Reasoning · Fireworks AI

Firesearch on GPQA Diamond: score, rank and what it means

Firesearch scores 65.0 on GPQA Diamond, placing it #359 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
65.0
0–100 scale
Rank
#359
of 600
Percentile
40th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
22.0
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Firesearch highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Firesearch sits at #359 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 22.0 points. The median model in this index scores 68.8, which puts Firesearch below the midpoint.

Fireworks AI models average 63.3 on this benchmark. Firesearch is 1.7 points above that provider line, so it is a stronger result than the average Fireworks AI model.

Among mid-range models, the average is 62.9. Firesearch is 2.1 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 65.0 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $7.03 per million input tokens, Firesearch is above the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Molmo Allen Institute for AI 32768 $2.49 68.5
Firesearch Max Fireworks AI 8192 $7.80 69.9
Nemotron Nano NVIDIA 8192 $2.24 66.6
OLMo 2 Allen Institute for AI 65536 $2.99 71.0
Firesearch Fireworks AI 32768 $7.03 68.5
Grok 3 Nano xAI 8192 $7.12 67.8
Qwen3-Max Nano Alibaba Cloud 65536 $8.31 71.7

Other benchmarks for Firesearch

BenchmarkScoreRankPercentileRelative
MMLU-Pro 71.6 384 36th
SWE-bench Verified 55.6 380 37th
HumanEval 73.6 365 39th
MATH-500 68.4 394 34th
AIME 2025 59.1 393 35th
LiveCodeBench 57.1 393 35th
IFEval 78.1 367 39th
TruthfulQA 75.1 328 45th
HellaSwag 82.4 338 44th
MMMU 67.4 353 41th
Arena Elo 1353.2 358 40th

FAQ

What score does Firesearch get on GPQA Diamond?

Firesearch scores 65.0 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Firesearch rank on GPQA Diamond?

It ranks #359 of 600 models, in the 40th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Firesearch good at GPQA Diamond?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.

How is the GPQA Diamond score calculated?

GPQA Diamond is a reasoning benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Firesearch cost?

Firesearch costs $7.03 per million input tokens and $29.81 per million output tokens.

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