Firesearch Nano on MMLU-Pro: score, rank and what it means
Firesearch Nano scores 63.0 on MMLU-Pro, placing it #488 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.
Score distribution
The chart shows the top 10 models on MMLU-Pro, with Firesearch Nano highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 2 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 3 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 4 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 5 | Gemini 3 Pro Reasoning | Google DeepMind | 200000 | $19.69 | 87.5 |
| 6 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 7 | GPT-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 8 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 9 | GPT-5.2 Vision | OpenAI | 1000000 | $19.03 | 87.4 |
| 10 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
What this score means
On MMLU-Pro, Firesearch Nano sits at #488 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 28.6 points. The median model in this index scores 76.1, which puts Firesearch Nano below the midpoint.
Fireworks AI models average 71.6 on this benchmark. Firesearch Nano is 8.6 points below that provider line, so it is a weaker result than the average Fireworks AI model.
Among mid-range models, the average is 71.5. Firesearch Nano is 8.5 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 63.0 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 MMLU-Pro. 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 |
|---|---|---|---|---|
| Llama 4 Scout 7B | Meta AI | 32768 | $1.30 | 60.0 |
| DeepSeek-Coder 8B | DeepSeek | 32768 | $1.26 | 58.7 |
| Embed 4 Mini | Cohere | 4096 | $2.48 | 55.8 |
| Pythia | EleutherAI | 32768 | $1.29 | 59.8 |
| Firesearch Nano | Fireworks AI | 8192 | $2.49 | 55.6 |
| MiniMax-Text 7B | MiniMax | 16384 | $1.10 | 57.7 |
| Llama 3.1 Cerebras 7B | Cerebras | 32768 | $0.95 | 56.5 |
Other benchmarks for Firesearch Nano
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| 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 | |
| MMMU | 54.8 | 500 | 17th | |
| Arena Elo | 1229.9 | 526 | 12th |
FAQ
What score does Firesearch Nano get on MMLU-Pro?
Firesearch Nano scores 63.0 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.
How does Firesearch Nano rank on MMLU-Pro?
It ranks #488 of 600 models, in the 19th percentile. The leader is GPT-5.2 Pro at 91.6.
Is Firesearch Nano good at MMLU-Pro?
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 MMLU-Pro score calculated?
MMLU-Pro is a knowledge 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.