Llama 4 Maverick 7B on LiveCodeBench: score, rank and what it means
Llama 4 Maverick 7B scores 48.5 on LiveCodeBench, placing it #461 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 Llama 4 Maverick 7B 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, Llama 4 Maverick 7B sits at #461 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 36.6 points. The median model in this index scores 64.7, which puts Llama 4 Maverick 7B below the midpoint.
Meta AI models average 59.3 on this benchmark. Llama 4 Maverick 7B is 10.8 points below that provider line, so it is a weaker result than the average Meta AI model.
Among small open-weight models, the average is 41.2. Llama 4 Maverick 7B is 7.3 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 48.5 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 $1.52 per million input tokens, Llama 4 Maverick 7B is below 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-NeoX Chat | EleutherAI | 16384 | $1.49 | 60.1 |
| Llama 3.1 8B | Meta AI | 8192 | $1.15 | 58.7 |
| MiniMax-Text 8B | MiniMax | 4096 | $1.22 | 59.5 |
| Zephyr | Hugging Face | 8192 | $1.61 | 62.8 |
| Llama 4 Maverick 7B | Meta AI | 4096 | $1.52 | 61.9 |
| DeepSeek-Coder 7B | DeepSeek | 32768 | $1.14 | 57.3 |
| Qwen3-Coder 7B | Alibaba Cloud | 32768 | $1.24 | 59.6 |
Other benchmarks for Llama 4 Maverick 7B
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 65.2 | 451 | 25th | |
| GPQA Diamond | 59.2 | 414 | 31th | |
| SWE-bench Verified | 50.0 | 422 | 30th | |
| HumanEval | 65.1 | 440 | 27th | |
| MATH-500 | 66.0 | 414 | 31th | |
| AIME 2025 | 56.5 | 407 | 32th | |
| IFEval | 70.7 | 445 | 26th | |
| TruthfulQA | 65.6 | 452 | 25th | |
| HellaSwag | 75.1 | 438 | 27th | |
| MMMU | 58.7 | 446 | 26th | |
| Arena Elo | 1287.3 | 435 | 28th |
FAQ
What score does Llama 4 Maverick 7B get on LiveCodeBench?
Llama 4 Maverick 7B scores 48.5 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.
How does Llama 4 Maverick 7B rank on LiveCodeBench?
It ranks #461 of 600 models, in the 23rd percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.
Is Llama 4 Maverick 7B 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 Llama 4 Maverick 7B cost?
Llama 4 Maverick 7B costs $1.52 per million input tokens and $8.19 per million output tokens.