Model Comparison

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

Meta

Llama 3.1 405B Instruct

Meta

Llama 3.1 405B Instruct is a language model developed by Meta. It achieves strong performance with an average score of 79.2% across 18 benchmarks. It excels particularly in ARC-C (96.9%), GSM8k (96.8%), API-Bank (92.0%). It supports a 256K token context window for handling large documents. The model is available through 8 API providers. Released in 2024, it represents Meta's latest advancement in AI technology.

Mistral AI

Mistral Small 3.2 24B Instruct

Mistral AI

Mistral Small 3.2 24B Instruct is a multimodal language model developed by Mistral AI. It achieves strong performance with an average score of 69.8% across 15 benchmarks. It excels particularly in DocVQA (94.9%), AI2D (92.9%), HumanEval Plus (92.9%). The model shows particular specialization in code tasks with an average performance of 85.6%. 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.

Meta

Llama 3.1 405B Instruct

Meta

2024-07-23

Mistral AI

Mistral Small 3.2 24B Instruct

Mistral AI

2025-06-20

11 months newer

Performance Metrics

Context window and performance specifications

Meta

Llama 3.1 405B Instruct

Larger context
Max Context:256.0K
Parameters:405.0B
Mistral AI

Mistral Small 3.2 24B Instruct

Max Context:-
Parameters:23.6B

Average performance across 4 common benchmarks

Meta

Llama 3.1 405B Instruct

+5.0%
Average Score:71.3%
Mistral AI

Mistral Small 3.2 24B Instruct

Average Score:66.3%

Performance comparison across key benchmark categories

Meta

Llama 3.1 405B Instruct

math
+19.1%
87.4%
code
81.4%
general
+8.7%
73.2%
Mistral AI

Mistral Small 3.2 24B Instruct

math
68.3%
code
+4.2%
85.6%
general
64.6%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Mistral Small 3.2 24B Instruct

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 3.1 405B Instruct

8 providers

Together

Throughput: 35 tok/s
Latency: 0.5ms

Hyperbolic

Throughput: 40 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 27 tok/s
Latency: 0.5ms

Google

Throughput: 42 tok/s
Latency: 0.4ms

Fireworks

Throughput: 78 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms

Lambda

Throughput: 42 tok/s
Latency: 0.5ms

Replicate

Throughput: 22 tok/s
Latency: 0.5ms
Mistral AI

Mistral Small 3.2 24B Instruct

0 providers
Meta

Llama 3.1 405B Instruct

+5.0%
Avg Score:71.3%
Providers:8
Mistral AI

Mistral Small 3.2 24B Instruct

Avg Score:66.3%
Providers:0