What context window do LLaMA 3.1 models support?

All LLaMA 3.1 and 3.2 models support a 128,000-token context window, equivalent to roughly 100,000 words or about 200 pages of text.

How does LLaMA tokenization work?

LLaMA 3 uses the tiktoken tokenizer (similar to GPT-4) with a vocabulary of 128,256 tokens. This tool approximates counts using ~1.25 tokens per word as a heuristic.

Are LLaMA models free to use?

LLaMA models are open-source and free to self-host, but third-party API providers charge for inference. Costs vary by provider. This tool uses typical market rates as estimates.

Is my text sent to any server?

No. Token counting happens entirely in your browser. No text is sent to any server.

LLaMA Token Counter

Count tokens for LLaMA 3.1 405B, 70B, 8B, and LLaMA 3.2 models.

Model

Text input

Tokens0

Words0

Characters0

Context window usage

00.0% of 128.0K

Cost estimate

Per request$0.000000

Per 1K requests$0.000000

Daily (100 req)$0.000000

Monthly est.$0.000000

0 input tokens0 output tokens

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FAQ

What context window do LLaMA 3.1 models support?: All LLaMA 3.1 and 3.2 models support a 128,000-token context window, equivalent to roughly 100,000 words or about 200 pages of text.
How does LLaMA tokenization work?: LLaMA 3 uses the tiktoken tokenizer (similar to GPT-4) with a vocabulary of 128,256 tokens. This tool approximates counts using ~1.25 tokens per word as a heuristic.
Are LLaMA models free to use?: LLaMA models are open-source and free to self-host, but third-party API providers charge for inference. Costs vary by provider. This tool uses typical market rates as estimates.
Is my text sent to any server?: No. Token counting happens entirely in your browser. No text is sent to any server.

Count tokens for Meta LLaMA models including LLaMA 3.1 405B, 70B, 8B, and LLaMA 3.2 3B. See the 128K context window usage and per-request cost estimate. Uses word-based heuristics — results are approximate.