Compare Mistral Large 2 vs. Llama 3.1 405B Instruct

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Turn your documents into engaging podcast discussions.

Overview

Mistral Large 2 was released 1 day after Llama 3.1 405B Instruct.

	Mistral Large 2	Llama 3.1 405B Instruct
Provider The entity that provides this model.	Mistral	Meta
Input Context Window The number of tokens supported by the input context window.	128K tokens	128K tokens
Maximum Output Tokens The number of tokens that can be generated by the model in a single request.	8,192 tokens	2,048 tokens
Release Date When the model was first released.	July 24th, 2024 3 months ago 2024-07-24	July 23rd, 2024 4 months ago 2024-07-23
Knowledge Cutoff Limit on the knowledge base used by the model.	Unknown	December 2023 December 2023
Open Source	Yes	Yes
API Providers The providers that offer this model. (This is not an exhaustive list.)	Azure AI, AWS Bedrock, Google Cloud Vertex AI Model Garden, Snowflake Cortex	Azure AI, AWS Bedrock, Google Cloud Vertex AI Model Garden, NVIDIA NIM, IBM watsonx

Pricing

	Mistral Large 2	Llama 3.1 405B Instruct
Input Cost of input data provided to the model.	$3.00 per million tokens	Pricing not available.
Output Cost of output tokens generated by the model.	$9.00 per million tokens	Pricing not available.

Benchmarks

Compare relevant benchmarks between Mistral Large 2 and Llama 3.1 405B Instruct.

	Mistral Large 2	Llama 3.1 405B Instruct
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	84.0 (5-shot) Source	85.2 (5-shot) Source
MMMU A wide ranging multi-discipline and multimodal benchmark.	Benchmark not available.	Benchmark not available.
HellaSwag A challenging sentence completion benchmark.	Benchmark not available.	Benchmark not available.
GSM8K Grade-school math problems benchmark.	Benchmark not available.	96.8 (8-shot) Source
HumanEval A benchmark to measure functional correctness for synthesizing programs from docstrings.	Benchmark not available.	Benchmark not available.
MATH Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.	Benchmark not available.	73.8 (0-shot) Source

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