Model Comparison

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

Meta

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.

Alibaba

Qwen2.5 VL 7B Instruct

Alibaba

Qwen2.5 VL 7B Instruct is a multimodal language model developed by Alibaba. It achieves strong performance with an average score of 64.5% across 32 benchmarks. It excels particularly in DocVQA (95.7%), Android Control Low_EM (91.4%), MobileMiniWob++_SR (91.4%). 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 3B Instruct

Meta

2024-09-25

Alibaba

Qwen2.5 VL 7B Instruct

Alibaba

2025-01-26

4 months newer

Performance Metrics

Context window and performance specifications

Meta

Llama 3.2 3B Instruct

Larger context
Max Context:256.0K
Parameters:3.2B
Alibaba

Qwen2.5 VL 7B Instruct

Max Context:-
Parameters:8.3B

Performance comparison across key benchmark categories

Meta

Llama 3.2 3B Instruct

general
42.5%
math
+14.7%
61.3%
Alibaba

Qwen2.5 VL 7B Instruct

general
+25.3%
67.7%
math
46.6%

Provider Availability & Performance

Available providers and their performance metrics

Meta

Llama 3.2 3B Instruct

1 providers

DeepInfra

Throughput: 171.5 tok/s
Latency: 0.24ms
Alibaba

Qwen2.5 VL 7B Instruct

0 providers
Meta

Llama 3.2 3B Instruct

Avg Score:0.0%
Providers:1
Alibaba

Qwen2.5 VL 7B Instruct

Avg Score:0.0%
Providers:0