Compare Mistral Large vs. o1 Mini 2024-09-12

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Understand and compare Mistral Large vs. o1 Mini 2024-09-12

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Overview

Mistral Large was released 7 months before o1 Mini 2024-09-12.

	Mistral Large	o1 Mini 2024-09-12
Provider The entity that provides this model.	Mistral	OpenAI
Input Context Window The number of tokens supported by the input context window.	32K tokens	128K tokens
Maximum Output Tokens The number of tokens that can be generated by the model in a single request.	4,096 tokens	65.5K tokens
Release Date When the model was first released.	February 26th, 2024 7 months ago 2024-02-26	September 12th, 2024 7 days ago 2024-09-12
Knowledge Cutoff Limit on the knowledge base used by the model.	Unknown	October 2023 October 2023
Open Source	Yes	No
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	OpenAI

Pricing

Mistral Large is roughly 2.7x more expensive compared to o1 Mini 2024-09-12 for input tokens and roughly 33.3% cheaper for output tokens.

	Mistral Large	o1 Mini 2024-09-12
Input Cost of input data provided to the model.	$8.00 per million tokens	$3.00 per million tokens
Output Cost of output tokens generated by the model.	$8.00 per million tokens	$12.00 per million tokens

Benchmarks

Compare relevant benchmarks between Mistral Large and o1 Mini 2024-09-12.

	Mistral Large	o1 Mini 2024-09-12
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	81.2 (5-shot) Source	Benchmark not available.
MMMU A wide ranging multi-discipline and multimodal benchmark.	Benchmark not available.	Benchmark not available.
HellaSwag A challenging sentence completion benchmark.	89.2 (10-shot) Source	Benchmark not available.
GSM8K Grade-school math problems benchmark.	Benchmark not available.	Benchmark not available.
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.	Benchmark not available.