Understand and compare
Mistral Large
vs.
GPT-4 32K 0613
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Podial
Turn your documents into engaging podcast discussions.
Overview
Mistral Large was released
9 months after
GPT-4 32K 0613.
Mistral Large
|
GPT-4 32K 0613
|
|
---|---|---|
Provider
The entity that provides this model.
|
Mistral
|
OpenAI
|
Input Context Window
The number of tokens supported by the input context window.
|
32K
tokens
|
32.8K
tokens
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
4,096
tokens
|
Not specified.
|
Release Date
When the model was first released.
|
2024-02-26
|
2023-06-13
|
Knowledge Cutoff
Limit on the knowledge base used by the model.
|
Unknown
|
Unknown
|
Open Source
|
|
|
API Providers
The providers that offer this model. (This is not an exhaustive list.)
|
|
|
Pricing
Mistral Large is
roughly 7.5x cheaper compared
to GPT-4 32K 0613 for input tokens and
roughly 15x cheaper
for output tokens.
Mistral Large
|
GPT-4 32K 0613
|
|
---|---|---|
Input
Cost of input data provided to the model.
|
$8.00
per million tokens
|
$60.00
per million tokens
|
Output
Cost of output tokens generated by the model.
|
$8.00
per million tokens
|
$120.00
per million tokens
|
Benchmarks
Compare relevant benchmarks between Mistral Large
and GPT-4 32K 0613.
Mistral Large
|
GPT-4 32K 0613
|
|
---|---|---|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
81.2
(5-shot)
|
Benchmark not available.
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
Benchmark not available.
|
Benchmark not available.
|
HellaSwag
A challenging sentence completion benchmark.
|
89.2
(10-shot)
|
Benchmark not available.
|
GSM8K
Grade-school math problems benchmark.
|
Benchmark not available.
|
Benchmark not available.
|
HumanEval
A benchmark to measure functional correctness for synthesizing programs from docstrings.
|
Benchmark not available.
|
Benchmark not available.
|
MATH
Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
|
Benchmark not available.
|
Benchmark not available.
|
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 32K 0613, developed by OpenAI, features a context window of 32768 tokens. The model costs 6.0 cents per thousand tokens for input and 12.0 cents per thousand tokens for output. It was released on June 13, 2023.
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