SAMBANOVA MODEL TOKEN COUNTER

Meta-Llama-3.2-3B-Instruct Token Counter

Count tokens for Meta-Llama-3.2-3B-Instruct and estimate API cost before you send a request. SambaNova does not publish this tokenizer, so counts are calibrated estimates for planning. Your text never leaves the browser.

PROMPT

Paste text to count Meta-Llama-3.2-3B-Instruct 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 Meta-Llama-3.2-3B-Instruct preselected.

Meta-Llama-3.2-3B-Instruct at a glance

Provider. SambaNova

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

API pricing. $0.08 input / $0.16 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.

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Or browse the full model token counter directory and the LLM pricing comparison table to see how Meta-Llama-3.2-3B-Instruct prices against other providers.

FAQ

Meta-Llama-3.2-3B-Instruct token counter FAQ

How do I count tokens for Meta-Llama-3.2-3B-Instruct?

Paste your prompt into the counter on this page. SambaNova does not publish the Meta-Llama-3.2-3B-Instruct 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 Meta-Llama-3.2-3B-Instruct cost per token?

Meta-Llama-3.2-3B-Instruct costs $0.08 per 1 million input tokens and $0.16 per 1 million output tokens, based on the community-maintained LiteLLM pricing dataset checked 2026-07-01.

What is the context window of Meta-Llama-3.2-3B-Instruct?

Meta-Llama-3.2-3B-Instruct 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 Meta-Llama-3.2-3B-Instruct token count exact?

No. It is a clearly labeled estimate, because SambaNova has not released a public tokenizer for Meta-Llama-3.2-3B-Instruct. Estimates are usually within a reasonable range for English text but can drift for code, JSON, or non-English languages.