Understand and compare
Gemini Ultra
vs.
GPT-4 Turbo 2024-04-09
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Podial
Turn your documents into engaging podcast discussions.
Overview
Gemini Ultra
|
GPT-4 Turbo 2024-04-09
|
|
|---|---|---|
|
Provider
The entity that provides this model.
|
Google
|
OpenAI
|
|
Input Context Window
The number of tokens supported by the input context window.
|
32.8K
characters
|
128K
tokens
|
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
8,192
characters
|
4,096
tokens
|
|
Release Date
When the model was first released.
|
Unknown
|
2024-04-09
|
|
Knowledge Cutoff
Limit on the knowledge base used by the model.
|
Unknown
|
December 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
|
Gemini Ultra
|
GPT-4 Turbo 2024-04-09
|
|
|---|---|---|
|
Input
Cost of input data provided to the model.
|
Pricing not available.
|
$10.00
per million tokens
|
|
Output
Cost of output tokens generated by the model.
|
Pricing not available.
|
$30.00
per million tokens
|
Benchmarks
Compare relevant benchmarks between Gemini Ultra
and GPT-4 Turbo 2024-04-09.
|
Gemini Ultra
|
GPT-4 Turbo 2024-04-09
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
83.7
(5-shot)
|
86.7
(5-shot)
|
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
59.4
(0-shot pass@1)
|
Benchmark not available.
|
|
HellaSwag
A challenging sentence completion benchmark.
|
Benchmark not available.
|
Benchmark not available.
|
|
GSM8K
Grade-school math problems benchmark.
|
88.9
(11-shot)
|
Benchmark not available.
|
|
HumanEval
A benchmark to measure functional correctness for synthesizing programs from docstrings.
|
74.4
(0-shot)
|
88.2
(0-shot)
|
|
MATH
Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
|
53.2
(4-shot Minerva Prompt)
|
73.4
(0-shot)
|
Gemini Ultra, developed by Google, features a large context window of 32768 tokens. The model has excelled in benchmarks like MMMU with a score of 59.4 in a 0-shot pass@1 scenario and MMLU with a score of 83.7 in a 5-shot scenario.
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.
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