Gemini 2.5 Pro Nano on IFEval: score, rank and what it means
Gemini 2.5 Pro Nano scores 79.9 on IFEval, placing it #334 of 600 models in the index. The benchmark average is 78.6 and the leader is Claude Opus 4.5 Pro at 96.1.
Score distribution
The chart shows the top 10 models on IFEval, with Gemini 2.5 Pro Nano highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 2 | Claude Opus 4.5 Reasoning | Anthropic | 2000000 | $20.91 | 88.2 |
| 3 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 4 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 5 | GPT-5.2 Reasoning | OpenAI | 1000000 | $20.98 | 87.5 |
| 6 | GPT-5.1 Pro | OpenAI | 200000 | $19.77 | 87.8 |
| 7 | Gemini 3 Pro Max | Google DeepMind | 2000000 | $20.57 | 87.9 |
| 8 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
| 9 | Claude Opus 4.5 Max | Anthropic | 1000000 | $20.90 | 87.8 |
| 10 | o4 Reasoning | OpenAI | 1000000 | $19.69 | 87.5 |
What this score means
On IFEval, Gemini 2.5 Pro Nano sits at #334 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 16.2 points. The median model in this index scores 81.2, which puts Gemini 2.5 Pro Nano below the midpoint.
Google DeepMind models average 85.7 on this benchmark. Gemini 2.5 Pro Nano is 5.8 points below that provider line, so it is a weaker result than the average Google DeepMind model.
Among mid-range models, the average is 76.5. Gemini 2.5 Pro Nano is 3.4 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 79.9 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 $7.28 per million input tokens, Gemini 2.5 Pro Nano is above the median input price of $4.00 across the 600 models scored on IFEval. 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 Chat | Together AI | 32768 | $3.02 | 71.7 |
| Firesearch Pro | Fireworks AI | 32768 | $7.67 | 70.4 |
| Mistral Small 3 Base | Mistral AI | 16384 | $3.19 | 72.7 |
| Yi-Lightning Base | 01.AI | 16384 | $3.31 | 72.7 |
| Gemini 2.5 Pro Nano | Google DeepMind | 32768 | $7.28 | 69.2 |
| Firefunction Turbo | Fireworks AI | 32768 | $8.44 | 70.7 |
| Mixtral Instruct | Mistral AI | 65536 | $3.35 | 72.9 |
Other benchmarks for Gemini 2.5 Pro Nano
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 71.4 | 385 | 36th | |
| GPQA Diamond | 65.4 | 353 | 41th | |
| SWE-bench Verified | 54.3 | 390 | 35th | |
| HumanEval | 71.1 | 387 | 36th | |
| MATH-500 | 74.9 | 327 | 46th | |
| AIME 2025 | 63.7 | 360 | 40th | |
| LiveCodeBench | 59.2 | 376 | 37th | |
| TruthfulQA | 74.4 | 343 | 43th | |
| HellaSwag | 80.7 | 375 | 38th | |
| MMMU | 65.9 | 374 | 38th | |
| Arena Elo | 1349.7 | 364 | 39th |
FAQ
What score does Gemini 2.5 Pro Nano get on IFEval?
Gemini 2.5 Pro Nano scores 79.9 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.
How does Gemini 2.5 Pro Nano rank on IFEval?
It ranks #334 of 600 models, in the 44th percentile. The leader is Claude Opus 4.5 Pro at 96.1.
Is Gemini 2.5 Pro Nano good at IFEval?
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 IFEval score calculated?
IFEval is a instruction following 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 2.5 Pro Nano cost?
Gemini 2.5 Pro Nano costs $7.28 per million input tokens and $28.44 per million output tokens.