Llama 3.1 405B Instruct
vs
openai logo
GPT-4

Compare performance metrics, pricing, and capabilities of these AI models.

Key Differences
Context Length
Better
Llama 3.1 405B Instruct: 131K (advantage)
GPT-4: 8K (disadvantage)
Cost Efficiency
Lower Cost
Prompt: $3.50M vs $30.00M
Completion: $3.50M vs $60.00M

Capabilities

Llama 3.1 405B Instruct
Modality: text->text
Inputs: text
GPT-4
Modality: text->text
Inputs: text
M
Llama 3.1 405B Instruct
meta-llama/llama-3.1-405b-instruct

The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the f...

Context Length131K
Prompt Price$3.50M
ReleasedJuly 23, 2024
Supports:
text->text
O
GPT-4
openai/gpt-4

OpenAI's flagship model, GPT-4 is a large-scale multimodal language model capable of solving difficult problems with greater accuracy than previous mo...

Context Length8K
Prompt Price$30.00M
ReleasedMay 28, 2023
Supports:
text->text
Detailed Comparison
Feature
Llama 3.1 405B Instruct
openai logo
GPT-4
Context Length131K8K
Prompt Price$3.50M$30.00M
Completion Price$3.50M$60.00M
Modalitytext->texttext->text
Release DateJuly 23, 2024May 28, 2023
Analysis & Recommendations

Quick Summary

This comparison reveals key trade-offs between Llama 3.1 405B Instruct and GPT-4. Llama 3.1 405B Instruct offers a larger context window of 131K compared to GPT-4's 8K, though GPT-4 comes at a higher cost.

Llama 3.1 405B Instruct Strengths

  • Larger context window (131K) for processing longer documents
  • More cost-effective per token
  • Specialized for text tasks
  • Latest generation model

GPT-4 Strengths

  • Competitive context size (8K)
  • Premium pricing for high-quality output
  • Specialized for text tasks
  • Proven and stable model

When to Use Each Model

Choose Llama 3.1 405B Instruct when:
  • • You need the larger context window for complex tasks
  • • Cost efficiency is important in your use case
  • • Working with text-based tasks that benefit from deep analysis
Choose GPT-4 when:
  • • You need competitive context capability for long-form content
  • • Cost efficiency is not the primary concern for your budget
  • • Working with text-based tasks that require advanced processing
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