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Discover how Anthropic's Claude 2 and Meta's Llama 2 Chat 70B stack up against each other in this comprehensive comparison of two leading AI language models.

Released in July 2023 and July 2023 respectively, these models represent significant advancements in artificial intelligence, with Claude 2 offering a 100,000-token context window and Llama 2 Chat 70B featuring a 4,096-token capacity. Their distinct approaches to natural language processing are reflected in their benchmark performances, with Claude 2 achieving 78.5% on MMLU and Llama 2 Chat 70B scoring 68.9%, making this comparison essential for developers and organizations seeking the right AI solution for their specific needs.

Models Overview

Anthropic Claude 2
Anthropic Llama 2 Chat 70B

Provider

Company that developed the model
Anthropic Meta

Context Length

Maximum number of tokens the model can process
100K undefined

Maximum Output

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

Release Date

Date when the model was released
11-07-2023 18-07-2023

Knowledge Cutoff

Training data cutoff date
Early 2023 September 2022

Open Source

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

API Providers

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

Pricing Comparison

Compare the pricing of Anthropic's Claude 2 and Meta's Llama 2 Chat 70B to determine the most cost-effective solution for your AI needs.

Anthropic Claude 2
Anthropic Llama 2 Chat 70B

Input Cost

Cost per million input tokens
$8 / 1M tokens Pricing not available

Output Cost

Cost per million tokens generated
$24 / 1M tokens Pricing not available

Comparing Benchmarks and Performance

Compare the performances of Anthropic's Claude 2 and Meta's Llama 2 Chat 70B on industry benchmarks. This section provides a detailed comparison on MMLU, MMMU, HumanEval, MATH and other key benchmarks.

Anthropic Claude 2
Anthropic Llama 2 Chat 70B

MMLU

Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
78.5% 68.9%

MMMU

A wide ranging multi-discipline and multimodal benchmark.
Benchmark not available 30.1%

HellaSwag

A challenging sentence completion benchmark.
Benchmark not available 85.3%

GSM8K

Grade-school math problems benchmark.
Benchmark not available 56.8%

HumanEval

A benchmark to measure functional correctness for synthesizing programs from docstrings.
Benchmark not available 29.9%

MATH

Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
Benchmark not available Benchmark not available

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