This content originally appeared on DEV Community and was authored by Dr. Furqan Ullah
Main Models
GPT-4.1 — 128,000 tokens
GPT-5 mini — 128,000 tokens
GPT-5 — 128,000 tokens
GPT-4o — 128,000 tokens
o3-mini — 200,000 tokens
Claude Sonnet 3.5 — 90,000 tokens
Claude Sonnet 3.7 — 200,000 tokens
Claude Sonnet 4 — 128,000 tokens
Claude Sonnet 4.5 — 200,000 tokens (standard) / 1,000,000 tokens (beta)
Gemini 2.0 Flash — 1,000,000 tokens
Gemini 2.5 Pro — 128,000 tokens
o4-mini — 128,000 (picker) / 200,000 (full version)
Grok Code Fast 1 — 128,000 tokens
Smaller Models
GPT-3.5 Turbo — 16,384 tokens
GPT-4 — 32,768 tokens
GPT-4 Turbo — 128,000 tokens
GPT-4o mini — 128,000 tokens
💡 How big is that, really?
Let’s take Claude Sonnet 4.5 with a 200,000-token context window.
If one C++ or JavaScript file has ~2,000 lines and each line averages ≈ 15 tokens (including code, spaces, and comments), → one file ≈ 30,000 tokens.
That means Claude Sonnet 4.5 can process around 6 full files of 2,000 lines each at once. If you’re using the 1,000,000-token extended version, that jumps to ~33 files.
🧠 Conclusion
So next time your AI assistant suddenly “forgets” what was said earlier or mixes details halfway through your project, remember — it’s not confused… it’s simply “lost in the middle.”
Once that context window fills up, older information fades away to make room for new input.
👉 Now you know why the “lost in the middle” problem happens — because even AI can only remember so much at once.
This content originally appeared on DEV Community and was authored by Dr. Furqan Ullah
Dr. Furqan Ullah | Sciencx (2025-11-13T03:14:55+00:00) GitHub Copilot Model Context Sizes (Nov 2025). Retrieved from https://www.scien.cx/2025/11/13/github-copilot-model-context-sizes-nov-2025/
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