Understand and compare
Gemini Pro
vs.
Llama 3 70B Instruct
Overview
Gemini Pro was released
4 months before
Llama 3 70B Instruct.
Gemini Pro
|
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.
|
32.8K
characters
|
8,000
tokens
|
|
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
|
8,192
characters
|
2,048
tokens
|
|
Release Date
When the model was first released.
|
2023-12-13
|
2024-04-18
|
Pricing
|
Gemini Pro
|
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 Gemini Pro
and Llama 3 70B Instruct.
|
Gemini Pro
|
Llama 3 70B Instruct
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
71.8
(5-shot)
|
82.0
(5-shot)
|
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
47.9
(pass@1)
|
Benchmark not available.
|
|
HellaSwag
A challenging sentence completion benchmark.
|
Benchmark not available.
|
Benchmark not available.
|
Gemini Pro, developed by Google, features a context window of 32768 tokens. The model costs 0.0125 cents per thousand tokens for input and 0.0375 cents per thousand tokens for output. It was released on December 13, 2023, and has achieved a score of 47.9 in the MMMU benchmark with a "pass@1" caveat and a score of 71.8 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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