Understand and compare
Llama 3 70B Instruct
vs.
GPT-4
Overview
Llama 3 70B Instruct was released
about 1 year after
GPT-4.
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|
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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.
|
8,000
tokens
|
8,192
tokens
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
2,048
tokens
|
8,192
tokens
|
Release Date
When the model was first released.
|
2024-04-18
|
2023-03-14
|
Pricing
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Input
Cost of input data provided to the model.
|
Pricing not available.
|
$30.00
per million tokens
|
Output
Cost of output tokens generated by the model.
|
Pricing not available.
|
$60.00
per million tokens
|
Benchmarks
Compare relevant benchmarks between Llama 3 70B Instruct
and GPT-4.
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MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
82.0
(5-shot)
|
86.4
(5-shot)
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
Benchmark not available.
|
34.9
|
HellaSwag
A challenging sentence completion benchmark.
|
Benchmark not available.
|
95.3
(10-shot)
|
![](https://with.context.ai/assets/meta-b0d3356199f47d298a09385682430689ec6f3da855e3be6d323d4f11b7283d6b.png)
GPT-4, developed by OpenAI, features a context window of 8192 tokens. The model costs 3.0 cents per thousand tokens for input and 6.0 cents per thousand tokens for output. It was released on March 14, 2023, and has achieved impressive scores in benchmarks like HellaSwag with a score of 95.3 in a 10-shot scenario and MMLU with a score of 86.4 in a 5-shot scenario.
![](https://with.context.ai/assets/openai-5e3235388de8d8803af80dc53ea68559e0a4f698ae58b3eb9ea8048515f1bac1.png)
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