FIREWORKS AI MODEL TOKEN COUNTER

nvidia-nemotron-nano-9b-v2 Token Counter

Count tokens for nvidia-nemotron-nano-9b-v2 and estimate API cost before you send a request. Fireworks AI does not publish this tokenizer, so counts are calibrated estimates for planning. Your text never leaves the browser.

PROMPT

Paste text to count nvidia-nemotron-nano-9b-v2 tokens.

Tokens

0

Words

0

Characters

0

Input cost

$0.00

Output cost

$0.00

Total request

$0.00

131,072 token context window 0%

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nvidia-nemotron-nano-9b-v2 at a glance

Provider. Fireworks AI

Context window. 131,072 tokens (about 98,000 English words).

API pricing. $0.20 input / $0.20 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.

FAQ

nvidia-nemotron-nano-9b-v2 token counter FAQ

How do I count tokens for nvidia-nemotron-nano-9b-v2?

Paste your prompt into the counter on this page. Fireworks AI does not publish the nvidia-nemotron-nano-9b-v2 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 nvidia-nemotron-nano-9b-v2 cost per token?

nvidia-nemotron-nano-9b-v2 costs $0.20 per 1 million input tokens and $0.20 per 1 million output tokens, based on the community-maintained LiteLLM pricing dataset checked 2026-07-01.

What is the context window of nvidia-nemotron-nano-9b-v2?

nvidia-nemotron-nano-9b-v2 has a context window of 131,072 tokens, which is roughly 98,000 English words of combined prompt and response. The counter above shows how much of that window your text consumes.

Is this nvidia-nemotron-nano-9b-v2 token count exact?

No. It is a clearly labeled estimate, because Fireworks AI has not released a public tokenizer for nvidia-nemotron-nano-9b-v2. Estimates are usually within a reasonable range for English text but can drift for code, JSON, or non-English languages.