Coding · Google DeepMind

Gemini 2.5 Pro Mini on LiveCodeBench: score, rank and what it means

Gemini 2.5 Pro Mini scores 65.4 on LiveCodeBench, placing it #284 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
65.4
0–100 scale
Rank
#284
of 600
Percentile
53th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
19.7
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Gemini 2.5 Pro Mini 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 2.5 Pro Mini sits at #284 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 19.7 points. The median model in this index scores 64.7, which puts Gemini 2.5 Pro Mini above the midpoint.

Google DeepMind models average 70.8 on this benchmark. Gemini 2.5 Pro Mini is 5.4 points below that provider line, so it is a weaker result than the average Google DeepMind model.

Among multimodal models, the average is 70.3. Gemini 2.5 Pro Mini is 4.9 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 65.4 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 $10.07 per million input tokens, Gemini 2.5 Pro Mini 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
Llama 3 Lambda Base Lambda 8192 $3.19 72.9
Nova Lite Reasoning Amazon 32768 $9.92 74.3
Nova Lite Turbo Amazon 8192 $9.14 73.2
Seed-OSS Base ByteDance 16384 $3.14 72.2
Gemini 2.5 Pro Mini Google DeepMind 128000 $10.07 74.2
Gemma 3 Google DeepMind 65536 $3.68 73.6
Nova Lite Max Amazon 200000 $9.79 73.4

Other benchmarks for Gemini 2.5 Pro Mini

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.1 206 66th
GPQA Diamond 69.9 266 56th
SWE-bench Verified 63.6 242 60th
HumanEval 79.0 265 56th
MATH-500 76.0 298 50th
AIME 2025 68.2 292 51th
IFEval 81.5 287 52th
TruthfulQA 78.4 239 60th
HellaSwag 83.3 312 48th
MMMU 71.4 263 56th
Arena Elo 1399.4 209 65th

FAQ

What score does Gemini 2.5 Pro Mini get on LiveCodeBench?

Gemini 2.5 Pro Mini scores 65.4 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Gemini 2.5 Pro Mini rank on LiveCodeBench?

It ranks #284 of 600 models, in the 53rd percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Gemini 2.5 Pro Mini 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 2.5 Pro Mini cost?

Gemini 2.5 Pro Mini costs $10.07 per million input tokens and $53.47 per million output tokens.

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