Model Comparison

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

Meta

Llama 3.2 90B Instruct

Meta

Llama 3.2 90B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.3% across 13 benchmarks. It excels particularly in AI2D (92.3%), DocVQA (90.1%), MGSM (86.9%). It supports a 256K token context window for handling large documents. The model is available through 5 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Meta's latest advancement in AI technology.

Alibaba

Qwen2.5-Omni-7B

Alibaba

Qwen2.5-Omni-7B is a multimodal language model developed by Alibaba. The model shows competitive results across 45 benchmarks. It excels particularly in DocVQA (95.2%), VocalSound (93.9%), GSM8k (88.7%). The model shows particular specialization in code tasks with an average performance of 76.0%. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Meta

Llama 3.2 90B Instruct

Meta

2024-09-25

Alibaba

Qwen2.5-Omni-7B

Alibaba

2025-03-27

6 months newer

Performance Metrics

Context window and performance specifications

Meta

Llama 3.2 90B Instruct

Larger context
Max Context:256.0K
Parameters:90.0B
Alibaba

Qwen2.5-Omni-7B

Max Context:-
Parameters:7.0B

Average performance across 9 common benchmarks

Meta

Llama 3.2 90B Instruct

+0.5%
Average Score:68.8%
Alibaba

Qwen2.5-Omni-7B

Average Score:68.2%

Performance comparison across key benchmark categories

Meta

Llama 3.2 90B Instruct

general
+14.8%
73.5%
math
+7.5%
70.7%
vision
69.4%
Alibaba

Qwen2.5-Omni-7B

general
58.7%
math
63.3%
vision
+0.1%
69.6%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores

Provider Availability & Performance

Available providers and their performance metrics

Meta

Llama 3.2 90B Instruct

5 providers

Together

Throughput: 57 tok/s
Latency: 0.5ms

Hyperbolic

Throughput: 42 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 24 tok/s
Latency: 0.5ms

Fireworks

Throughput: 50 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
Alibaba

Qwen2.5-Omni-7B

0 providers
Meta

Llama 3.2 90B Instruct

+0.5%
Avg Score:68.8%
Providers:5
Alibaba

Qwen2.5-Omni-7B

Avg Score:68.2%
Providers:0