Firefunction Nano on MATH-500: score, rank and what it means
Firefunction Nano scores 61.3 on MATH-500, placing it #450 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.
Score distribution
The chart shows the top 10 models on MATH-500, with Firefunction Nano highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg 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 Nano sits at #450 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 35.4 points. The median model in this index scores 76.0, which puts Firefunction Nano below the midpoint.
Fireworks AI models average 69.4 on this benchmark. Firefunction Nano is 8.1 points below that provider line, so it is a weaker result than the average Fireworks AI model.
Among mid-range models, the average is 70.0. Firefunction Nano is 8.7 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 61.3 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 $3.07 per million input tokens, Firefunction Nano is below 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.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| SmolLM3 Chat | Hugging Face | 16384 | $1.61 | 62.1 |
| Qwen3-Coder 7B | Alibaba Cloud | 32768 | $1.24 | 59.6 |
| Reka Flash Nano | Reka AI | 16384 | $3.93 | 61.0 |
| Llama 4 Scout 7B | Meta AI | 32768 | $1.30 | 60.0 |
| Firefunction Nano | Fireworks AI | 16384 | $3.07 | 58.1 |
| Zephyr Chat | Hugging Face | 4096 | $1.49 | 61.3 |
| Mistral Large 3 8B | Mistral AI | 16384 | $1.62 | 61.6 |
Other benchmarks for Firefunction Nano
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 64.0 | 470 | 22th | |
| GPQA Diamond | 52.5 | 494 | 18th | |
| SWE-bench Verified | 42.3 | 499 | 17th | |
| HumanEval | 62.4 | 464 | 23th | |
| AIME 2025 | 45.3 | 496 | 17th | |
| LiveCodeBench | 46.9 | 476 | 21th | |
| IFEval | 69.4 | 469 | 22th | |
| TruthfulQA | 65.5 | 453 | 25th | |
| HellaSwag | 73.8 | 458 | 24th | |
| MMMU | 56.1 | 486 | 19th | |
| Arena Elo | 1265.6 | 467 | 22th |
FAQ
What score does Firefunction Nano get on MATH-500?
Firefunction Nano scores 61.3 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.
How does Firefunction Nano rank on MATH-500?
It ranks #450 of 600 models, in the 25th percentile. The leader is GPT-5.2 Max at 96.7.
Is Firefunction Nano good at MATH-500?
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 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 Nano cost?
Firefunction Nano costs $3.07 per million input tokens and $12.50 per million output tokens.