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- A new study found that DeepSeek V4’s context window of 1M tokens is no longer sufficient for production environments, as it leads to precision degradation and response latency issues.
- The research conducted on three different codebases showed mixed results: tasks under 150k tokens performed well, but beyond this threshold precision degrades significantly. For example, exact line number references become vague or inaccurate at higher token counts.
- Response times also increased dramatically with larger context windows, making the model less suitable for interactive workflows where quick responses are critical. The time to first answer stretched up to 120 seconds in max reasoning mode.
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Originally published at reddit.com. Curated by AI Maestro.
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