Understand and compare
GPT-4 Turbo 2024-04-09
vs.
Mistral 7B Instruct
Overview
GPT-4 Turbo 2024-04-09 was released
7 months after
Mistral 7B Instruct.
GPT-4 Turbo 2024-04-09
|
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.
|
2024-04-09
|
2023-09-27
|
Pricing
GPT-4 Turbo 2024-04-09 is
roughly 40x more expensive compared
to Mistral 7B Instruct for input tokens and
roughly 120x more expensive
for output tokens.
|
GPT-4 Turbo 2024-04-09
|
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 2024-04-09
and Mistral 7B Instruct.
|
GPT-4 Turbo 2024-04-09
|
Mistral 7B Instruct
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
Benchmark not available.
|
60.1
(5-shot)
|
|
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 2024-04-09, developed by OpenAI, features an impressive 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 April 9, 2024.
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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