Understand and compare
Mistral Large
vs.
GPT-4
Overview
Mistral Large was released
12 months after
GPT-4.
Mistral Large
|
GPT-4
|
|
|---|---|---|
|
Provider
The entity that provides this model.
|
Mistral
|
OpenAI
|
|
Input Context Window
The number of tokens supported by the input context window.
|
32K
tokens
|
8,192
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.
|
2024-02-26
|
2023-03-14
|
Pricing
Mistral Large is
roughly 3.7x cheaper compared
to GPT-4 for input tokens and
roughly 7.5x cheaper
for output tokens.
|
Mistral Large
|
GPT-4
|
|
|---|---|---|
|
Input
Cost of input data provided to the model.
|
$8.00
per million tokens
|
$30.00
per million tokens
|
|
Output
Cost of output tokens generated by the model.
|
$8.00
per million tokens
|
$60.00
per million tokens
|
Benchmarks
Compare relevant benchmarks between Mistral Large
and GPT-4.
|
Mistral Large
|
GPT-4
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
81.2
(5-shot)
|
86.4
(5-shot)
|
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
Benchmark not available.
|
34.9
|
|
HellaSwag
A challenging sentence completion benchmark.
|
89.2
(10-shot)
|
95.3
(10-shot)
|
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).
GPT-4, developed by OpenAI, features a context window of 8192 tokens. The model costs 3.0 cents per thousand tokens for input and 6.0 cents per thousand tokens for output. It was released on March 14, 2023, and has achieved impressive scores in benchmarks like HellaSwag with a score of 95.3 in a 10-shot scenario and MMLU with a score of 86.4 in a 5-shot scenario.
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