Compare Gemini 1.5 Pro vs. Mistral 7B Instruct

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Understand and compare Gemini 1.5 Pro vs. Mistral 7B Instruct

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

Overview

Gemini 1.5 Pro was released 5 months after Mistral 7B Instruct.

	Gemini 1.5 Pro	Mistral 7B Instruct
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	8,192 tokens
Release Date When the model was first released.	February 15th, 2024 5 months ago 2024-02-15	September 27th, 2023 9 months ago 2023-09-27

Pricing

Gemini 1.5 Pro is roughly 28x more expensive compared to Mistral 7B Instruct for input tokens and roughly 84x more expensive for output tokens.

	Gemini 1.5 Pro	Mistral 7B Instruct
Input Cost of input data provided to the model.	$7.00 per million tokens	$0.25 per million tokens
Output Cost of output tokens generated by the model.	$21.00 per million tokens	$0.25 per million tokens

Benchmarks

Compare relevant benchmarks between Gemini 1.5 Pro and Mistral 7B Instruct.

	Gemini 1.5 Pro	Mistral 7B Instruct
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	81.9 (5-shot) Source	60.1 (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.	Benchmark not available.

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 7B Instruct, developed by Mistral, features a large context window of 32000 tokens. The model is priced at 0.025 cents per thousand tokens for both input and output. It was released on September 27, 2023, and achieved a score of 60.1 in the MMLU benchmark under a 5-shot scenario.

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