Seed-OSS Instruct on GPQA Diamond: score, rank and what it means
Seed-OSS Instruct scores 72.3 on GPQA Diamond, placing it #215 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 Seed-OSS 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, Seed-OSS Instruct sits at #215 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 14.7 points. The median model in this index scores 68.8, which puts Seed-OSS Instruct above the midpoint.
ByteDance models average 67.2 on this benchmark. Seed-OSS Instruct is 5.1 points above that provider line, so it is a stronger result than the average ByteDance model.
Among multimodal models, the average is 73.5. Seed-OSS Instruct is 1.2 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 72.3 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 $3.79 per million input tokens, Seed-OSS Instruct is below 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 |
|---|---|---|---|---|
| Llama 3.1 Chat | Meta AI | 32768 | $3.82 | 75.3 |
| Nova Pro Turbo | Amazon | 128000 | $13.18 | 78.4 |
| Qwen3-Coder Chat | Alibaba Cloud | 128000 | $4.59 | 78.4 |
| Magistral Chat | Mistral AI | 128000 | $4.33 | 76.8 |
| Seed-OSS Instruct | ByteDance | 128000 | $3.79 | 76.0 |
| Qwen3-Coder Base | Alibaba Cloud | 200000 | $3.99 | 76.6 |
| Gemini 3 Pro Mini | Google DeepMind | 128000 | $12.27 | 78.1 |
Other benchmarks for Seed-OSS Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 78.5 | 226 | 62th | |
| SWE-bench Verified | 63.3 | 249 | 59th | |
| HumanEval | 80.2 | 228 | 62th | |
| MATH-500 | 81.2 | 187 | 69th | |
| AIME 2025 | 71.2 | 233 | 61th | |
| LiveCodeBench | 65.4 | 287 | 52th | |
| IFEval | 82.8 | 252 | 58th | |
| TruthfulQA | 79.3 | 207 | 66th | |
| HellaSwag | 87.2 | 169 | 72th | |
| MMMU | 74.5 | 170 | 72th | |
| Arena Elo | 1400.9 | 206 | 66th |
FAQ
What score does Seed-OSS Instruct get on GPQA Diamond?
Seed-OSS Instruct scores 72.3 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.
How does Seed-OSS Instruct rank on GPQA Diamond?
It ranks #215 of 600 models, in the 64th percentile. The leader is GPT-5.2 Reasoning at 87.0.
Is Seed-OSS 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 Seed-OSS Instruct cost?
Seed-OSS Instruct costs $3.79 per million input tokens and $20.28 per million output tokens.