Compare Gemini 1.5 Pro vs. Llama 3.1 70B Instruct

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Overview

Gemini 1.5 Pro was released 5 months before Llama 3.1 70B Instruct.

	Gemini 1.5 Pro	Llama 3.1 70B Instruct
Provider The entity that provides this model.	Google	Meta
Input Context Window The number of tokens supported by the input context window.	1M tokens	128K tokens
Maximum Output Tokens The number of tokens that can be generated by the model in a single request.	8,192 tokens	2,048 tokens
Release Date When the model was first released.	February 15th, 2024 9 months ago 2024-02-15	July 23rd, 2024 4 months ago 2024-07-23
Knowledge Cutoff Limit on the knowledge base used by the model.	November 2023 November 2023	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 1.5 Pro	Llama 3.1 70B Instruct
Input Cost of input data provided to the model.	$7.00 per million tokens	Pricing not available.
Output Cost of output tokens generated by the model.	$21.00 per million tokens	Pricing not available.

Benchmarks

Compare relevant benchmarks between Gemini 1.5 Pro and Llama 3.1 70B Instruct.

	Gemini 1.5 Pro	Llama 3.1 70B Instruct
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	81.9 (5-shot) Source	83.6 (5-shot) Source
MMMU A wide ranging multi-discipline and multimodal benchmark.	58.5 (0-shot) Source	Benchmark not available.
HellaSwag A challenging sentence completion benchmark.	93.3 (10-shot) Source	Benchmark not available.
GSM8K Grade-school math problems benchmark.	90.8 (11-shot) Source	95.1 (8-shot) Source
HumanEval A benchmark to measure functional correctness for synthesizing programs from docstrings.	84.1 (0-shot) Source	Benchmark not available.
MATH Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.	67.7 (4-shot Minerva Prompt) Source	68.0 (0-shot) Source

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