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连夜实测DeepSeek V4 Pro 正式版,低于预期,不推荐接入Codex

WeChat: 夕小瑶科技说 LLMs & Foundation Models 2026-08-12
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TL;DR - A hands-on review finds DeepSeek V4 Pro inexpensive and operationally robust, but disappointing as a primary Codex model due to limited progress visibility, aggressive reuse of prior context, and weaker-than-expected frontend and writing performance.

  • A 41.39M-token API test achieved 100% request success, 52.3K tok/s aggregate throughput, and roughly 96% cache hits for ¥8.5.
  • Reasoning comprised 84.5% of output tokens, while sparse user-facing updates made long-running tasks difficult to monitor.
  • The model repeatedly reused artifacts and conclusions from earlier sessions, improving efficiency but raising concerns about stale or inappropriate context reuse.
  • Latency reached 4.9 seconds at p50 and 12.3 seconds at p99 under the reported workload; frontend generation and writing also trailed expectations.

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