Model Comparison

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

Anthropic

Claude Opus 4

Anthropic

Claude Opus 4 is a multimodal language model developed by Anthropic. It achieves strong performance with an average score of 64.6% across 9 benchmarks. It excels particularly in MMMLU (88.8%), TAU-bench Retail (81.4%), GPQA (79.6%). It supports a 328K token context window for handling large documents. The model is available through 3 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Anthropic's latest advancement in AI technology.

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.

Meta

Llama 3.2 11B Instruct

Meta

2024-09-25

Anthropic

Claude Opus 4

Anthropic

2025-05-22

7 months newer

Pricing Comparison

Cost per million tokens (USD)

Anthropic

Claude Opus 4

Input:$15.00
Output:$75.00
Meta

Llama 3.2 11B Instruct

$89.90 cheaper
Input:$0.05
Output:$0.05

Performance Metrics

Context window and performance specifications

Anthropic

Claude Opus 4

Larger context
Max Context:328.0K
Meta

Llama 3.2 11B Instruct

Max Context:256.0K
Parameters:10.6B

Average performance across 1 common benchmarks

Anthropic

Claude Opus 4

+46.8%
Average Score:79.6%
Meta

Llama 3.2 11B Instruct

Average Score:32.8%

Performance comparison across key benchmark categories

Anthropic

Claude Opus 4

vision
+14.7%
76.5%
general
+1.0%
71.1%
Meta

Llama 3.2 11B Instruct

vision
61.8%
general
70.1%
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

Anthropic

Claude Opus 4

3 providers

Google

Throughput: 42 tok/s
Latency: 0.4ms

Bedrock

Throughput: 120 tok/s
Latency: 0.5ms

Anthropic

Throughput: 100 tok/s
Latency: 0.5ms
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
Anthropic

Claude Opus 4

+46.8%
Avg Score:79.6%
Providers:3
Meta

Llama 3.2 11B Instruct

Avg Score:32.8%
Providers:6