Reasoning · Fireworks AI

Firefunction Pro on GPQA Diamond: score, rank and what it means

Firefunction Pro scores 66.1 on GPQA Diamond, placing it #342 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
66.1
0–100 scale
Rank
#342
of 600
Percentile
43th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
20.9
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Firefunction Pro 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, Firefunction Pro sits at #342 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 20.9 points. The median model in this index scores 68.8, which puts Firefunction Pro below the midpoint.

Fireworks AI models average 63.3 on this benchmark. Firefunction Pro is 2.8 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. Firefunction Pro is 3.2 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 66.1 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 $9.05 per million input tokens, Firefunction Pro 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
DBRX Base Databricks 32768 $2.63 69.1
Llama 3 Replicate Base Replicate 65536 $3.15 72.1
Llama 3 Modal Base Modal 16384 $3.21 72.2
Claude Haiku 4.5 Mini Anthropic 16384 $8.76 71.6
Firefunction Pro Fireworks AI 16384 $9.05 72.9
Mixtral Groq Groq 16384 $3.37 73.1
Auto Reasoning OpenRouter 65536 $8.39 71.5

Other benchmarks for Firefunction Pro

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.6 315 48th
SWE-bench Verified 60.9 303 50th
HumanEval 76.5 319 47th
MATH-500 74.6 337 44th
AIME 2025 71.4 231 62th
LiveCodeBench 66.0 274 54th
IFEval 82.6 256 57th
TruthfulQA 74.8 333 45th
HellaSwag 85.0 242 60th
MMMU 68.4 338 44th
Arena Elo 1358.8 347 42th

FAQ

What score does Firefunction Pro get on GPQA Diamond?

Firefunction Pro scores 66.1 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Firefunction Pro rank on GPQA Diamond?

It ranks #342 of 600 models, in the 43rd percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Firefunction Pro 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 Firefunction Pro cost?

Firefunction Pro costs $9.05 per million input tokens and $49.41 per million output tokens.

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