Context Window
32,768
Tokens
Model Cost Profile
Meta: Llama 3.1 405B (base)
Developer: meta-llama
Pricing updated Mar 11, 2026
Input rank: #315Output rank: #251
Meta: Llama 3.1 405B (base) offers a substantial context window of 32,768 tokens, making it suitable for applications requiring extensive text understanding, such as document summarization and conversational AI. With a competitive pricing structure of $4.00 per million tokens for both input and output, teams can effectively manage costs while scaling their usage based on project needs. This model is ideal for organizations looking to integrate advanced natural language processing capabilities into their workflows without incurring prohibitive expenses.
Input Price / 1M
$4.00
Prompt tokens
Output Price / 1M
$4.00
Completion tokens
Intelligence (MMLU)
Benchmark Pending
Massive Multitask Language Understanding
Side-by-Side Pricing Table
| Usage Type | Price / 1M Tokens |
|---|---|
| Input (Prompt) | $4.00 |
| Output (Completion) | $4.00 |
Price History
Meta: Llama 3.1 405B (base) Pricing Trend
Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 — Mar 11
Current Input / 1M
$4.00
Current Output / 1M
$4.00
Cost Calculator
Estimate monthly spend for Meta: Llama 3.1 405B (base) based on your workload.
01.0B
0500M
Estimated Monthly Cost
$148
25M input + 12M output tokens
Cheaper Alternatives to Compare
Quick links for cost-down decisions before production rollout.
FAQ
Common pricing and benchmark questions for Meta: Llama 3.1 405B (base).
How much does Meta: Llama 3.1 405B (base) cost per 1M input tokens?
Meta: Llama 3.1 405B (base) input pricing is $4.00 per 1M tokens based on the latest synced provider data.
How much does Meta: Llama 3.1 405B (base) cost per 1M output tokens?
Meta: Llama 3.1 405B (base) output pricing is $4.00 per 1M tokens based on the latest synced provider data.
What context window does Meta: Llama 3.1 405B (base) support?
Meta: Llama 3.1 405B (base) supports a context window of 32,768 tokens.
How can I compare Meta: Llama 3.1 405B (base) with cheaper alternatives?
Use the comparison links on this page to open direct model-vs-model pricing and benchmark pages, then evaluate monthly spend projections for your workload.