Understand and compare
Gemini 1.5 Pro
vs.
GPT-4 32K 0613
Try
Podial
Turn your documents into engaging podcast discussions.
Overview
Gemini 1.5 Pro was released
8 months after
GPT-4 32K 0613.
Gemini 1.5 Pro
|
GPT-4 32K 0613
|
|
|---|---|---|
|
Provider
The entity that provides this model.
|
Google
|
OpenAI
|
|
Input Context Window
The number of tokens supported by the input context window.
|
1M
tokens
|
32.8K
tokens
|
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
8,192
tokens
|
Not specified.
|
|
Release Date
When the model was first released.
|
2024-02-15
|
2023-06-13
|
|
Knowledge Cutoff
Limit on the knowledge base used by the model.
|
November 2023
|
Unknown
|
|
Open Source
|
|
|
|
API Providers
The providers that offer this model. (This is not an exhaustive list.)
|
|
|
Pricing
Gemini 1.5 Pro is
roughly 8.6x cheaper compared
to GPT-4 32K 0613 for input tokens and
roughly 5.7x cheaper
for output tokens.
|
Gemini 1.5 Pro
|
GPT-4 32K 0613
|
|
|---|---|---|
|
Input
Cost of input data provided to the model.
|
$7.00
per million tokens
|
$60.00
per million tokens
|
|
Output
Cost of output tokens generated by the model.
|
$21.00
per million tokens
|
$120.00
per million tokens
|
Benchmarks
Compare relevant benchmarks between Gemini 1.5 Pro
and GPT-4 32K 0613.
|
Gemini 1.5 Pro
|
GPT-4 32K 0613
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
81.9
(5-shot)
|
Benchmark not available.
|
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
58.5
(0-shot)
|
Benchmark not available.
|
|
HellaSwag
A challenging sentence completion benchmark.
|
93.3
(10-shot)
|
Benchmark not available.
|
|
GSM8K
Grade-school math problems benchmark.
|
90.8
(11-shot)
|
Benchmark not available.
|
|
HumanEval
A benchmark to measure functional correctness for synthesizing programs from docstrings.
|
84.1
(0-shot)
|
Benchmark not available.
|
|
MATH
Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
|
67.7
(4-shot Minerva Prompt)
|
Benchmark not available.
|
Gemini 1.5 Pro by Google features a vast context window of 1,000,000 tokens. The model is priced at 0.7 cents per thousand tokens for input and 2.1 cents per thousand tokens for output. It was launched on February 15, 2024. In benchmark tests, it achieved a score of 58.5 in MMMU with a 0-shot scenario and 81.9 in MMLU with a 5-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.
Claude 3 Sonnet
Llama 3.1 70B Instruct
Measure & Improve LLM
Product Performance.
Get Started
© 2023-2024 Context