Model Comparison

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

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.

Mistral AI

Mistral Small 3 24B Base

Mistral AI

Mistral Small 3 24B Base is a multimodal language model developed by Mistral AI. It achieves strong performance with an average score of 67.0% across 9 benchmarks. It excels particularly in ARC-C (91.3%), GSM8k (80.7%), MMLU (80.7%). 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 2025, it represents Mistral AI's latest advancement in AI technology.

Mistral AI

Mistral Small 3 24B Base

Mistral AI

2025-01-30

Meta

Llama 4 Scout

Meta

2025-04-05

2 months newer

Performance Metrics

Context window and performance specifications

Meta

Llama 4 Scout

Larger context
Max Context:20.0M
Parameters:109.0B
Mistral AI

Mistral Small 3 24B Base

Max Context:-
Parameters:23.6B

Average performance across 5 common benchmarks

Meta

Llama 4 Scout

+8.8%
Average Score:65.8%
Mistral AI

Mistral Small 3 24B Base

Average Score:57.0%

Performance comparison across key benchmark categories

Meta

Llama 4 Scout

math
+7.2%
70.5%
code
50.3%
general
+3.8%
66.3%
Mistral AI

Mistral Small 3 24B Base

math
63.4%
code
+17.4%
67.7%
general
62.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Mistral Small 3 24B Base

2023-10-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

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
Mistral AI

Mistral Small 3 24B Base

0 providers
Meta

Llama 4 Scout

+8.8%
Avg Score:65.8%
Providers:6
Mistral AI

Mistral Small 3 24B Base

Avg Score:57.0%
Providers:0