Unverified50% confidenceCautionExact time
Because thinking tokens count toward max_tokens, a low max_tokens budget set for a non-thinking model will squeeze the answer space, causing responses to be too short or truncated; it is recommended to keep it ample (e.g., 32,000), and for long agent runs raise it to 256K or above per the model card's recommendation.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/19/2026
First Seen
Valid until: 1/17/2027
Sources
Related Entities
Related Claims
UnverifiedThe official recommendation is to appropriately relax the max tokens limit to leave room for both reasoning and responses, avoiding truncated output.72% similarUnverifiedSkill file size is under a hard budget measured in bytes: below 6KB, zero burnouts across eight runs; 6–9KB, about 25% empty responses; above 9KB, about 50%; one skill file that naturally ballooned to 9.2KB made the weak model return empty responses six times in a row.72% similarUnverifiedThe embedding model's maximum length means that inputs exceeding 512 tokens are silently truncated, so the example sets the chunk budget to 480 tokens.70% similarUnverifiedThe UP host estimates that inference speed could improve to 30–40 tokens/s after using a GPU with 50GB of VRAM (not confirmed through actual testing).70% similarUnverified智能体对内存要求较高，64GB 内存可秒出结果，32GB 或 16GB 首次对话会较慢需要预热过程70% similar
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