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

QvQ-72B-Preview

Alibaba

QvQ-72B-Preview is a multimodal language model developed by Alibaba. The model shows competitive results across 4 benchmarks. Notable strengths include MathVista (71.4%), MMMU (70.3%), MathVision (35.9%). 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 Alibaba's latest advancement in AI technology.

Meta

Llama 3.2 3B Instruct

Meta

2024-09-25

Alibaba

QvQ-72B-Preview

Alibaba

2024-12-25

3 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

QvQ-72B-Preview

Max Context:-
Parameters:73.4B

Performance comparison across key benchmark categories

Meta

Llama 3.2 3B Instruct

math
+7.6%
61.3%
general
+22.1%
42.5%
Alibaba

QvQ-72B-Preview

math
53.6%
general
20.4%

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

QvQ-72B-Preview

0 providers
Meta

Llama 3.2 3B Instruct

Avg Score:0.0%
Providers:1
Alibaba

QvQ-72B-Preview

Avg Score:0.0%
Providers:0