Model Stopped Naturally Not Context Limit | Generated by AI
Good question — the context length (1M tokens) and the finish reason: stop are two different things.
Here’s what happened in your run:
1. Context length isn’t the limiter here
Your request used about 11,500 tokens total (9007 prompt + 2511 completion), which is tiny compared to the 1M limit. So it wasn’t cut short because of context exhaustion.
2. Why “finish reason: stop” appears
This flag just means the model reached a natural stopping point — it finished generating based on your prompt and didn’t hit any hard constraints. Other possible finish reasons include:
length: model stopped because it hit the max tokens setting.content_filter: stopped due to policy filter.tool_end/function_call: when tool invocation ends output.
Since you got stop, it means the model simply completed its thought and ended normally.
3. Why the output might feel shorter
Even with a huge context window, the actual completion length depends on:
- Max tokens parameter you (or the API defaults) set — if set to 3000, it won’t generate beyond that.
- Prompt design — if the instruction leads the model to produce a concise answer, it may stop earlier.
- Sampling dynamics — models decide when to stop when they predict an EOS (end-of-sequence) token.
4. The cost line you saw
The 0.0647 cost is just billing for 11.5K tokens. That’s correct and not tied to why it stopped.
👉 So in short: It stopped because the model believed it had finished its response — not because it hit the 1M context ceiling.
Do you want me to show you how to force longer generations with Claude Sonnet (e.g., by setting max_output_tokens, adjusting stop sequences, or prompt tricks)?