Compare Gemini Ultra vs. Llama 3.1 8B Instruct

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Overview

	Gemini Ultra	Llama 3.1 8B 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	128K 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.	Unknown	July 23rd, 2024 5 months ago 2024-07-23
Knowledge Cutoff Limit on the knowledge base used by the model.	Unknown	December 2023 December 2023
Open Source	No	Yes
API Providers The providers that offer this model. (This is not an exhaustive list.)	Google Cloud Vertex AI Model Garden	Azure AI, AWS Bedrock, Google Cloud Vertex AI Model Garden, NVIDIA NIM, IBM watsonx

Pricing

	Gemini Ultra	Llama 3.1 8B 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 Ultra and Llama 3.1 8B Instruct.

	Gemini Ultra	Llama 3.1 8B Instruct
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	83.7 (5-shot) Source	66.7 (5-shot) Source
MMMU A wide ranging multi-discipline and multimodal benchmark.	59.4 (0-shot pass@1) Source	Benchmark not available.
HellaSwag A challenging sentence completion benchmark.	Benchmark not available.	Benchmark not available.
GSM8K Grade-school math problems benchmark.	88.9 (11-shot) Source	84.5 (8-shot) Source
HumanEval A benchmark to measure functional correctness for synthesizing programs from docstrings.	74.4 (0-shot) Source	Benchmark not available.
MATH Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.	53.2 (4-shot Minerva Prompt) Source	51.9 (0-shot) Source

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