Model Comparison

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

Meta

Llama 3.2 11B Instruct

Meta

Llama 3.2 11B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 63.6% across 11 benchmarks. It excels particularly in AI2D (91.1%), DocVQA (88.4%), ChartQA (83.4%). It supports a 256K token context window for handling large documents. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Meta's latest advancement in AI technology.

Alibaba

Qwen2.5-Coder 7B Instruct

Alibaba

Qwen2.5-Coder 7B Instruct is a language model developed by Alibaba. The model shows competitive results across 19 benchmarks. It excels particularly in HumanEval (88.4%), GSM8k (83.9%), MBPP (83.5%). 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 7B Instruct

Alibaba

2024-09-19

Meta

Llama 3.2 11B Instruct

Meta

2024-09-25

6 days newer

Performance Metrics

Context window and performance specifications

Meta

Llama 3.2 11B Instruct

Larger context
Max Context:256.0K
Parameters:10.6B
Alibaba

Qwen2.5-Coder 7B Instruct

Max Context:-
Parameters:7.0B

Average performance across 2 common benchmarks

Meta

Llama 3.2 11B Instruct

+5.3%
Average Score:62.5%
Alibaba

Qwen2.5-Coder 7B Instruct

Average Score:57.1%

Performance comparison across key benchmark categories

Meta

Llama 3.2 11B Instruct

general
+17.8%
70.1%
math
57.4%
Alibaba

Qwen2.5-Coder 7B Instruct

general
52.3%
math
+7.8%
65.3%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Llama 3.2 11B Instruct

2023-12-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Meta

Llama 3.2 11B Instruct

6 providers

Sambanova

Throughput: 100 tok/s
Latency: 0.5ms

Together

Throughput: 168 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 108 tok/s
Latency: 0.5ms

Fireworks

Throughput: 125 tok/s
Latency: 0.2ms

Groq

Throughput: 100 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
Alibaba

Qwen2.5-Coder 7B Instruct

0 providers
Meta

Llama 3.2 11B Instruct

+5.3%
Avg Score:62.5%
Providers:6
Alibaba

Qwen2.5-Coder 7B Instruct

Avg Score:57.1%
Providers:0