Mathematics · Alibaba Cloud

Qwen3-Coder 1.5B on MATH-500: score, rank and what it means

Qwen3-Coder 1.5B scores 51.9 on MATH-500, placing it #541 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
51.9
0–100 scale
Rank
#541
of 600
Percentile
10th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
44.8
points

Score distribution

The chart shows the top 10 models on MATH-500, with Qwen3-Coder 1.5B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Qwen3-Coder 1.5B sits at #541 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 44.8 points. The median model in this index scores 76.0, which puts Qwen3-Coder 1.5B below the midpoint.

Alibaba Cloud models average 76.4 on this benchmark. Qwen3-Coder 1.5B is 24.5 points below that provider line, so it is a weaker result than the average Alibaba Cloud model.

Among coding models, the average is 71.0. Qwen3-Coder 1.5B is 19.1 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 51.9 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 $0.76 per million input tokens, Qwen3-Coder 1.5B is below the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Embed 4 Nano Cohere 8192 $1.48 49.7
Phi-3.5 8B Microsoft 16384 $0.59 51.2
Command R+ 1.5B Cohere 32768 $0.51 50.0
Llama 3.1 1.5B Meta AI 4096 $0.53 50.7
Qwen3-Coder 1.5B Alibaba Cloud 32768 $0.76 52.8
Arctic 7B Snowflake 8192 $0.49 50.3
Llama 3.3 1.5B Meta AI 4096 $0.61 52.2

Other benchmarks for Qwen3-Coder 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 57.8 552 8th
GPQA Diamond 46.7 552 8th
SWE-bench Verified 37.0 541 10th
HumanEval 58.6 517 14th
AIME 2025 43.2 521 13th
LiveCodeBench 40.8 533 11th
IFEval 63.8 540 10th
TruthfulQA 59.9 532 11th
HellaSwag 68.5 555 8th
MMMU 53.0 520 13th
Arena Elo 1215.0 538 10th

FAQ

What score does Qwen3-Coder 1.5B get on MATH-500?

Qwen3-Coder 1.5B scores 51.9 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Qwen3-Coder 1.5B rank on MATH-500?

It ranks #541 of 600 models, in the 10th percentile. The leader is GPT-5.2 Max at 96.7.

Is Qwen3-Coder 1.5B good at MATH-500?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.

How is the MATH-500 score calculated?

MATH-500 is a mathematics 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 Qwen3-Coder 1.5B cost?

Qwen3-Coder 1.5B costs $0.76 per million input tokens and $2.67 per million output tokens.

Related