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Fireworks: Ember-1 API Pricing

Fireworks: Ember-1 costs $3.00 per 1M input tokens and $15.00 per 1M output tokens (cache reads: $0.300). Context window: 1.0M. Prices verified 2026-10-21 · source

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Price history
2026-09-24 → 2026-10-21 · 59 daily snapshots
inputoutput

Rebuilt daily from our snapshot archive — the chart appears once a model has 5+ snapshots of history.

Pricing behavior
Stable — no price moves across our 59 daily snapshots (2026-08-23 → 2026-10-21).

From our own daily snapshot archive — independent of provider announcements.

Input / 1M tokens
$3.00
Output / 1M tokens
$15.00
Context window
1.0M
Max output
944K

Token economics

Token typePricevs base input
Standard input$3.00—
Cache read$0.300−90%
Output$15.00—

Prompt caching stores repeated context server-side: reads cost far less, but writes carry a one-time premium.

Reasoning behavior
Mode: On by default (toggleable)
Effort levels:maxhighlownone

Higher effort = deeper thinking = more reasoning tokens billed as output.

What would Fireworks: Ember-1 cost you per month?

WorkloadRequests/moAvg tokens (in/out)Est. monthly cost
Light chatbot10,000800 / 400$84.00
Coding agent5,0008,000 / 2,000$270.00
RAG pipeline30,0004,000 / 500$585.00
Doc summarizer2,00020,000 / 1,000$150.00

Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.

About Fireworks: Ember-1

Ember-1 is a specialized reasoning model from Fireworks Research, built on [Kimi K3](https://openrouter.ai/moonshotai/kimi-k3). It is designed to make every token go further: it produces shorter reasoning traces, using roughly 40%...

Compare Fireworks: Ember-1 with

Popular head-to-heads — see all on the comparisons index.

Frequently asked questions

How much does Fireworks: Ember-1 cost?

Fireworks: Ember-1 costs $3.00 per 1M input tokens and $15.00 per 1M output tokens; cached input tokens cost $0.300 per 1M. Verified 2026-10-21 — provider source.

What is the context window?

1.0M tokens, with up to 944K output tokens per response. That's roughly 1311 pages of text in a single request.

Does it support prompt caching?

Yes — cached input is $0.300/1M, about 90% cheaper than standard input. Agents and RAG workloads with repeated context benefit most.

What's a cheaper alternative?

ScaleDown: Summarize saves about 99% on a typical workload with comparable quality.

Official resources