Firesearch Nano on MMMU: score, rank and what it means
Firesearch Nano scores 54.8 on MMMU, placing it #500 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 Firesearch 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, Firesearch Nano sits at #500 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 32.1 points. The median model in this index scores 70.0, which puts Firesearch Nano below the midpoint.
Fireworks AI models average 65.3 on this benchmark. Firesearch Nano is 10.5 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. Firesearch Nano is 10.2 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 54.8 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 $2.49 per million input tokens, Firesearch 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 |
|---|---|---|---|---|
| DBRX 8B | Databricks | 4096 | $0.82 | 54.1 |
| Pythia | EleutherAI | 32768 | $1.29 | 59.8 |
| Yi-Large 8B | 01.AI | 32768 | $0.88 | 56.1 |
| Llama 3 Baseten 7B | Baseten | 32768 | $0.87 | 55.3 |
| Firesearch Nano | Fireworks AI | 8192 | $2.49 | 55.6 |
| MiniMax-M2 1.5B | MiniMax | 16384 | $0.84 | 54.6 |
| Mixtral 7B | Mistral AI | 16384 | $0.70 | 54.1 |
Other benchmarks for Firesearch Nano
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 63.0 | 488 | 19th | |
| GPQA Diamond | 52.6 | 493 | 18th | |
| SWE-bench Verified | 40.0 | 521 | 13th | |
| HumanEval | 58.9 | 513 | 15th | |
| MATH-500 | 52.9 | 533 | 11th | |
| AIME 2025 | 45.7 | 492 | 18th | |
| LiveCodeBench | 41.5 | 529 | 12th | |
| IFEval | 66.5 | 509 | 15th | |
| TruthfulQA | 62.6 | 495 | 18th | |
| HellaSwag | 73.2 | 475 | 21th | |
| Arena Elo | 1229.9 | 526 | 12th |
FAQ
What score does Firesearch Nano get on MMMU?
Firesearch Nano scores 54.8 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.
How does Firesearch Nano rank on MMMU?
It ranks #500 of 600 models, in the 17th percentile. The leader is GPT-5.2 Max at 86.9.
Is Firesearch 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 Firesearch Nano cost?
Firesearch Nano costs $2.49 per million input tokens and $11.16 per million output tokens.