Llama 4 Scout Instruct on GPQA Diamond: score, rank and what it means
Llama 4 Scout Instruct scores 76.1 on GPQA Diamond, placing it #121 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.
Score distribution
The chart shows the top 10 models on GPQA Diamond, with Llama 4 Scout Instruct highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Reasoning | OpenAI | 1000000 | $20.98 | 87.5 |
| 2 | GPT-5.1 Max | OpenAI | 2000000 | $20.50 | 87.9 |
| 3 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 4 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 5 | Claude Sonnet 4.5 Reasoning | Anthropic | 400000 | $19.48 | 87.7 |
| 6 | GPT-5.2 | OpenAI | 2000000 | $19.71 | 88.0 |
| 7 | o4 Turbo | OpenAI | 2000000 | $19.34 | 86.6 |
| 8 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 9 | Grok 4 Turbo | xAI | 1000000 | $19.21 | 86.7 |
| 10 | Claude Sonnet 4.5 Max | Anthropic | 1000000 | $19.90 | 87.2 |
What this score means
On GPQA Diamond, Llama 4 Scout Instruct sits at #121 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 10.9 points. The median model in this index scores 68.8, which puts Llama 4 Scout Instruct above the midpoint.
Meta AI models average 64.6 on this benchmark. Llama 4 Scout Instruct is 11.5 points above that provider line, so it is a stronger result than the average Meta AI model.
Among multimodal models, the average is 73.5. Llama 4 Scout Instruct is 2.6 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 76.1 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 $4.59 per million input tokens, Llama 4 Scout Instruct is above the median input price of $4.00 across the 600 models scored on GPQA Diamond. 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 |
|---|---|---|---|---|
| Doubao 1.5 Pro Max | ByteDance | 400000 | $14.93 | 81.2 |
| GPT-4.1 | OpenAI | 1000000 | $15.71 | 82.4 |
| GPT-4.1 Turbo | OpenAI | 1000000 | $16.12 | 82.9 |
| Kimi K2 Base | Moonshot AI | 65536 | $4.82 | 79.2 |
| Llama 4 Scout Instruct | Meta AI | 32768 | $4.59 | 79.1 |
| Hunyuan-Turbo Pro | Tencent | 65536 | $12.00 | 77.6 |
| Mistral Large 3 Chat | Mistral AI | 1000000 | $4.90 | 79.1 |
Other benchmarks for Llama 4 Scout Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 80.0 | 183 | 70th | |
| SWE-bench Verified | 70.1 | 108 | 82th | |
| HumanEval | 81.6 | 194 | 68th | |
| MATH-500 | 84.7 | 114 | 81th | |
| AIME 2025 | 77.3 | 125 | 79th | |
| LiveCodeBench | 73.8 | 113 | 81th | |
| IFEval | 85.2 | 185 | 69th | |
| TruthfulQA | 79.9 | 181 | 70th | |
| HellaSwag | 88.4 | 127 | 79th | |
| MMMU | 73.0 | 221 | 63th | |
| Arena Elo | 1429.1 | 122 | 80th |
FAQ
What score does Llama 4 Scout Instruct get on GPQA Diamond?
Llama 4 Scout Instruct scores 76.1 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.
How does Llama 4 Scout Instruct rank on GPQA Diamond?
It ranks #121 of 600 models, in the 80th percentile. The leader is GPT-5.2 Reasoning at 87.0.
Is Llama 4 Scout Instruct good at GPQA Diamond?
Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.
How is the GPQA Diamond score calculated?
GPQA Diamond is a reasoning 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 Scout Instruct cost?
Llama 4 Scout Instruct costs $4.59 per million input tokens and $20.15 per million output tokens.