Tokens · Context
Context window calculator and planning guide
Context windows are often marketed in millions of tokens, but engineering success depends on what you actually send each call.
Token calculation explanation
Your effective context is the minimum of model window, latency budget, and price tolerance—not the brochure number.
Words-to-token examples
Large documents quickly reach tens of thousands of tokens—measure with tokenizer tools before promising “full PDF” features.
Prompt optimization tips
Chunk documents, summarize sections, and attach only high-signal excerpts.
Token reduction techniques
Hierarchy: title summary → section summary → raw excerpt only if needed.
Context window explanation
When prompts near limits, consider splitting tasks or using secondary models for pre-compression.
Real pricing examples
Large prompts multiply input spend linearly—doubling retrieved chunks doubles input cost for that call.
Context-heavy scenarios
| Scenario | Prompt tokens | Output tokens | Model (est.) | Cost / request |
|---|---|---|---|---|
| Medium RAG bundle | 12000 | 400 | GPT-4o | $0.0340 |
| Long policy review | 48000 | 900 | Claude 3.5 Sonnet | $0.1575 |
| Flash summarizer | 6000 | 350 | gemini-2.5-flash | $0.0006 |
Figures use rates from config/models.php; confirm against your provider before billing decisions.
FAQ: Context windows
Short answers mirror the structured data on this page for search engines and readers.
- Does a bigger window always help quality?
- Not if noise drowns signal—curation often beats brute force.
- What if we exceed the window?
- Expect errors or truncation—handle gracefully in code.
- Are long contexts slower?
- Often yes—latency can indirectly increase user churn and retries.
- How does chunk overlap affect cost?
- Overlap duplicates tokens—minimize while preserving coherence.