Understand and compare
GPT-3.5 Turbo
vs.
Gemini 1.5 Pro
Try
Podial
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Overview
GPT-3.5 Turbo was released
about 1 year before
Gemini 1.5 Pro.
GPT-3.5 Turbo
|
Gemini 1.5 Pro
|
|
|---|---|---|
|
Provider
The entity that provides this model.
|
OpenAI
|
Google
|
|
Input Context Window
The number of tokens supported by the input context window.
|
4,096
tokens
|
1M
tokens
|
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
4,096
tokens
|
8,192
tokens
|
|
Release Date
When the model was first released.
|
2022-11-28
|
2024-02-15
|
|
Knowledge Cutoff
Limit on the knowledge base used by the model.
|
September 2021
|
November 2023
|
|
Open Source
|
|
|
|
API Providers
The providers that offer this model. (This is not an exhaustive list.)
|
|
|
Pricing
GPT-3.5 Turbo is
roughly 14x cheaper compared
to Gemini 1.5 Pro for input and output tokens.
|
GPT-3.5 Turbo
|
Gemini 1.5 Pro
|
|
|---|---|---|
|
Input
Cost of input data provided to the model.
|
$0.50
per million tokens
|
$7.00
per million tokens
|
|
Output
Cost of output tokens generated by the model.
|
$1.50
per million tokens
|
$21.00
per million tokens
|
Benchmarks
Compare relevant benchmarks between GPT-3.5 Turbo
and Gemini 1.5 Pro.
|
GPT-3.5 Turbo
|
Gemini 1.5 Pro
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
70.0
(5-shot)
|
81.9
(5-shot)
|
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
Benchmark not available.
|
58.5
(0-shot)
|
|
HellaSwag
A challenging sentence completion benchmark.
|
85.5
(10-shot)
|
93.3
(10-shot)
|
|
GSM8K
Grade-school math problems benchmark.
|
Benchmark not available.
|
90.8
(11-shot)
|
|
HumanEval
A benchmark to measure functional correctness for synthesizing programs from docstrings.
|
Benchmark not available.
|
84.1
(0-shot)
|
|
MATH
Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
|
43.1
(0-shot)
|
67.7
(4-shot Minerva Prompt)
|
GPT-3.5 Turbo, developed by OpenAI, features a context window of 4096 tokens. It is priced at 0.05 cents per thousand tokens for input and 0.15 cents per thousand tokens for output. The model was released on November 28, 2022, and has achieved high scores in benchmarks like HellaSwag (85.5 in a 10-shot scenario) and MMLU (70.0 in a 5-shot scenario).
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.
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