M
MoneyMath

Context Window — Will It Fit?

Will your novel fit in Claude? Can Gemini swallow the whole annual report? Quick visual check of which LLM context window your input actually fits inside.

🟢 Updated April 2026👤 Reviewed by MoneyMath Editorial⚡ Runs in your browser · no data sent
Estimated tokens
33,250
≈ 3.8 chars per token (English)
Show the formula
tokens ≈ characters / 3.8 (English average)
tokens ≈ words × 1.33
pages × 500 words/page × 1.33 = tokens

Model-by-model fit check

ModelContextFits?% usedTokens left
GPT-4o128,000✅ Yes26.0%94,750
GPT-4 Turbo128,000✅ Yes26.0%94,750
Claude Sonnet 4 (1M)1,000,000✅ Yes3.3%966,750
Claude Opus 4 (200k)200,000✅ Yes16.6%166,750
Gemini 2.5 Pro (2M)2,000,000✅ Yes1.7%1,966,750
Gemini 2.5 Flash (1M)1,000,000✅ Yes3.3%966,750
GPT-3.5 Turbo16,000❌ No207.8%0

What the context window actually limits

The context window is the total number of tokens the model can attend to in a single request — your system prompt, user message, uploaded files, AND the model's response all share this budget. A "200k context" doesn't mean you can dump 200k tokens of input and still get a long reply.

Practical budgeting

  • Reserve 10–25% of the window for output tokens.
  • Long outputs (2,000+ tokens) can actually exceed some models' per-response cap even when context allows.
  • Quality degrades past ~50% of the window on most models — "lost in the middle" problem.
  • You pay per input token. A 2M-context call isn't free just because the model accepts it.

Frequently Asked Questions

Why does quality drop in long contexts?

Research ("Lost in the Middle", 2023) shows LLMs attend most strongly to the beginning and end of context, with accuracy dropping in the middle. At 80%+ of a model's window, retrieval accuracy on middle content can fall 30–50%. For critical lookups, summarize or chunk rather than dumping everything.

What fits in 128k tokens?

Roughly 300 pages of a novel, a 250-page PDF, a 90-minute podcast transcript, or a mid-size codebase (~20k lines of well-commented code). Claude Opus' 200k gets you ~500 pages, and Gemini Pro's 2M handles an entire book series.

Does my system prompt count against the context?

Yes. System prompts, user messages, previous turns in a conversation, and tool-call results ALL consume context tokens. Long chat histories silently eat your budget — trim aggressively or summarize.

What about Claude's 1M beta?

Claude Sonnet 4's 1M context is available via API with specific pricing tiers (input above 200k costs 2x). Opus 4 is capped at 200k. Pricing and availability may have changed — check Anthropic's current docs before relying on it.