Understand and compare
GPT-4 Turbo 2024-04-09
vs.
Llama 3 70B Instruct
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Podial
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Overview
GPT-4 Turbo 2024-04-09 was released
9 days before
Llama 3 70B Instruct.
GPT-4 Turbo 2024-04-09
|
Llama 3 70B Instruct
|
|
|---|---|---|
|
Provider
The entity that provides this model.
|
OpenAI
|
Meta
|
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Input Context Window
The number of tokens supported by the input context window.
|
128K
tokens
|
8,000
tokens
|
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
4,096
tokens
|
2,048
tokens
|
|
Release Date
When the model was first released.
|
2024-04-09
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2024-04-18
|
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Knowledge Cutoff
Limit on the knowledge base used by the model.
|
December 2023
|
December 2023
|
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Open Source
|
|
|
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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 70B Instruct
|
|
|---|---|---|
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Input
Cost of input data provided to the model.
|
$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 70B Instruct.
|
GPT-4 Turbo 2024-04-09
|
Llama 3 70B Instruct
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
86.7
(5-shot)
|
82.0
(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.
|
|
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.
|
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)
|
51.0
(0-shot)
|
GPT-4 Turbo 2024-04-09, developed by OpenAI, features an impressive context window of 128,000 tokens. The model costs 1.0 cent per thousand tokens for input and 3.0 cents per thousand tokens for output. It is set to be released on April 9, 2024.
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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