Model Comparison

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

xAI

Grok-4

xAI

Grok-4 is a multimodal language model developed by xAI. It achieves strong performance with an average score of 63.1% across 7 benchmarks. It excels particularly in AIME 2025 (91.7%), HMMT25 (90.0%), GPQA (87.5%). It supports a 264K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents xAI's latest advancement in AI technology.

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 3.2 90B Instruct

Meta

2024-09-25

xAI

Grok-4

xAI

2025-07-09

9 months newer

Pricing Comparison

Cost per million tokens (USD)

xAI

Grok-4

Input:$3.00
Output:$15.00
Meta

Llama 3.2 90B Instruct

$17.25 cheaper
Input:$0.35
Output:$0.40

Performance Metrics

Context window and performance specifications

xAI

Grok-4

Larger context
Max Context:264.0K
Meta

Llama 3.2 90B Instruct

Max Context:256.0K
Parameters:90.0B

Average performance across 1 common benchmarks

xAI

Grok-4

+40.8%
Average Score:87.5%
Meta

Llama 3.2 90B Instruct

Average Score:46.7%

Performance comparison across key benchmark categories

xAI

Grok-4

general
69.3%
Meta

Llama 3.2 90B Instruct

general
+4.1%
73.5%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Grok-4

2024-12-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

xAI

Grok-4

2 providers

xAI

Throughput: 100 tok/s
Latency: 0.7ms

ZeroEval

Throughput: 100 tok/s
Latency: 0.7ms
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
xAI

Grok-4

+40.8%
Avg Score:87.5%
Providers:2
Meta

Llama 3.2 90B Instruct

Avg Score:46.7%
Providers:5