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Discover how Anthropic's Claude 3.5 Sonnet and Mistral's Mistral Large 2 stack up against each other in this comprehensive comparison of two leading AI language models.

Released in June 2024 and July 2024 respectively, these models represent significant advancements in artificial intelligence, with Claude 3.5 Sonnet offering a 200,000-token context window and Mistral Large 2 featuring a 128,000-token capacity. Their distinct approaches to natural language processing are reflected in their benchmark performances, with Claude 3.5 Sonnet achieving 90.4% on MMLU and Mistral Large 2 scoring 84%, making this comparison essential for developers and organizations seeking the right AI solution for their specific needs.

Models Overview

Anthropic Claude 3.5 Sonnet
Anthropic Mistral Large 2

Provider

Company that developed the model
Anthropic Mistral

Context Length

Maximum number of tokens the model can process
200K 128K

Maximum Output

Maximum number of tokens the model can generate in a single response
4096 8192

Release Date

Date when the model was released
20-06-2024 24-07-2024

Knowledge Cutoff

Training data cutoff date
April 2024 Unknown

Open Source

Whether the model's code is open-source
FALSE TRUE

API Providers

API providers that offer access to the model
Anthropic API, Vertex AI, AWS Bedrock Azure AI, AWS Bedrock, Google Cloud Vertex AI Model Garden, Snowflake Cortex, Hugging Face

Pricing Comparison

Compare the pricing of Anthropic's Claude 3.5 Sonnet and Mistral's Mistral Large 2 to determine the most cost-effective solution for your AI needs.

Anthropic Claude 3.5 Sonnet
Anthropic Mistral Large 2

Input Cost

Cost per million input tokens
$3 / 1M tokens $3 / 1M tokens

Output Cost

Cost per million tokens generated
$15 / 1M tokens $9 / 1M tokens

Comparing Benchmarks and Performance

Compare the performances of Anthropic's Claude 3.5 Sonnet and Mistral's Mistral Large 2 on industry benchmarks. This section provides a detailed comparison on MMLU, MMMU, HumanEval, MATH and other key benchmarks.

Anthropic Claude 3.5 Sonnet
Anthropic Mistral Large 2

MMLU

Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
90.4% 84%

MMMU

A wide ranging multi-discipline and multimodal benchmark.
70.4% Benchmark not available

HellaSwag

A challenging sentence completion benchmark.
Benchmark not available 85%

GSM8K

Grade-school math problems benchmark.
96.4% Benchmark not available

HumanEval

A benchmark to measure functional correctness for synthesizing programs from docstrings.
93.7% 87%

MATH

Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
78.3% 72%

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