Coding · Google DeepMind

Gemini 3 Flash Max on LiveCodeBench: score, rank and what it means

Gemini 3 Flash Max scores 78.3 on LiveCodeBench, placing it #62 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
78.3
0–100 scale
Rank
#62
of 600
Percentile
90th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
6.8
points

Score distribution

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

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Gemini 3 Flash Max sits at #62 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 6.8 points. The median model in this index scores 64.7, which puts Gemini 3 Flash Max above the midpoint.

Google DeepMind models average 70.8 on this benchmark. Gemini 3 Flash Max is 7.5 points above that provider line, so it is a stronger result than the average Google DeepMind model.

Among frontier models, the average is 80.6. Gemini 3 Flash Max is 2.3 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 78.3 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 $17.43 per million input tokens, Gemini 3 Flash Max is above the median input price of $4.00 across the 600 models scored on LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7
GPT-4.1 Max OpenAI 400000 $17.34 84.7
Gemini 3 Flash Turbo Google DeepMind 200000 $17.07 84.1
Kimi K2 Moonshot AI 128000 $5.85 83.0
Gemini 3 Flash Max Google DeepMind 1000000 $17.43 85.0
Claude 3.7 Sonnet Max Anthropic 128000 $16.88 83.7
Qwen3-Max Reasoning Alibaba Cloud 2000000 $18.12 85.9

Other benchmarks for Gemini 3 Flash Max

BenchmarkScoreRankPercentileRelative
MMLU-Pro 87.8 19 97th
GPQA Diamond 80.9 45 93th
SWE-bench Verified 73.8 56 91th
HumanEval 88.5 64 89th
MATH-500 88.6 64 89th
AIME 2025 86.7 22 96th
IFEval 91.3 48 92th
TruthfulQA 87.1 34 94th
HellaSwag 91.1 60 90th
MMMU 81.0 43 93th
Arena Elo 1448.5 77 87th

FAQ

What score does Gemini 3 Flash Max get on LiveCodeBench?

Gemini 3 Flash Max scores 78.3 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Gemini 3 Flash Max rank on LiveCodeBench?

It ranks #62 of 600 models, in the 90th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Gemini 3 Flash Max good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench is a coding 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 Max cost?

Gemini 3 Flash Max costs $17.43 per million input tokens and $63.42 per million output tokens.

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