Understand and compare
GPT-4 Turbo 0125
vs.
GPT-4o Mini
Overview
GPT-4 Turbo 0125 was released
6 months before
GPT-4o Mini.
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Provider
The entity that provides this model.
|
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Input Context Window
The number of tokens supported by the input context window.
|
128K
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.
|
2024-01-25
|
2024-07-18
|
Knowledge Cutoff
Limit on the knowledge base used by the model.
|
December 2023
|
October 2023
|
Open Source
|
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API Providers
The providers that offer this model. (This is not an exhaustive list.)
|
|
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Pricing
GPT-4 Turbo 0125 is
roughly 67x more expensive compared
to GPT-4o Mini for input tokens and
roughly 50x more expensive
for output tokens.
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Input
Cost of input data provided to the model.
|
$10.00
per million tokens
|
$0.15
per million tokens
|
Output
Cost of output tokens generated by the model.
|
$30.00
per million tokens
|
$0.60
per million tokens
|
Benchmarks
Compare relevant benchmarks between GPT-4 Turbo 0125
and GPT-4o Mini.
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MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
85.4
(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.
|
Benchmark not available.
|
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.
|
86.6
(0-shot)
|
87.2
(0-shot)
|
MATH
Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
|
64.5
(0-shot)
|
70.2
(0-shot)
|
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