FIREWORKS AI MODEL TOKEN COUNTER

mistral-7b-v0p2 Token Counter

Count tokens for mistral-7b-v0p2 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 mistral-7b-v0p2 tokens.

Tokens

0

Words

0

Characters

0

Input cost

$0.00

Output cost

$0.00

Total request

$0.00

32,768 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 mistral-7b-v0p2 preselected.

mistral-7b-v0p2 at a glance

Provider. Fireworks AI

Context window. 32,768 tokens (about 25,000 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

mistral-7b-v0p2 token counter FAQ

How do I count tokens for mistral-7b-v0p2?

Paste your prompt into the counter on this page. Fireworks AI does not publish the mistral-7b-v0p2 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 mistral-7b-v0p2 cost per token?

mistral-7b-v0p2 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 mistral-7b-v0p2?

mistral-7b-v0p2 has a context window of 32,768 tokens, which is roughly 25,000 English words of combined prompt and response. The counter above shows how much of that window your text consumes.

Is this mistral-7b-v0p2 token count exact?

No. It is a clearly labeled estimate, because Fireworks AI has not released a public tokenizer for mistral-7b-v0p2. Estimates are usually within a reasonable range for English text but can drift for code, JSON, or non-English languages.