Understand and compare
GPT-3.5 Turbo
vs.
Chat Bison
Try
Podial
Turn your documents into engaging podcast discussions.
Overview
GPT-3.5 Turbo was released
7 months before
Chat Bison.
GPT-3.5 Turbo
|
Chat Bison
|
|
|---|---|---|
|
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
|
8,192
characters
|
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
4,096
tokens
|
2,048
characters
|
|
Release Date
When the model was first released.
|
2022-11-28
|
2023-07-10
|
|
Knowledge Cutoff
Limit on the knowledge base used by the model.
|
September 2021
|
Mid 2021
|
|
Open Source
|
|
|
|
API Providers
The providers that offer this model. (This is not an exhaustive list.)
|
|
|
Pricing
|
GPT-3.5 Turbo
|
Chat Bison
|
|
|---|---|---|
|
Input
Cost of input data provided to the model.
|
$0.50
per million tokens
|
Pricing not available.
|
|
Output
Cost of output tokens generated by the model.
|
$1.50
per million tokens
|
Pricing not available.
|
Benchmarks
Compare relevant benchmarks between GPT-3.5 Turbo
and Chat Bison.
|
GPT-3.5 Turbo
|
Chat Bison
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
70.0
(5-shot)
|
78.3
(5-shot)
|
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
Benchmark not available.
|
Benchmark not available.
|
|
HellaSwag
A challenging sentence completion benchmark.
|
85.5
(10-shot)
|
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.
|
Benchmark not available.
|
Benchmark not available.
|
|
MATH
Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
|
43.1
(0-shot)
|
Benchmark not available.
|
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).
Chat Bison, developed by Google, features a context window of 8192 tokens. The model costs 0.025 cents per thousand tokens for input and 0.05 cents per thousand tokens for output. It was released on July 10, 2023, and achieved a score of 78.3 in the MMLU benchmark in a 5-shot scenario.
Llama 3 70B Instruct
Mistral 8x7B Instruct
Measure & Improve LLM
Product Performance.
Get Started
© 2023-2024 Context