Compare Gemini 1.5 Pro vs. Mistral Large

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Understand and compare Gemini 1.5 Pro vs. Mistral Large

Generate side-by-side samples for these models in the Context.ai playground

Overview

Gemini 1.5 Pro was released 11 days before Mistral Large.

	Gemini 1.5 Pro	Mistral Large
Provider The entity that provides this model.	Google	Mistral
Input Context Window The number of tokens supported by the input context window.	1M tokens	32K tokens
Maximum Output Tokens The number of tokens that can be generated by the model in a single request.	8,192 tokens	4,096 tokens
Release Date When the model was first released.	February 15th, 2024 5 months ago 2024-02-15	February 26th, 2024 4 months ago 2024-02-26

Pricing

Gemini 1.5 Pro is roughly 12.5% cheaper compared to Mistral Large for input tokens and roughly 2.6x more expensive for output tokens.

	Gemini 1.5 Pro	Mistral Large
Input Cost of input data provided to the model.	$7.00 per million tokens	$8.00 per million tokens
Output Cost of output tokens generated by the model.	$21.00 per million tokens	$8.00 per million tokens

Benchmarks

Compare relevant benchmarks between Gemini 1.5 Pro and Mistral Large.

	Gemini 1.5 Pro	Mistral Large
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	81.9 (5-shot) Source	81.2 (5-shot) Source
MMMU A wide ranging multi-discipline and multimodal benchmark.	58.5 (0-shot) Source	Benchmark not available.
HellaSwag A challenging sentence completion benchmark.	Benchmark not available.	89.2 (10-shot) Source

Gemini 1.5 Pro by Google features a vast context window of 1,000,000 tokens. The model is priced at 0.7 cents per thousand tokens for input and 2.1 cents per thousand tokens for output. It was launched on February 15, 2024. In benchmark tests, it achieved a score of 58.5 in MMMU with a 0-shot scenario and 81.9 in MMLU with a 5-shot scenario.

Mistral Large, developed by Mistral, features a context window of 32000 tokens. The model is priced at 0.8 cents per thousand tokens for both input and output. It was released on February 26, 2024, and has achieved impressive scores in benchmarks like MMLU (81.2 in a 5-shot scenario) and HellaSwag (89.2 in a 10-shot scenario).

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