Compare GPT-4 Turbo vs. Claude 3 Sonnet

Pricing About Us Blog Docs

Book a demo Get Started

Compare

Understand and compare GPT-4 Turbo vs. Claude 3 Sonnet

Generate side-by-side samples for these models in the Context.ai playground

Overview

GPT-4 Turbo was released 4 months before Claude 3 Sonnet.

	GPT-4 Turbo	Claude 3 Sonnet
Provider The entity that provides this model.	OpenAI	Anthropic
Input Context Window The number of tokens supported by the input context window.	128K tokens	200K tokens
Maximum Output Tokens The number of tokens that can be generated by the model in a single request.	4,096 tokens	4,096 tokens
Release Date When the model was first released.	November 6th, 2023 6 months ago 2023-11-06	March 4th, 2024 2 months ago 2024-03-04

Pricing

GPT-4 Turbo is roughly 3.3x more expensive compared to Claude 3 Sonnet for input tokens and roughly 2.0x more expensive for output tokens.

	GPT-4 Turbo	Claude 3 Sonnet
Input Cost of input data provided to the model.	$10.00 per million tokens	$3.00 per million tokens
Output Cost of output tokens generated by the model.	$30.00 per million tokens	$15.00 per million tokens

Benchmarks

Compare relevant benchmarks between GPT-4 Turbo and Claude 3 Sonnet.

	GPT-4 Turbo	Claude 3 Sonnet
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	Benchmark not available.	81.5 (5-shot CoT) Source
MMMU A wide ranging multi-discipline and multimodal benchmark.	Benchmark not available.	53.1 Source
HellaSwag A challenging sentence completion benchmark.	Benchmark not available.	89.0 (10-shot) Source

GPT-4 Turbo, developed by OpenAI, features a large context window of 128,000 tokens. The model costs 1.0 cent per thousand tokens for input and 3.0 cents per thousand tokens for output. It is set to be released on November 6, 2023.

Claude 3 Sonnet, developed by Anthropic, features a context window of 200,000 tokens. The model costs 0.3 cents per thousand tokens for input and 1.5 cents per thousand tokens for output. It was released on March 4, 2024, and has achieved benchmark scores of 53.1 in MMMU, 89.0 in HellaSwag (10-shot), and 81.5 in MMLU (5-shot CoT).

Compare more models