Compare Gemini Ultra vs. Llama 3 70B Instruct

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Overview

	Gemini Ultra	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.	Unknown	April 18th, 2024 7 months ago 2024-04-18
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 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 Ultra and Llama 3 70B Instruct.

	Gemini Ultra	Llama 3 70B Instruct
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	83.7 (5-shot) Source	82.0 (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	93.0 (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	51.0 (0-shot) Source

Gemini Ultra, developed by Google, features a large context window of 32768 tokens. The model has excelled in benchmarks like MMMU with a score of 59.4 in a 0-shot pass@1 scenario and MMLU with a score of 83.7 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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