Firesearch Max on LiveCodeBench: score, rank and what it means
Firesearch Max scores 63.7 on LiveCodeBench, placing it #327 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.
Score distribution
The chart shows the top 10 models on LiveCodeBench, with Firesearch Max highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 2 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 3 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 4 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 5 | Grok 4 Turbo | xAI | 1000000 | $19.21 | 86.7 |
| 6 | GPT-5.1 Turbo | OpenAI | 2000000 | $19.19 | 86.1 |
| 7 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 8 | GPT-5.2 Reasoning | OpenAI | 1000000 | $20.98 | 87.5 |
| 9 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 10 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
What this score means
On LiveCodeBench, Firesearch Max sits at #327 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 21.4 points. The median model in this index scores 64.7, which puts Firesearch Max below the midpoint.
Fireworks AI models average 58.6 on this benchmark. Firesearch Max is 5.1 points above that provider line, so it is a stronger result than the average Fireworks AI model.
Among mid-range models, the average is 58.3. Firesearch Max is 5.4 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 63.7 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 LiveCodeBench. 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 |
|---|---|---|---|---|
| GPT-5.1 Nano | OpenAI | 32768 | $9.56 | 74.1 |
| OLMo 2 Instruct | Allen Institute for AI | 32768 | $3.03 | 71.7 |
| Seed-OSS Chat | ByteDance | 65536 | $3.49 | 74.4 |
| Firefunction Reasoning | Fireworks AI | 8192 | $9.08 | 72.5 |
| Firesearch Max | Fireworks AI | 8192 | $7.80 | 69.9 |
| Mistral Small 3 Base | Mistral AI | 16384 | $3.19 | 72.7 |
| Phi-4 Base | Microsoft | 32768 | $3.15 | 71.2 |
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 | |
| HumanEval | 72.9 | 373 | 38th | |
| MATH-500 | 73.0 | 358 | 40th | |
| AIME 2025 | 62.5 | 370 | 38th | |
| 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 LiveCodeBench?
Firesearch Max scores 63.7 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.
How does Firesearch Max rank on LiveCodeBench?
It ranks #327 of 600 models, in the 46th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.
Is Firesearch Max good at LiveCodeBench?
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 LiveCodeBench score calculated?
LiveCodeBench 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.