Gemini 3 Flash Nano on GPQA Diamond: score, rank and what it means
Gemini 3 Flash Nano scores 62.9 on GPQA Diamond, placing it #384 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 Gemini 3 Flash Nano 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, Gemini 3 Flash Nano sits at #384 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 24.1 points. The median model in this index scores 68.8, which puts Gemini 3 Flash Nano below the midpoint.
Google DeepMind models average 73.4 on this benchmark. Gemini 3 Flash Nano is 10.5 points below that provider line, so it is a weaker result than the average Google DeepMind model.
Among mid-range models, the average is 62.9. Gemini 3 Flash Nano is 0.0 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 62.9 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 $7.56 per million input tokens, Gemini 3 Flash Nano 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 |
|---|---|---|---|---|
| Mixtral Turbo Base | Together AI | 32768 | $2.53 | 69.7 |
| Molmo Chat | Allen Institute for AI | 32768 | $2.40 | 66.7 |
| Firesearch Reasoning | Fireworks AI | 32768 | $7.74 | 69.0 |
| Hunyuan-Turbo Mini | Tencent | 8192 | $6.59 | 68.3 |
| Gemini 3 Flash Nano | Google DeepMind | 32768 | $7.56 | 69.4 |
| Embed 4 Reasoning | Cohere | 4096 | $5.50 | 65.3 |
| Doubao 1.5 Pro Nano | ByteDance | 16384 | $5.78 | 66.6 |
Other benchmarks for Gemini 3 Flash Nano
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 71.4 | 386 | 36th | |
| SWE-bench Verified | 55.7 | 379 | 37th | |
| HumanEval | 73.0 | 372 | 38th | |
| MATH-500 | 75.0 | 323 | 46th | |
| AIME 2025 | 62.9 | 365 | 39th | |
| LiveCodeBench | 60.3 | 364 | 39th | |
| IFEval | 77.5 | 371 | 38th | |
| TruthfulQA | 72.0 | 379 | 37th | |
| HellaSwag | 83.4 | 308 | 49th | |
| MMMU | 69.5 | 316 | 47th | |
| Arena Elo | 1348.8 | 367 | 39th |
FAQ
What score does Gemini 3 Flash Nano get on GPQA Diamond?
Gemini 3 Flash Nano scores 62.9 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.
How does Gemini 3 Flash Nano rank on GPQA Diamond?
It ranks #384 of 600 models, in the 36th percentile. The leader is GPT-5.2 Reasoning at 87.0.
Is Gemini 3 Flash Nano good at GPQA Diamond?
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 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 Gemini 3 Flash Nano cost?
Gemini 3 Flash Nano costs $7.56 per million input tokens and $41.55 per million output tokens.