Instruction following · Google DeepMind

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

Gemini 3 Flash Vision scores 86.9 on IFEval, placing it #135 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
86.9
0–100 scale
Rank
#135
of 600
Percentile
78th
within the index
Benchmark avg
78.6
all models
Leader
96.1
Claude Opus 4.5 Pro
Gap to leader
9.2
points

Score distribution

The chart shows the top 10 models on IFEval, with Gemini 3 Flash Vision 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 Vision sits at #135 of 600. The leader, Claude Opus 4.5 Pro, scores 96.1, so the gap to the top is 9.2 points. The median model in this index scores 81.2, which puts Gemini 3 Flash Vision above the midpoint.

Google DeepMind models average 85.7 on this benchmark. Gemini 3 Flash Vision is 1.2 points above that provider line, so it is a stronger result than the average Google DeepMind model.

Among multimodal models, the average is 85.2. Gemini 3 Flash Vision is 1.7 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 86.9 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 $15.06 per million input tokens, Gemini 3 Flash Vision 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
Sonar Pro Reasoning Perplexity 128000 $13.94 80.5
Llama 3.3 Meta AI 128000 $4.56 78.2
DeepSeek-V3.2 Base DeepSeek 128000 $5.05 80.2
GLM-4.6 Base Zhipu AI 128000 $4.53 78.5
Gemini 3 Flash Vision Google DeepMind 400000 $15.06 81.9
Llama 4 Scout Meta AI 200000 $4.90 79.3
Command A Turbo Cohere 32768 $13.53 79.8

Other benchmarks for Gemini 3 Flash Vision

BenchmarkScoreRankPercentileRelative
MMLU-Pro 81.8 125 79th
GPQA Diamond 75.7 130 78th
SWE-bench Verified 71.4 86 86th
HumanEval 84.5 124 79th
MATH-500 87.5 72 88th
AIME 2025 82.4 61 90th
LiveCodeBench 73.2 122 80th
TruthfulQA 85.5 59 90th
HellaSwag 91.5 47 92th
MMMU 80.3 55 91th
Arena Elo 1430.3 120 80th

FAQ

What score does Gemini 3 Flash Vision get on IFEval?

Gemini 3 Flash Vision scores 86.9 on IFEval in this index. The benchmark average is 78.6 and the top score is 96.1.

How does Gemini 3 Flash Vision rank on IFEval?

It ranks #135 of 600 models, in the 78th percentile. The leader is Claude Opus 4.5 Pro at 96.1.

Is Gemini 3 Flash Vision 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 Vision cost?

Gemini 3 Flash Vision costs $15.06 per million input tokens and $82.14 per million output tokens.

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