Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Llama 3.2 3B Instruct

Meta

Llama 3.2 3B Instruct is a language model developed by Meta. The model shows competitive results across 15 benchmarks. It excels particularly in NIH/Multi-needle (84.7%), ARC-C (78.6%), GSM8k (77.7%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents Meta's latest advancement in AI technology.

QwQ-32B

Alibaba

QwQ-32B is a language model developed by Alibaba. It achieves strong performance with an average score of 74.6% across 7 benchmarks. It excels particularly in MATH-500 (90.6%), IFEval (83.9%), AIME 2024 (79.5%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Llama 3.2 3B Instruct

Performance Metrics

Context window and performance specifications

Llama 3.2 3B Instruct

Larger context

Max Context:256.0K

Parameters:3.2B

QwQ-32B

Max Context:-

Parameters:32.5B

Average performance across 2 common benchmarks

Llama 3.2 3B Instruct

Average Score:55.1%

QwQ-32B

+19.5%

Average Score:74.6%

Performance comparison across key benchmark categories

Llama 3.2 3B Instruct

math

61.3%

code

+3.8%

77.4%

general

42.5%

QwQ-32B

math

+29.3%

90.6%

code

73.6%

general

+27.9%

70.4%

Benchmark Scores - Detailed View

Side-by-side comparison of all benchmark scores

Knowledge Cutoff

Training data recency comparison

QwQ-32B

2024-11-28

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Llama 3.2 3B Instruct

1 providers

DeepInfra

Throughput: 171.5 tok/s

Latency: 0.24ms

QwQ-32B

0 providers

Llama 3.2 3B Instruct

Avg Score:55.1%

Providers:1

QwQ-32B

+19.5%

Avg Score:74.6%

Providers:0