Mathematics · Fireworks AI

Firefunction on MATH-500: score, rank and what it means

Firefunction scores 76.7 on MATH-500, placing it #288 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
76.7
0–100 scale
Rank
#288
of 600
Percentile
52th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
20.0
points

Score distribution

The chart shows the top 10 models on MATH-500, with Firefunction highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Firefunction sits at #288 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 20.0 points. The median model in this index scores 76.0, which puts Firefunction above the midpoint.

Fireworks AI models average 69.4 on this benchmark. Firefunction is 7.3 points above that provider line, so it is a stronger result than the average Fireworks AI model.

Among mid-range models, the average is 70.0. Firefunction is 6.7 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 76.7 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 $8.16 per million input tokens, Firefunction is above the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3.1 Turbo Base Together AI 16384 $3.30 73.0
Mixtral Base Mistral AI 65536 $2.95 71.1
Nemotron 4 Base NVIDIA 8192 $3.29 73.0
Command R+ Chat Cohere 32768 $4.02 76.0
Firefunction Fireworks AI 16384 $8.16 72.3
Llama 3 Lambda Base Lambda 8192 $3.19 72.9
Firefunction Reasoning Fireworks AI 8192 $9.08 72.5

Other benchmarks for Firefunction

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.0 306 49th
GPQA Diamond 69.2 288 52th
SWE-bench Verified 60.6 314 48th
HumanEval 75.1 342 43th
AIME 2025 69.0 281 53th
LiveCodeBench 61.4 357 41th
IFEval 78.8 359 40th
TruthfulQA 73.6 362 40th
HellaSwag 84.0 281 53th
MMMU 70.8 277 54th
Arena Elo 1356.8 349 42th

FAQ

What score does Firefunction get on MATH-500?

Firefunction scores 76.7 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Firefunction rank on MATH-500?

It ranks #288 of 600 models, in the 52nd percentile. The leader is GPT-5.2 Max at 96.7.

Is Firefunction good at MATH-500?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the MATH-500 score calculated?

MATH-500 is a mathematics 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 cost?

Firefunction costs $8.16 per million input tokens and $41.40 per million output tokens.

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