Will numbers and dates in Kimi K3 remain accurate?

Yes. Safe Vault locks all numbers, dates, currency values, and citations before compression takes place.

What is the typical savings on Kimi K3 document processing?

Teams processing RAG documents and legal texts see an average of 52% to 62% reduction in overall token bills.

Moonshot AI · Kimi K3 · Kimi 160k BPE

Kimi K3 token cost optimizer and calculator

Maximize ultra-long context window value by compressing source documents and pruning output fluff.

Input token price

$3.00/1M

Output token price

$15.00/1M (5x)

Tokenizer family

Kimi 160k BPE

Average combined savings

Up to 65%

Why Kimi K3 generates high API invoices

Kimi K3 excels at processing massive document collections and long contexts, but ingesting 200k+ token files at $3.00/1M input and $15.00/1M output quickly escalates costs. Raw document formatting and repetitive context eat up large portions of your budget.

Long-context document bloat

PDF scrapes, legal texts, and financial reports contain excessive whitespace, headers, and footers that burn thousands of billable tokens.

5x output generation rate

Output tokens cost $15.00/1M. Unconstrained summaries and verbose synthesis multiply expenses unnecessarily.

Kimi 160k BPE number splitting

Numeric sequences and table data in financial documents can split into sub-tokens under dense tokenization, increasing token volume.

Moonshot Kimi 160k BPE profile

Efficiency rating: Strong long-context handling with 160k vocabulary

Trained for long-horizon context retrieval with a 160,000 vocabulary size. Shows high efficiency on long-form context and documents.

How Curtly optimizes Kimi K3 workflows

Document structural deduplication

Removes redundant headers, footers, and structural noise from retrieved long context before forwarding to Kimi K3.

Concise summary injection

Constrains Kimi K3 output to direct, high-information findings, saving up to 45% on generation tokens.

Safe Vault data preservation

Guarantees that financial tables, dates, and citations remain exact and unaltered.

1-line drop-in integration (typescript)

import OpenAI from 'openai'; const client = new OpenAI({ apiKey: process.env.MOONSHOT_API_KEY, baseURL: 'https://proxy.curtly.dev/v1', defaultHeaders: { 'X-Curtly-Key': process.env.CURTLY_API_KEY }, }); const response = await client.chat.completions.create({ model: 'kimi-k3', messages: [{ role: 'user', content: 'Extract key clauses from 50-page agreement' }], });

Kimi K3 ROI simulator