Understand and compare
Chat Bison
vs.
Llama 3 70B Instruct
Try
Podial
Turn your documents into engaging podcast discussions.
Overview
Chat Bison was released
9 months before
Llama 3 70B Instruct.
Chat Bison
|
Llama 3 70B Instruct
|
|
|---|---|---|
|
Provider
The entity that provides this model.
|
Google
|
Meta
|
|
Input Context Window
The number of tokens supported by the input context window.
|
8,192
characters
|
8,000
tokens
|
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
2,048
characters
|
2,048
tokens
|
|
Release Date
When the model was first released.
|
2023-07-10
|
2024-04-18
|
|
Knowledge Cutoff
Limit on the knowledge base used by the model.
|
Mid 2021
|
December 2023
|
|
Open Source
|
|
|
|
API Providers
The providers that offer this model. (This is not an exhaustive list.)
|
|
|
Pricing
|
Chat Bison
|
Llama 3 70B Instruct
|
|
|---|---|---|
|
Input
Cost of input data provided to the model.
|
Pricing not available.
|
Pricing not available.
|
|
Output
Cost of output tokens generated by the model.
|
Pricing not available.
|
Pricing not available.
|
Benchmarks
Compare relevant benchmarks between Chat Bison
and Llama 3 70B Instruct.
|
Chat Bison
|
Llama 3 70B Instruct
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
78.3
(5-shot)
|
82.0
(5-shot)
|
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
Benchmark not available.
|
Benchmark not available.
|
|
HellaSwag
A challenging sentence completion benchmark.
|
Benchmark not available.
|
Benchmark not available.
|
|
GSM8K
Grade-school math problems benchmark.
|
Benchmark not available.
|
93.0
(8-shot)
|
|
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.
|
Benchmark not available.
|
51.0
(0-shot)
|
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, developed by Meta, features a context window of 8000 tokens. The model was released on April 18, 2024, and achieved a score of 82.0 in the MMLU benchmark under a 5-shot scenario.
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