Understand and compare
Gemini 1.5 Pro
vs.
GPT-4 32K 0613
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
|
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.
|
Benchmark not available.
|
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.
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