Model Comparison

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

NVIDIA

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.

Alibaba

Qwen2.5 72B Instruct

Alibaba

Qwen2.5 72B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 77.4% across 14 benchmarks. It excels particularly in GSM8k (95.8%), MT-Bench (93.5%), MBPP (88.2%). The model shows particular specialization in math tasks with an average performance of 89.5%. It supports a 139K 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 72B Instruct

Alibaba

2024-09-19

NVIDIA

Llama 3.1 Nemotron 70B Instruct

NVIDIA

2024-10-01

12 days newer

Performance Metrics

Context window and performance specifications

NVIDIA

Llama 3.1 Nemotron 70B Instruct

Max Context:-
Parameters:70.0B
Alibaba

Qwen2.5 72B Instruct

Larger context
Max Context:139.3K
Parameters:72.7B

Average performance across 2 common benchmarks

NVIDIA

Llama 3.1 Nemotron 70B Instruct

Average Score:50.2%
Alibaba

Qwen2.5 72B Instruct

+44.4%
Average Score:94.7%

Performance comparison across key benchmark categories

NVIDIA

Llama 3.1 Nemotron 70B Instruct

math
86.7%
code
73.8%
general
64.1%
roleplay
9.0%
Alibaba

Qwen2.5 72B Instruct

math
+2.8%
89.5%
code
+4.8%
78.6%
general
+10.0%
74.1%
roleplay
+63.9%
72.9%
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

NVIDIA

Llama 3.1 Nemotron 70B Instruct

0 providers
Alibaba

Qwen2.5 72B Instruct

4 providers

Together

Throughput: 47 tok/s
Latency: 0.5ms

Hyperbolic

Throughput: 100 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 10 tok/s
Latency: 0.5ms

Fireworks

Throughput: 59 tok/s
Latency: 0.37ms
NVIDIA

Llama 3.1 Nemotron 70B Instruct

Avg Score:50.2%
Providers:0
Alibaba

Qwen2.5 72B Instruct

+44.4%
Avg Score:94.7%
Providers:4