Model Comparison

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

Meta

Llama 3.2 90B Instruct

Meta

Llama 3.2 90B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.3% across 13 benchmarks. It excels particularly in AI2D (92.3%), DocVQA (90.1%), MGSM (86.9%). It supports a 256K token context window for handling large documents. The model is available through 5 API providers. 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 Meta's latest advancement in AI technology.

Meta

Llama 4 Scout

Meta

Llama 4 Scout is a multimodal language model developed by Meta. It achieves strong performance with an average score of 67.3% across 12 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (90.6%), ChartQA (88.8%). The model shows particular specialization in vision tasks with an average performance of 81.9%. With a 20.0M token context window, it can handle extensive documents and complex multi-turn conversations. 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 2025, it represents Meta's latest advancement in AI technology.

Meta

Llama 3.2 90B Instruct

Meta

2024-09-25

Meta

Llama 4 Scout

Meta

2025-04-05

6 months newer

Pricing Comparison

Cost per million tokens (USD)

Meta

Llama 3.2 90B Instruct

Input:$0.35
Output:$0.40
Meta

Llama 4 Scout

$0.37 cheaper
Input:$0.08
Output:$0.30

Performance Metrics

Context window and performance specifications

Meta

Llama 3.2 90B Instruct

Max Context:256.0K
Parameters:90.0B
Meta

Llama 4 Scout

Larger context
Max Context:20.0M
Parameters:109.0B

Average performance across 8 common benchmarks

Meta

Llama 3.2 90B Instruct

Average Score:72.6%
Meta

Llama 4 Scout

+2.5%
Average Score:75.1%

Performance comparison across key benchmark categories

Meta

Llama 3.2 90B Instruct

vision
69.4%
general
+7.2%
73.5%
math
+0.2%
70.7%
Meta

Llama 4 Scout

vision
+12.5%
81.9%
general
66.3%
math
70.5%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores

Provider Availability & Performance

Available providers and their performance metrics

Meta

Llama 3.2 90B Instruct

5 providers

Together

Throughput: 57 tok/s
Latency: 0.5ms

Hyperbolic

Throughput: 42 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 24 tok/s
Latency: 0.5ms

Fireworks

Throughput: 50 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
Meta

Llama 4 Scout

6 providers

Together

Throughput: 106.9 tok/s
Latency: 0.54ms

DeepInfra

Throughput: 76.1 tok/s
Latency: 0.31ms

Fireworks

Throughput: 116.1 tok/s
Latency: 0.53ms

Groq

Throughput: 776.1 tok/s
Latency: 1.08ms

Novita

Throughput: 69.82 tok/s
Latency: 0.85ms

Lambda

Throughput: 139.7 tok/s
Latency: 0.43ms
Meta

Llama 3.2 90B Instruct

Avg Score:72.6%
Providers:5
Meta

Llama 4 Scout

+2.5%
Avg Score:75.1%
Providers:6