Instruction following · Google DeepMind

Gemini 3 Flash Turbo on IFEval: score, rank and what it means

Gemini 3 Flash Turbo scores 88.9 on IFEval, placing it #85 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
88.9
0–100 scale
Rank
#85
of 600
Percentile
86th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
7.2
points

Score distribution

The chart shows the top 10 models on IFEval, with Gemini 3 Flash Turbo highlighted. Longer bars mean higher scores.

Claude Opus 4.5 Pro 96.1
Claude Opus 4.5 Reasoning 95.9
GPT-5.2 Pro 95.6
GPT-5.2 Max 95.2
GPT-5.2 Reasoning 95.0
GPT-5.1 Pro 94.8
Gemini 3 Pro Max 94.7
GPT-5.1 Reasoning 94.6
Claude Opus 4.5 Max 94.5
o4 Reasoning 94.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg 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 3 Flash Turbo sits at #85 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 7.2 points. The median model in this index scores 81.2, which puts Gemini 3 Flash Turbo above the midpoint.

Google DeepMind models average 85.7 on this benchmark. Gemini 3 Flash Turbo is 3.2 points above that provider line, so it is a stronger result than the average Google DeepMind model.

Among frontier models, the average is 92.0. Gemini 3 Flash Turbo is 3.1 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 88.9 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 $17.07 per million input tokens, Gemini 3 Flash Turbo 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.

ModelProviderContextInput / 1MAvg score
o4 Vision OpenAI 200000 $17.01 84.5
Command A Pro Cohere 200000 $14.28 81.3
DeepSeek-R1 Instruct DeepSeek 1000000 $5.90 83.1
Doubao 1.5 Pro Turbo ByteDance 128000 $13.81 79.4
Gemini 3 Flash Turbo Google DeepMind 200000 $17.07 84.1
Llama 4 Maverick Instruct Meta AI 200000 $5.33 81.7
Doubao 1.5 Pro Reasoning ByteDance 128000 $14.56 81.6

Other benchmarks for Gemini 3 Flash Turbo

BenchmarkScoreRankPercentileRelative
MMLU-Pro 87.9 18 97th
GPQA Diamond 77.5 96 84th
SWE-bench Verified 72.5 68 89th
HumanEval 90.6 37 94th
MATH-500 87.6 70 88th
AIME 2025 81.3 69 89th
LiveCodeBench 78.5 60 90th
TruthfulQA 87.4 29 95th
HellaSwag 89.5 99 84th
MMMU 83.0 23 96th
Arena Elo 1473.4 27 96th

FAQ

What score does Gemini 3 Flash Turbo get on IFEval?

Gemini 3 Flash Turbo scores 88.9 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does Gemini 3 Flash Turbo rank on IFEval?

It ranks #85 of 600 models, in the 86th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is Gemini 3 Flash Turbo good at IFEval?

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 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 3 Flash Turbo cost?

Gemini 3 Flash Turbo costs $17.07 per million input tokens and $69.05 per million output tokens.

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