Coding · OpenAI

GPT-4.1 Mini on LiveCodeBench: score, rank and what it means

GPT-4.1 Mini scores 67.0 on LiveCodeBench, placing it #249 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
67.0
0–100 scale
Rank
#249
of 600
Percentile
59th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
18.1
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with GPT-4.1 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, GPT-4.1 Mini sits at #249 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 18.1 points. The median model in this index scores 64.7, which puts GPT-4.1 Mini above the midpoint.

OpenAI models average 77.2 on this benchmark. GPT-4.1 Mini is 10.2 points below that provider line, so it is a weaker result than the average OpenAI model.

Among multimodal models, the average is 70.3. GPT-4.1 Mini is 3.3 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 67.0 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 $10.43 per million input tokens, GPT-4.1 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 Baseten Base Baseten 16384 $3.16 72.4
Llama 3.1 Cerebras Instruct Cerebras 65536 $4.11 76.1
Llama 3.3 Instruct Meta AI 128000 $4.33 76.6
Codestral Chat Mistral AI 32768 $3.89 75.8
GPT-4.1 Mini OpenAI 128000 $10.43 74.3
Kimi K1.5 Base Moonshot AI 65536 $4.34 77.4
Llama 3 Modal Instruct Modal 128000 $3.84 75.2

Other benchmarks for GPT-4.1 Mini

BenchmarkScoreRankPercentileRelative
MMLU-Pro 76.7 285 53th
GPQA Diamond 69.3 285 53th
SWE-bench Verified 60.9 304 49th
HumanEval 78.9 267 56th
MATH-500 77.9 259 57th
AIME 2025 66.9 314 48th
IFEval 81.4 289 52th
TruthfulQA 79.8 185 69th
HellaSwag 84.9 250 58th
MMMU 73.9 195 68th
Arena Elo 1379.7 274 54th

FAQ

What score does GPT-4.1 Mini get on LiveCodeBench?

GPT-4.1 Mini scores 67.0 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does GPT-4.1 Mini rank on LiveCodeBench?

It ranks #249 of 600 models, in the 59th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is GPT-4.1 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 GPT-4.1 Mini cost?

GPT-4.1 Mini costs $10.43 per million input tokens and $49.01 per million output tokens.

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