Llama 3.1 405B (base)vs
GPT-4
Llama 3.1 405B (base)
vsCompare performance metrics, pricing, and capabilities of these AI models.
Key Differences
Context Length
Better
Llama 3.1 405B (base): 33K (advantage)
GPT-4: 8K (disadvantage)
Cost Efficiency
Lower Cost
Prompt: $4.00M vs $30.00M
Completion: $4.00M vs $60.00M
Capabilities
Llama 3.1 405B (base)
Modality: text->text
Inputs: text
GPT-4
Modality: text->text
Inputs: text
M
Llama 3.1 405B (base)
meta-llama/llama-3.1-405b
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This is the base 405B pre-trained version. It has demonstrated st...
Context Length33K
Prompt Price$4.00M
ReleasedAugust 2, 2024
Supports:
text->textO
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->textDetailed Comparison
| Feature | Llama 3.1 405B (base) | |
|---|---|---|
| Context Length | 33K | 8K |
| Prompt Price | $4.00M | $30.00M |
| Completion Price | $4.00M | $60.00M |
| Modality | text->text | text->text |
| Release Date | August 2, 2024 | May 28, 2023 |
Analysis & Recommendations
Quick Summary
This comparison reveals key trade-offs between Llama 3.1 405B (base) and GPT-4. Llama 3.1 405B (base) offers a larger context window of 33K compared to GPT-4's 8K, though GPT-4 comes at a higher cost.
Llama 3.1 405B (base) Strengths
- •Larger context window (33K) 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 (base) 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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