Mathematics · Alibaba Cloud

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

Qwen3 1.5B scores 54.2 on MATH-500, placing it #526 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
54.2
0–100 scale
Rank
#526
of 600
Percentile
12th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
42.5
points

Score distribution

The chart shows the top 10 models on MATH-500, with Qwen3 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 1.5B sits at #526 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 42.5 points. The median model in this index scores 76.0, which puts Qwen3 1.5B below the midpoint.

Alibaba Cloud models average 76.4 on this benchmark. Qwen3 1.5B is 22.2 points below that provider line, so it is a weaker result than the average Alibaba Cloud model.

Among small open-weight models, the average is 53.7. Qwen3 1.5B is 0.5 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 54.2 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 $0.84 per million input tokens, Qwen3 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
Phi-4 8B Microsoft 32768 $0.96 54.9
Embed 4 Mini Cohere 4096 $2.48 55.8
Llama 4 Maverick 1.5B Meta AI 8192 $0.93 55.2
Seed-OSS 7B ByteDance 8192 $0.85 55.5
Qwen3 1.5B Alibaba Cloud 4096 $0.84 53.5
MiniMax-Text 1.5B MiniMax 32768 $0.58 51.5
Mixtral Groq 8B Groq 32768 $0.77 54.8

Other benchmarks for Qwen3 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 60.8 516 14th
GPQA Diamond 49.8 527 12th
SWE-bench Verified 36.9 542 10th
HumanEval 59.8 507 16th
AIME 2025 41.5 533 11th
LiveCodeBench 38.8 544 9th
IFEval 64.5 536 11th
TruthfulQA 60.9 520 13th
HellaSwag 69.1 547 9th
MMMU 52.1 530 12th
Arena Elo 1238.1 517 14th

FAQ

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

Qwen3 1.5B scores 54.2 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Qwen3 1.5B rank on MATH-500?

It ranks #526 of 600 models, in the 12th percentile. The leader is GPT-5.2 Max at 96.7.

Is Qwen3 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 1.5B cost?

Qwen3 1.5B costs $0.84 per million input tokens and $4.53 per million output tokens.

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