Firefunction Nano on MMMU: score, rank and what it means
Firefunction Nano scores 56.1 on MMMU, placing it #486 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.
Score distribution
The chart shows the top 10 models on MMMU, 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-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 4 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 5 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 6 | Grok 4 Pro | xAI | 1000000 | $19.00 | 85.4 |
| 7 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 8 | Claude Sonnet 4.5 Pro | Anthropic | 1000000 | $18.73 | 86.7 |
| 9 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 10 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
What this score means
On MMMU, Firefunction Nano sits at #486 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 30.8 points. The median model in this index scores 70.0, which puts Firefunction Nano below the midpoint.
Fireworks AI models average 65.3 on this benchmark. Firefunction Nano is 9.2 points below that provider line, so it is a weaker result than the average Fireworks AI model.
Among mid-range models, the average is 65.0. Firefunction Nano is 8.9 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 56.1 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 $3.07 per million input tokens, Firefunction Nano is below the median input price of $4.00 across the 600 models scored on MMMU. 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 |
|---|---|---|---|---|
| Qwen3-Coder 7B | Alibaba Cloud | 32768 | $1.24 | 59.6 |
| DeepSeek-V3.2 1.5B | DeepSeek | 4096 | $1.02 | 56.9 |
| DeepSeek-R1 1.5B | DeepSeek | 16384 | $1.04 | 56.6 |
| Pythia Instruct | EleutherAI | 8192 | $1.41 | 60.8 |
| Firefunction Nano | Fireworks AI | 16384 | $3.07 | 58.1 |
| Llama 3 Anyscale 7B | Anyscale | 4096 | $0.98 | 56.2 |
| Llama 3.3 Groq 7B | Groq | 16384 | $1.01 | 56.7 |
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 | |
| MATH-500 | 61.3 | 450 | 25th | |
| 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 | |
| Arena Elo | 1265.6 | 467 | 22th |
FAQ
What score does Firefunction Nano get on MMMU?
Firefunction Nano scores 56.1 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.
How does Firefunction Nano rank on MMMU?
It ranks #486 of 600 models, in the 19th percentile. The leader is GPT-5.2 Max at 86.9.
Is Firefunction Nano good at MMMU?
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 MMMU score calculated?
MMMU is a multimodal 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.