Understand and compare
Claude 3 Haiku
vs.
GPT-4 Turbo
Overview
Claude 3 Haiku was released
4 months after
GPT-4 Turbo.
Claude 3 Haiku
|
GPT-4 Turbo
|
|
|---|---|---|
|
Provider
The entity that provides this model.
|
Anthropic
|
OpenAI
|
|
Input Context Window
The number of tokens supported by the input context window.
|
200K
tokens
|
128K
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.
|
2024-03-13
|
2023-11-06
|
Pricing
Claude 3 Haiku is
roughly 40x cheaper compared
to GPT-4 Turbo for input tokens and
roughly 24x cheaper
for output tokens.
|
Claude 3 Haiku
|
GPT-4 Turbo
|
|
|---|---|---|
|
Input
Cost of input data provided to the model.
|
$0.25
per million tokens
|
$10.00
per million tokens
|
|
Output
Cost of output tokens generated by the model.
|
$1.25
per million tokens
|
$30.00
per million tokens
|
Benchmarks
Compare relevant benchmarks between Claude 3 Haiku
and GPT-4 Turbo.
|
Claude 3 Haiku
|
GPT-4 Turbo
|
|
|---|---|---|
|
MMLU
Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
|
76.7
(5-shot CoT)
|
Benchmark not available.
|
|
MMMU
A wide ranging multi-discipline and multimodal benchmark.
|
50.2
|
Benchmark not available.
|
|
HellaSwag
A challenging sentence completion benchmark.
|
85.9
(10-shot)
|
Benchmark not available.
|
Claude 3 Haiku, developed by Anthropic, features a context window of 200,000 tokens. The model costs 0.025 cents per thousand tokens for input and 0.125 cents per thousand tokens for output. It was released on March 13, 2024. In benchmarks, it achieved a score of 50.2 in MMMU, 85.9 in HellaSwag in a 10-shot scenario, and 76.7 in MMLU in a 5-shot CoT scenario.
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.
Llama 2 Chat 13B
Mistral 8x7B Instruct
Measure & Improve LLM
Product Performance.
Get Started
© 2023-2024 Context