Compare Gemini Ultra vs. Llama 2 Chat 70B

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Overview

	Gemini Ultra	Llama 2 Chat 70B
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	4,096 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 18th, 2023 over 1 year ago 2023-07-18
Knowledge Cutoff Limit on the knowledge base used by the model.	Unknown	September 2022 September 2022
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 2 Chat 70B
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 2 Chat 70B.

	Gemini Ultra	Llama 2 Chat 70B
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	83.7 (5-shot) Source	68.9 Source
MMMU A wide ranging multi-discipline and multimodal benchmark.	59.4 (0-shot pass@1) Source	30.1 Source
HellaSwag A challenging sentence completion benchmark.	Benchmark not available.	85.3 (0-shot) Source
GSM8K Grade-school math problems benchmark.	88.9 (11-shot) Source	56.8 (8-shot) Source
HumanEval A benchmark to measure functional correctness for synthesizing programs from docstrings.	74.4 (0-shot) Source	29.9 (0-shot) Source
MATH Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.	53.2 (4-shot Minerva Prompt) Source	Benchmark not available.

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 2 Chat 70B, developed by Meta, features a context window of 4096 tokens. The model was released on July 18, 2023, and has achieved a score of 30.1 in the MMMU benchmark and 68.9 in the MMLU benchmark.

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