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Discover how Meta's Llama 2 Chat 13B and Anthropic's Claude 3.5 Sonnet stack up against each other in this comprehensive comparison of two leading AI language models.

Released in July 2023 and June 2024 respectively, these models represent significant advancements in artificial intelligence, with Llama 2 Chat 13B offering a 4,096-token context window and Claude 3.5 Sonnet featuring a 200,000-token capacity. Their distinct approaches to natural language processing are reflected in their benchmark performances, with Llama 2 Chat 13B achieving 54.8% on MMLU and Claude 3.5 Sonnet scoring 90.4%, making this comparison essential for developers and organizations seeking the right AI solution for their specific needs.

Models Overview

Meta Llama 2 Chat 13B
Meta Claude 3.5 Sonnet

Provider

Company that developed the model
Meta Anthropic

Context Length

Maximum number of tokens the model can process
undefined 200K

Maximum Output

Maximum number of tokens the model can generate in a single response
2048 4096

Release Date

Date when the model was released
18-07-2023 20-06-2024

Knowledge Cutoff

Training data cutoff date
September 2022 April 2024

Open Source

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

API Providers

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

Pricing Comparison

Compare the pricing of Meta's Llama 2 Chat 13B and Anthropic's Claude 3.5 Sonnet to determine the most cost-effective solution for your AI needs.

Meta Llama 2 Chat 13B
Meta Claude 3.5 Sonnet

Input Cost

Cost per million input tokens
Pricing not available $3 / 1M tokens

Output Cost

Cost per million tokens generated
Pricing not available $15 / 1M tokens

Comparing Benchmarks and Performance

Compare the performances of Meta's Llama 2 Chat 13B and Anthropic's Claude 3.5 Sonnet on industry benchmarks. This section provides a detailed comparison on MMLU, MMMU, HumanEval, MATH and other key benchmarks.

Meta Llama 2 Chat 13B
Meta Claude 3.5 Sonnet

MMLU

Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.
54.8% 90.4%

MMMU

A wide ranging multi-discipline and multimodal benchmark.
Benchmark not available 70.4%

HellaSwag

A challenging sentence completion benchmark.
80.7% Benchmark not available

GSM8K

Grade-school math problems benchmark.
28.7% 96.4%

HumanEval

A benchmark to measure functional correctness for synthesizing programs from docstrings.
18.3% 93.7%

MATH

Benchmark performance on Math problems ranging across 5 levels of difficulty and 7 sub-disciplines.
Benchmark not available 78.3%

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