Firesearch Max on HumanEval: score, rank and what it means
Firesearch Max scores 72.9 on HumanEval, placing it #373 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.
Score distribution
The chart shows the top 10 models on HumanEval, with Firesearch Max 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 | Gemini 3 Pro Pro | Google DeepMind | 200000 | $19.80 | 87.3 |
| 3 | o4 Max | OpenAI | 2000000 | $19.51 | 86.2 |
| 4 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 5 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 6 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 7 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 8 | Grok 4 Max | xAI | 2000000 | $19.70 | 86.6 |
| 9 | GPT-5.2 Turbo | OpenAI | 1000000 | $20.73 | 87.4 |
| 10 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
What this score means
On HumanEval, Firesearch Max sits at #373 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 23.9 points. The median model in this index scores 77.4, which puts Firesearch Max below the midpoint.
Fireworks AI models average 71.5 on this benchmark. Firesearch Max is 1.4 points above that provider line, so it is a stronger result than the average Fireworks AI model.
Among mid-range models, the average is 71.5. Firesearch Max is 1.4 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 72.9 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 $7.80 per million input tokens, Firesearch Max is above the median input price of $4.00 across the 600 models scored on HumanEval. 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 |
|---|---|---|---|---|
| Yi-Large Base | 01.AI | 16384 | $2.78 | 70.3 |
| Arctic | Snowflake | 8192 | $2.72 | 68.8 |
| Phi-3.5 Base | Microsoft | 65536 | $2.24 | 66.6 |
| Gemini 3 Flash Nano | Google DeepMind | 32768 | $7.56 | 69.4 |
| Firesearch Max | Fireworks AI | 8192 | $7.80 | 69.9 |
| Mixtral Turbo Base | Together AI | 32768 | $2.53 | 69.7 |
| Nemotron Nano Instruct | NVIDIA | 32768 | $2.33 | 67.4 |
Other benchmarks for Firesearch Max
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 72.2 | 382 | 36th | |
| GPQA Diamond | 65.2 | 356 | 41th | |
| SWE-bench Verified | 61.0 | 297 | 51th | |
| MATH-500 | 73.0 | 358 | 40th | |
| AIME 2025 | 62.5 | 370 | 38th | |
| LiveCodeBench | 63.7 | 327 | 46th | |
| IFEval | 78.0 | 368 | 39th | |
| TruthfulQA | 71.7 | 384 | 36th | |
| HellaSwag | 81.1 | 366 | 39th | |
| MMMU | 67.3 | 355 | 41th | |
| Arena Elo | 1361.1 | 341 | 43th |
FAQ
What score does Firesearch Max get on HumanEval?
Firesearch Max scores 72.9 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.
How does Firesearch Max rank on HumanEval?
It ranks #373 of 600 models, in the 38th percentile. The leader is GPT-5.2 Pro at 96.8.
Is Firesearch Max good at HumanEval?
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 HumanEval score calculated?
HumanEval is a coding 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 Max cost?
Firesearch Max costs $7.80 per million input tokens and $31.80 per million output tokens.