Fireworks — pricing & performance
Models served
16
of 1,094 tracked models
Mean output speed
73
tokens per second, averaged over
11 measured endpoints
11 measured endpoints
Mean latency
1.4s
time to first token, averaged over
11 measured endpoints
11 measured endpoints
Cheapest blended
$0.13
per 1M tokens at a 3:1
input:output blend
input:output blend
Output speed on Fireworks
Output tokens per second for the 11 of 16 models on Fireworks with published throughput telemetry, the most recent figure OpenRouter publishes for each host. The full table below lists all 16, measured or not. Higher is better. We do not run these measurements ourselves.
The Known Good
16 models on Fireworks
Full leaderboard →
| Model | Creator | Input $/M | Output $/M | Blended | Speed | TTFT | Context |
|---|---|---|---|---|---|---|---|
|
|
DeepSeek | $0.14 | $0.28 | $0.17 | — | — | 1.05M |
|
|
DeepSeek | $0.22 | $0.66 | $0.33 | 64 | 0.9s | 1.05M |
|
|
DeepSeek | $0.22 | $0.66 | $0.33 | 147 | 0.8s | 1.05M |
|
|
DeepSeek | $1.20 | $1.20 | $1.20 | — | — | 1.05M |
|
|
DeepSeek | $1.32 | $3.96 | $1.98 | 59 | 1.3s | 1.05M |
|
|
Meta | $0.35 | $1.50 | $0.64 | 54 | 0.9s | 131k |
|
|
MiniMax | $0.30 | $1.20 | $0.53 | — | — | 197k |
|
|
Moonshot AI | $0.95 | $4.00 | $1.71 | 38 | 1.1s | 262k |
|
|
Moonshot AI | $0.95 | $4.00 | $1.71 | 56 | 0.8s | 262k |
|
|
Moonshot AI | $3.00 | $15.00 | $6.00 | 81 | 0.6s | 1.05M |
|
|
OpenAI | $0.070 | $0.30 | $0.13 | — | — | 131k |
|
|
Alibaba | $2.00 | $6.00 | $3.00 | 46 | 5.4s | 262k |
|
|
Z.ai | $1.40 | $4.40 | $2.15 | — | — | 203k |
|
|
Z.ai | $1.40 | $4.40 | $2.15 | 149 | 0.6s | 1.05M |
|
|
Z.ai | $1.40 | $4.40 | $2.15 | 58 | 1.0s | 1.05M |
|
|
Z.ai | $0.15 | $0.50 | $0.24 | 51 | 1.4s | 1.05M |
The Known Good
Source. Prices, endpoint availability and throughput for Fireworks are ingested from OpenRouter;
model metadata is enriched from models.dev. A blank cell means the figure was not published for that endpoint —
it never means zero. Blended price is (3 × input + output) ÷ 4, the same 3:1 blend used everywhere on this
site; see methodology. Quality scores are not provider-specific:
a model scores the same wherever it is hosted, so quality lives on the
model pages.