REPLICATE MODEL TOKEN COUNTER

llama-2-7b Token Counter

Count tokens for llama-2-7b and estimate API cost before you send a request. Replicate does not publish this tokenizer, so counts are calibrated estimates for planning. Your text never leaves the browser.

PROMPT

Paste text to count llama-2-7b tokens.

Expected output

Tokens

Words

Characters

Input cost

$0.00

Output cost

$0.00

Total request

$0.00

4,096 token context window 0%

Need optimization suggestions, a token heatmap, monthly cost projection, or a side-by-side model comparison? Open the full analyzer with llama-2-7b preselected.

llama-2-7b at a glance

Provider. Replicate

Context window. 4,096 tokens (about 3,000 English words).

API pricing. $0.05 input / $0.25 output per 1M tokens.

Tokenizer. Not public; counts on this page are calibrated estimates.

Pricing source. The community-maintained LiteLLM pricing dataset, refreshed 2026-07-01. Community-tracked rates can lag provider changes; confirm with the provider before budgeting.

Other Replicate model token counters

llama-2-13b llama-2-13b-chat llama-2-70b llama-2-7b-chat llama-3-70b llama-3-8b mistral-7b-instruct-v0.2 mistral-7b-v0.1

Or browse the full model token counter directory and the LLM pricing comparison table to see how llama-2-7b prices against other providers.

FAQ

llama-2-7b token counter FAQ

How do I count tokens for llama-2-7b?

Paste your prompt into the counter on this page. Replicate does not publish the llama-2-7b tokenizer, so the count is a calibrated estimate based on text length, language, and structure. Treat it as planning guidance rather than an exact billing number.

How much does llama-2-7b cost per token?

llama-2-7b costs $0.05 per 1 million input tokens and $0.25 per 1 million output tokens, based on the community-maintained LiteLLM pricing dataset checked 2026-07-01.

What is the context window of llama-2-7b?

llama-2-7b has a context window of 4,096 tokens, which is roughly 3,000 English words of combined prompt and response. The counter above shows how much of that window your text consumes.

Is this llama-2-7b token count exact?

No. It is a clearly labeled estimate, because Replicate has not released a public tokenizer for llama-2-7b. Estimates are usually within a reasonable range for English text but can drift for code, JSON, or non-English languages.