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 32B Instruct

Alibaba

Qwen2.5-Coder 32B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 64.9% across 15 benchmarks. It excels particularly in HumanEval (92.7%), GSM8k (91.1%), MBPP (90.2%). The model shows particular specialization in reasoning tasks with an average performance of 78.1%. It supports a 256K 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-Coder 32B Instruct

Alibaba

2024-09-19

Meta

Llama 3.2 11B Instruct

Meta

2024-09-25

6 days newer

Pricing Comparison

Cost per million tokens (USD)

Meta

Llama 3.2 11B Instruct

$0.08 cheaper
Input:$0.05
Output:$0.05
Alibaba

Qwen2.5-Coder 32B Instruct

Input:$0.09
Output:$0.09

Performance Metrics

Context window and performance specifications

Meta

Llama 3.2 11B Instruct

Max Context:256.0K
Parameters:10.6B
Alibaba

Qwen2.5-Coder 32B Instruct

Max Context:256.0K
Parameters:32.0B

Average performance across 2 common benchmarks

Meta

Llama 3.2 11B Instruct

Average Score:62.5%
Alibaba

Qwen2.5-Coder 32B Instruct

+3.7%
Average Score:66.1%

Performance comparison across key benchmark categories

Meta

Llama 3.2 11B Instruct

math
57.4%
general
+8.6%
70.1%
Alibaba

Qwen2.5-Coder 32B Instruct

math
+16.7%
74.2%
general
61.5%
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 32B Instruct

4 providers

Hyperbolic

Throughput: 100 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 44 tok/s
Latency: 0.5ms

Fireworks

Throughput: 110 tok/s
Latency: 0.26ms

Lambda

Throughput: 42 tok/s
Latency: 0.5ms
Meta

Llama 3.2 11B Instruct

Avg Score:62.5%
Providers:6
Alibaba

Qwen2.5-Coder 32B Instruct

+3.7%
Avg Score:66.1%
Providers:4