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Discover how Open AI's GPT-4o Mini and Meta's Llama 3 70B Instruct stack up against each other in this comprehensive comparison of two leading AI language models.

Released in July 2024 and April 2024 respectively, these models represent significant advancements in artificial intelligence, with GPT-4o Mini offering a 128,000-token context window and Llama 3 70B Instruct featuring a 8,000-token capacity. Their distinct approaches to natural language processing are reflected in their benchmark performances, with GPT-4o Mini achieving 82% on MMLU and Llama 3 70B Instruct scoring 82%, making this comparison essential for developers and organizations seeking the right AI solution for their specific needs.

Models Overview

Open AI GPT-4o Mini
Open AI Llama 3 70B Instruct

Provider

Company that developed the model
Open AI Meta

Context Length

Maximum number of tokens the model can process
128K undefined

Maximum Output

Maximum number of tokens the model can generate in a single response
16400 2048

Release Date

Date when the model was released
18-07-2024 18-04-2024

Knowledge Cutoff

Training data cutoff date
October 2023 December 2023

Open Source

Whether the model's code is open-source
FALSE TRUE

API Providers

API providers that offer access to the model
OpenAI API Azure AI, AWS Bedrock, Vertex AI, NVIDIA NIM, IBM watsonx, Hugging Face

Pricing Comparison

Compare the pricing of Open AI's GPT-4o Mini and Meta's Llama 3 70B Instruct to determine the most cost-effective solution for your AI needs.

Open AI GPT-4o Mini
Open AI Llama 3 70B Instruct

Input Cost

Cost per million input tokens
$0.15 / 1M tokens Pricing not available

Output Cost

Cost per million tokens generated
$0.6 / 1M tokens Pricing not available

Comparing Benchmarks and Performance

Compare the performances of Open AI's GPT-4o Mini and Meta's Llama 3 70B Instruct on industry benchmarks. This section provides a detailed comparison on MMLU, MMMU, HumanEval, MATH and other key benchmarks.

Open AI GPT-4o Mini
Open AI Llama 3 70B Instruct

MMLU

Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
82% 82%

MMMU

A wide ranging multi-discipline and multimodal benchmark.
59.4% Benchmark not available

HellaSwag

A challenging sentence completion benchmark.
Benchmark not available Benchmark not available

GSM8K

Grade-school math problems benchmark.
Benchmark not available 93%

HumanEval

A benchmark to measure functional correctness for synthesizing programs from docstrings.
87.2% 81.7%

MATH

Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
70.2% 50.4%

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