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

QwQ-32B-Preview

Alibaba

QwQ-32B-Preview is a language model developed by Alibaba. It achieves strong performance with an average score of 64.0% across 4 benchmarks. It excels particularly in MATH-500 (90.6%), GPQA (65.2%), AIME 2024 (50.0%). 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.

Meta

Llama 3.2 11B Instruct

Meta

2024-09-25

Alibaba

QwQ-32B-Preview

Alibaba

2024-11-28

2 months newer

Pricing Comparison

Cost per million tokens (USD)

Meta

Llama 3.2 11B Instruct

$0.25 cheaper
Input:$0.05
Output:$0.05
Alibaba

QwQ-32B-Preview

Input:$0.15
Output:$0.20

Performance Metrics

Context window and performance specifications

Meta

Llama 3.2 11B Instruct

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

QwQ-32B-Preview

Max Context:65.5K
Parameters:32.5B

Average performance across 1 common benchmarks

Meta

Llama 3.2 11B Instruct

Average Score:32.8%
Alibaba

QwQ-32B-Preview

+32.4%
Average Score:65.2%

Performance comparison across key benchmark categories

Meta

Llama 3.2 11B Instruct

math
57.4%
general
+12.5%
70.1%
Alibaba

QwQ-32B-Preview

math
+33.2%
90.6%
general
57.6%
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

QwQ-32B-Preview

2024-11-28

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

QwQ-32B-Preview

4 providers

Together

Throughput: 62.14 tok/s
Latency: 0.74ms

Hyperbolic

Throughput: 31.9 tok/s
Latency: 1.05ms

DeepInfra

Throughput: 76.04 tok/s
Latency: 0.44ms

Fireworks

Throughput: 99.15 tok/s
Latency: 0.53ms
Meta

Llama 3.2 11B Instruct

Avg Score:32.8%
Providers:6
Alibaba

QwQ-32B-Preview

+32.4%
Avg Score:65.2%
Providers:4