Model Comparison

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

DeepSeek R1 Distill Qwen 1.5B

DeepSeek

DeepSeek R1 Distill Qwen 1.5B is a language model developed by DeepSeek. The model shows competitive results across 4 benchmarks. It excels particularly in MATH-500 (83.9%), AIME 2024 (52.7%), GPQA (33.8%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.

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.

Llama 3.2 3B Instruct

Performance Metrics

Context window and performance specifications

DeepSeek R1 Distill Qwen 1.5B

Max Context:-

Parameters:1.8B

Llama 3.2 3B Instruct

Larger context

Max Context:256.0K

Parameters:3.2B

Average performance across 1 common benchmarks

DeepSeek R1 Distill Qwen 1.5B

+1.0%

Average Score:33.8%

Llama 3.2 3B Instruct

Average Score:32.8%

Performance comparison across key benchmark categories

DeepSeek R1 Distill Qwen 1.5B

math

+22.6%

83.9%

code

16.9%

general

+0.8%

43.3%

Llama 3.2 3B Instruct

math

61.3%

code

+60.5%

77.4%

general

42.5%

Benchmark Scores - Detailed View

Side-by-side comparison of all benchmark scores

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek R1 Distill Qwen 1.5B

0 providers

Llama 3.2 3B Instruct

1 providers

DeepInfra

Throughput: 171.5 tok/s

Latency: 0.24ms

DeepSeek R1 Distill Qwen 1.5B

+1.0%

Avg Score:33.8%

Providers:0

Llama 3.2 3B Instruct

Avg Score:32.8%

Providers:1