Understand and compare
Mistral Large
vs.
GPT-4o Mini
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Overview
Mistral Large was released
5 months before
GPT-4o Mini.
Mistral Large
|
GPT-4o Mini
|
|
|---|---|---|
|
Provider
The entity that provides this model.
|
Mistral
|
OpenAI
|
|
Input Context Window
The number of tokens supported by the input context window.
|
32K
tokens
|
128K
tokens
|
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
4,096
tokens
|
16.4K
tokens
|
|
Release Date
When the model was first released.
|
2024-02-26
|
2024-07-18
|
|
Knowledge Cutoff
Limit on the knowledge base used by the model.
|
Unknown
|
October 2023
|
|
Open Source
|
|
|
|
API Providers
The providers that offer this model. (This is not an exhaustive list.)
|
|
|
Pricing
Mistral Large is
roughly 53x more expensive compared
to GPT-4o Mini for input tokens and
roughly 13x more expensive
for output tokens.
|
Mistral Large
|
GPT-4o Mini
|
|
|---|---|---|
|
Input
Cost of input data provided to the model.
|
$8.00
per million tokens
|
$0.15
per million tokens
|
|
Output
Cost of output tokens generated by the model.
|
$8.00
per million tokens
|
$0.60
per million tokens
|
Benchmarks
Compare relevant benchmarks between Mistral Large
and GPT-4o Mini.
|
Mistral Large
|
GPT-4o Mini
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
81.2
(5-shot)
|
82.0
(5-shot)
|
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
Benchmark not available.
|
59.4
|
|
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.
|
87.2
(0-shot)
|
|
MATH
Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
|
Benchmark not available.
|
70.2
(0-shot)
|
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