AI
74
Explore the Agent-Ready SaaS Index
25,480+ SaaS scored on agent-buyability — browse by readiness band, category, or jump straight to a pay-per-run tool on xpay.tools.
