LLM Comparison Tool
Gemini 1.5 Pro vs Mixtral 8x7B
Comparison of Large Language Model capabilities, costs, and benchmark performance between Google's Gemini 1.5 Pro and Replicate's Mixtral 8x7B.
Gemini 1.5 Pro is 2233.3% more expensive than Mixtral 8x7B
Gemini 1.5 Pro was released 2 months after after Mixtral 8x7B
Gemini 1.5 Pro shows better general knowledge performance with a 11.3% difference in MMLU scores
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Model Overview 🤖
Provider
Provider
Organization providing the model API.
Google
ReplicateModel Name
Name of the model.
Gemini 1.5 Pro
Mixtral 8x7B
Pricing
Input Processing
Cost per million tokens for processing prompts and inputs.
$7.00per million tokens
$0.30per million tokens
Generation
Cost per million tokens for model-generated responses.
$21.00per million tokens
$1.00per million tokens
Model Details
Context Length
Maximum input length the model can process at once.
1Ktokens
32000Ktokens
Response Length
Maximum length of a single generated response.
8Ktokens
4Ktokens
Initial Release
First public release date.
February 15, 2024
December 11, 2023
Training Data Cutoff
Latest date of data included in training.
November 2023
Unknown
License Type
Model licensing and availability.
Proprietary
Open Source
Performance Metrics
General Knowledge (MMLU)
Accuracy on diverse academic and real-world topics.
81.9score
5-shotsource
70.6score
5-shotsource
Multimodal Tasks (MMMU)
Performance on tasks combining text, images, and other media.
58.5score
0-shotsource
Not available
Common Sense (HellaSwag)
Understanding of everyday scenarios and situations.
93.3score
10-shotsource
Not available
Code Generation (HumanEval)
Ability to write and understand programming code.
84.1score
0-shotsource
Not available
Mathematical Ability (MATH)
Accuracy in mathematical computations and reasoning.
67.7score
Not available
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