Coding · OpenAI

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

GPT-4.1 Vision scores 74.3 on LiveCodeBench, placing it #102 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
74.3
0–100 scale
Rank
#102
of 600
Percentile
83th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
10.8
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with GPT-4.1 Vision 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 Vision sits at #102 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 10.8 points. The median model in this index scores 64.7, which puts GPT-4.1 Vision above the midpoint.

OpenAI models average 77.2 on this benchmark. GPT-4.1 Vision is 2.9 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 Vision is 4.0 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 74.3 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 $14.88 per million input tokens, GPT-4.1 Vision 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
Gemini 2.5 Pro Reasoning Google DeepMind 128000 $16.81 83.8
GLM-4.6 Base Zhipu AI 128000 $4.53 78.5
Kimi K2 Chat Moonshot AI 400000 $5.74 82.1
Mistral Large 3 Mistral AI 128000 $5.41 81.7
GPT-4.1 Vision OpenAI 1000000 $14.88 82.0
Grok 3 xAI 128000 $15.84 82.8
Nova Pro Reasoning Amazon 200000 $13.48 79.4

Other benchmarks for GPT-4.1 Vision

BenchmarkScoreRankPercentileRelative
MMLU-Pro 84.0 82 86th
GPQA Diamond 79.3 68 89th
SWE-bench Verified 72.4 70 88th
HumanEval 86.8 92 85th
MATH-500 87.5 71 88th
AIME 2025 77.2 128 79th
IFEval 88.7 89 85th
TruthfulQA 84.4 76 87th
HellaSwag 89.7 93 85th
MMMU 77.5 106 82th
Arena Elo 1451.8 69 89th

FAQ

What score does GPT-4.1 Vision get on LiveCodeBench?

GPT-4.1 Vision scores 74.3 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does GPT-4.1 Vision rank on LiveCodeBench?

It ranks #102 of 600 models, in the 83rd percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is GPT-4.1 Vision 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 Vision cost?

GPT-4.1 Vision costs $14.88 per million input tokens and $81.24 per million output tokens.

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