Model Comparison

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

Llama 3.1 Nemotron 70B Instruct

NVIDIA

Llama 3.1 Nemotron 70B Instruct is a language model developed by NVIDIA. It achieves strong performance with an average score of 67.9% across 11 benchmarks. It excels particularly in GSM8k (91.4%), HellaSwag (85.6%), Winogrande (84.5%). The model shows particular specialization in math tasks with an average performance of 86.7%. Released in 2024, it represents NVIDIA's latest advancement in AI technology.

Qwen2.5-Coder 32B Instruct

Alibaba

Qwen2.5-Coder 32B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 64.9% across 15 benchmarks. It excels particularly in HumanEval (92.7%), GSM8k (91.1%), MBPP (90.2%). The model shows particular specialization in reasoning tasks with an average performance of 78.1%. It supports a 256K token context window for handling large documents. The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Qwen2.5-Coder 32B Instruct

Alibaba

2024-09-19

Llama 3.1 Nemotron 70B Instruct

NVIDIA

2024-10-01

12 days newer

Performance Metrics

Context window and performance specifications

Llama 3.1 Nemotron 70B Instruct

Max Context:-

Parameters:70.0B

Qwen2.5-Coder 32B Instruct

Larger context

Max Context:256.0K

Parameters:32.0B

Average performance across 6 common benchmarks

Llama 3.1 Nemotron 70B Instruct

+2.5%

Average Score:78.3%

Qwen2.5-Coder 32B Instruct

Average Score:75.8%

Performance comparison across key benchmark categories

Llama 3.1 Nemotron 70B Instruct

math

+12.5%

86.7%

reasoning

+1.7%

79.8%

code

+15.7%

73.8%

general

+2.6%

64.1%

factuality

+4.4%

58.6%

Qwen2.5-Coder 32B Instruct

math

74.2%

reasoning

78.1%

code

58.2%

general

61.5%

factuality

54.2%

Benchmark Scores - Detailed View

Side-by-side comparison of all benchmark scores

Knowledge Cutoff

Training data recency comparison

Llama 3.1 Nemotron 70B Instruct

2023-12-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Llama 3.1 Nemotron 70B Instruct

0 providers

Qwen2.5-Coder 32B Instruct

4 providers

Hyperbolic

Throughput: 100 tok/s

Latency: 0.5ms

DeepInfra

Throughput: 44 tok/s

Latency: 0.5ms

Fireworks

Throughput: 110 tok/s

Latency: 0.26ms

Lambda

Throughput: 42 tok/s

Latency: 0.5ms

Llama 3.1 Nemotron 70B Instruct

+2.5%

Avg Score:78.3%

Providers:0

Qwen2.5-Coder 32B Instruct

Avg Score:75.8%

Providers:4