Model Comparison

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

NVIDIA

Llama 3.1 Nemotron Nano 8B V1

NVIDIA

Llama 3.1 Nemotron Nano 8B V1 is a language model developed by NVIDIA. It achieves strong performance with an average score of 72.2% across 7 benchmarks. It excels particularly in MATH-500 (95.4%), MBPP (84.6%), MT-Bench (81.0%). Released in 2025, it represents NVIDIA's latest advancement in AI technology.

Alibaba

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.

Alibaba

Qwen2.5-Coder 32B Instruct

Alibaba

2024-09-19

NVIDIA

Llama 3.1 Nemotron Nano 8B V1

NVIDIA

2025-03-18

6 months newer

Performance Metrics

Context window and performance specifications

NVIDIA

Llama 3.1 Nemotron Nano 8B V1

Max Context:-
Parameters:8.0B
Alibaba

Qwen2.5-Coder 32B Instruct

Larger context
Max Context:256.0K
Parameters:32.0B

Average performance across 1 common benchmarks

NVIDIA

Llama 3.1 Nemotron Nano 8B V1

Average Score:84.6%
Alibaba

Qwen2.5-Coder 32B Instruct

+5.6%
Average Score:90.2%

Performance comparison across key benchmark categories

NVIDIA

Llama 3.1 Nemotron Nano 8B V1

math
+21.2%
95.4%
code
+23.8%
82.0%
general
54.9%
Alibaba

Qwen2.5-Coder 32B Instruct

math
74.2%
code
58.2%
general
+6.6%
61.5%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Llama 3.1 Nemotron Nano 8B V1

2023-12-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

NVIDIA

Llama 3.1 Nemotron Nano 8B V1

0 providers
Alibaba

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
NVIDIA

Llama 3.1 Nemotron Nano 8B V1

Avg Score:84.6%
Providers:0
Alibaba

Qwen2.5-Coder 32B Instruct

+5.6%
Avg Score:90.2%
Providers:4