Understand and compare
GPT-4 Turbo 2024-04-09
vs.
Llama 3.1 405B Instruct
Try
Podial
Turn your documents into engaging podcast discussions.
Overview
GPT-4 Turbo 2024-04-09 was released
4 months before
Llama 3.1 405B Instruct.
GPT-4 Turbo 2024-04-09
|
Llama 3.1 405B Instruct
|
|
|---|---|---|
|
Provider
The entity that provides this model.
|
OpenAI
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Meta
|
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Input Context Window
The number of tokens supported by the input context window.
|
128K
tokens
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128K
tokens
|
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
4,096
tokens
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2,048
tokens
|
|
Release Date
When the model was first released.
|
2024-04-09
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2024-07-23
|
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Knowledge Cutoff
Limit on the knowledge base used by the model.
|
December 2023
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December 2023
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Open Source
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|
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API Providers
The providers that offer this model. (This is not an exhaustive list.)
|
|
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Pricing
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GPT-4 Turbo 2024-04-09
|
Llama 3.1 405B Instruct
|
|
|---|---|---|
|
Input
Cost of input data provided to the model.
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$10.00
per million tokens
|
Pricing not available.
|
|
Output
Cost of output tokens generated by the model.
|
$30.00
per million tokens
|
Pricing not available.
|
Benchmarks
Compare relevant benchmarks between GPT-4 Turbo 2024-04-09
and Llama 3.1 405B Instruct.
|
GPT-4 Turbo 2024-04-09
|
Llama 3.1 405B Instruct
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
86.7
(5-shot)
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85.2
(5-shot)
|
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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.
|
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GSM8K
Grade-school math problems benchmark.
|
Benchmark not available.
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96.8
(8-shot)
|
|
HumanEval
A benchmark to measure functional correctness for synthesizing programs from docstrings.
|
88.2
(0-shot)
|
Benchmark not available.
|
|
MATH
Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
|
73.4
(0-shot)
|
73.8
(0-shot)
|
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