Compare GPT-4 Turbo vs. Mistral 7B Instruct

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Understand and compare GPT-4 Turbo vs. Mistral 7B Instruct

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

Overview

GPT-4 Turbo was released about 1 month after Mistral 7B Instruct.

	GPT-4 Turbo	Mistral 7B Instruct
Provider The entity that provides this model.	OpenAI	Mistral
Input Context Window The number of tokens supported by the input context window.	128K tokens	32K tokens
Maximum Output Tokens The number of tokens that can be generated by the model in a single request.	4,096 tokens	8,192 tokens
Release Date When the model was first released.	November 6th, 2023 8 months ago 2023-11-06	September 27th, 2023 9 months ago 2023-09-27

Pricing

GPT-4 Turbo is roughly 40x more expensive compared to Mistral 7B Instruct for input tokens and roughly 120x more expensive for output tokens.

	GPT-4 Turbo	Mistral 7B Instruct
Input Cost of input data provided to the model.	$10.00 per million tokens	$0.25 per million tokens
Output Cost of output tokens generated by the model.	$30.00 per million tokens	$0.25 per million tokens

Benchmarks

Compare relevant benchmarks between GPT-4 Turbo and Mistral 7B Instruct.

	GPT-4 Turbo	Mistral 7B Instruct
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	Benchmark not available.	60.1 (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.

GPT-4 Turbo, developed by OpenAI, features a large context window of 128,000 tokens. The model costs 1.0 cent per thousand tokens for input and 3.0 cents per thousand tokens for output. It is set to be released on November 6, 2023.

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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