Claude Fable 5$22.000/MClaude Opus 4.8$11.000/MClaude Opus 4.7$11.000/MClaude Opus 4.6$11.000/MClaude Opus 4.5$33.000/MClaude Sonnet 3.7$6.600/MClaude Opus 3$33.000/MClaude 2.1$12.800/MClaude 2$12.800/MGPT-5.5$12.500/MGPT-5.2$5.425/MGPT-5.2-Codex$5.425/MGPT-5$3.875/MGPT-4.5$97.500/MGPT-4 Turbo Preview$16.000/MGPT-4$39.000/MGPT-4-32k$78.000/Mo3$19.000/Mo3-mini$2.090/Mo4-mini$2.090/Mo1$28.500/Mo1-mini$5.700/Mo1-preview$28.500/MGemini 3.5 Pro$5.000/MGemini 3.1 Pro$5.000/MGemini 3 Pro$5.000/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/MClaude Fable 5$22.000/MClaude Opus 4.8$11.000/MClaude Opus 4.7$11.000/MClaude Opus 4.6$11.000/MClaude Opus 4.5$33.000/MClaude Sonnet 3.7$6.600/MClaude Opus 3$33.000/MClaude 2.1$12.800/MClaude 2$12.800/MGPT-5.5$12.500/MGPT-5.2$5.425/MGPT-5.2-Codex$5.425/MGPT-5$3.875/MGPT-4.5$97.500/MGPT-4 Turbo Preview$16.000/MGPT-4$39.000/MGPT-4-32k$78.000/Mo3$19.000/Mo3-mini$2.090/Mo4-mini$2.090/Mo1$28.500/Mo1-mini$5.700/Mo1-preview$28.500/MGemini 3.5 Pro$5.000/MGemini 3.1 Pro$5.000/MGemini 3 Pro$5.000/MGemini 2.5 Pro$3.875/MGemini 1.5 Pro$2.375/MGemini 1.0 Ultra$12.000/MGemini 1.0 Pro$0.800/M
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Fireworks AIReasoning

DeepSeek-R1 (fw)

Reasoning

Open-weights reasoning model with chain-of-thought trained via RL. Comparable to o1 on math benchmarks at a fraction of the price.

DeepSeek-R1 (fw) is a reasoning AI model from Fireworks AI. It costs $3.000 per million input tokens and $8.000 per million output tokens (blended $4.500/M), with a 64K-token context window.

Profile inherited from upstream DeepSeek-R1 ↗ — this is a hosted variant of the same open-weights model.

Modalities textOfficial model page ↗Provider pricing ↗API docs ↗Compare with another model →Estimate monthly cost →
INPUT
$3.000/M
per million input tokens
OUTPUT
$8.000/M
per million output tokens
BLENDED 70/30
$4.500/M
default reference rate · how it's calculated →
CONTEXT
64K
64,000 tokens
What it's good at
  • Open-weights reasoning
  • Visible chain-of-thought
  • Math & code
  • Cheap
Typical use cases
  • Reasoning agents
  • Math/STEM tools
  • Self-hosted reasoning
Benchmarks
vs. best public score
Scores inherited from DeepSeek-R1 — this is a hosted variant of the same open-weights model, so the underlying benchmark scores are identical.
MMLU90%
Multitask academic knowledge across 57 subjects.
GPQA Diamond71%
Graduate-level science questions, "Google-proof".
MATH95%
High-school competition math problems.
HumanEval90%
Python function synthesis from docstrings.
SWE-bench Verified49%
Real GitHub issues solved end-to-end.
LMArena Elo1361 Elo
Crowd-sourced head-to-head preference Elo rating.
Hand-curated from each provider's published reports and public leaderboards. Methodology varies across sources — treat as directional rather than authoritative.
More from Fireworks AI
See all 7 →
Llama 3.1 405B (fw)
Serverless · 131K ctx
in $3.000/Mout $3.000/M
Mixtral 8x7B (fw)
Serverless · 32K ctx
in $0.200/Mout $0.200/M
Qwen2.5-72B (fw)
Balanced · 32K ctx
in $0.900/Mout $0.900/M
Llama 3.1 8B (fw)
Nano · 131K ctx
in $0.100/Mout $0.100/M
Yi-34B (fw)
Open · 4K ctx
in $0.900/Mout $0.900/M
Phind-CodeLlama-34B (fw)
Code · 16K ctx
in $0.800/Mout $0.800/M
Frequently asked questions

How much does DeepSeek-R1 (fw) cost?

DeepSeek-R1 (fw) costs $3.000 per million input tokens and $8.000 per million output tokens, for a blended reference rate of $4.500 per million tokens.

What is DeepSeek-R1 (fw)'s context window?

DeepSeek-R1 (fw) supports up to 64K tokens of context (64,000 tokens).

What is DeepSeek-R1 (fw) best for?

DeepSeek-R1 (fw) is well suited to Open-weights reasoning, Visible chain-of-thought and Math & code.

Who makes DeepSeek-R1 (fw)?

DeepSeek-R1 (fw) is developed and served by Fireworks AI.