Understand and compare
GPT-4 32K 0613
vs.
Llama 3 70B Instruct
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Shepherd
Make it trivial for customers to self-host your SaaS.
Overview
GPT-4 32K 0613 was released
10 months before
Llama 3 70B Instruct.
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Provider
The entity that provides this model.
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Input Context Window
The number of tokens supported by the input context window.
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32.8K
tokens
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8,000
tokens
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Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
Not specified.
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2,048
tokens
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Release Date
When the model was first released.
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2023-06-13
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2024-04-18
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Knowledge Cutoff
Limit on the knowledge base used by the model.
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Unknown
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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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Input
Cost of input data provided to the model.
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$60.00
per million tokens
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Pricing not available.
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Output
Cost of output tokens generated by the model.
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$120.00
per million tokens
|
Pricing not available.
|
Benchmarks
Compare relevant benchmarks between GPT-4 32K 0613
and Llama 3 70B Instruct.
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MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
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Benchmark not available.
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82.0
(5-shot)
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MMMU
A wide ranging multi-discipline and multimodal benchmark.
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Benchmark not available.
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Benchmark not available.
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HellaSwag
A challenging sentence completion benchmark.
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Benchmark not available.
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Benchmark not available.
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GSM8K
Grade-school math problems benchmark.
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Benchmark not available.
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93.0
(8-shot)
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HumanEval
A benchmark to measure functional correctness for synthesizing programs from docstrings.
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Benchmark not available.
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Benchmark not available.
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MATH
Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
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Benchmark not available.
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51.0
(0-shot)
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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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