Coding · Alibaba Cloud

QwQ 1.5B on LiveCodeBench: score, rank and what it means

QwQ 1.5B scores 42.5 on LiveCodeBench, placing it #523 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
42.5
0–100 scale
Rank
#523
of 600
Percentile
13th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
42.6
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with QwQ 1.5B 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, QwQ 1.5B sits at #523 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 42.6 points. The median model in this index scores 64.7, which puts QwQ 1.5B below the midpoint.

Alibaba Cloud models average 64.0 on this benchmark. QwQ 1.5B is 21.5 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 41.2. QwQ 1.5B is 1.3 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 42.5 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 $0.61 per million input tokens, QwQ 1.5B is below 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
Gemma 3 7B Google DeepMind 32768 $0.90 55.9
Yi-Large 7B 01.AI 4096 $0.83 55.0
Llama 3 Baseten 7B Baseten 32768 $0.87 55.3
Llama 3 Modal 8B Modal 32768 $0.98 56.6
QwQ 1.5B Alibaba Cloud 32768 $0.61 51.6
Kimi K2 1.5B Moonshot AI 4096 $0.99 56.8
Llama 4 Maverick 1.5B Meta AI 8192 $0.93 55.2

Other benchmarks for QwQ 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 57.5 555 8th
GPQA Diamond 47.3 545 9th
SWE-bench Verified 35.0 557 7th
HumanEval 53.1 554 8th
MATH-500 50.8 549 9th
AIME 2025 39.9 541 10th
IFEval 63.1 546 9th
TruthfulQA 57.3 551 8th
HellaSwag 69.5 541 10th
MMMU 51.7 536 11th
Arena Elo 1211.8 542 10th

FAQ

What score does QwQ 1.5B get on LiveCodeBench?

QwQ 1.5B scores 42.5 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does QwQ 1.5B rank on LiveCodeBench?

It ranks #523 of 600 models, in the 13th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is QwQ 1.5B good at LiveCodeBench?

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 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 QwQ 1.5B cost?

QwQ 1.5B costs $0.61 per million input tokens and $3.19 per million output tokens.

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