万字长文拆解DeepSeek V4 Pro与Harness：从后训练到「代理自进化」，更大的变化在开源框架里
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TL;DR - A hands-on analysis of DeepSeek V4 Pro and its open-source Harness argues that agent performance depends as much on post-training, model routing, context handling, and orchestration as on the base model. The Harness matters because it exposes the infrastructure used for official evaluations and enables longer-running, cost-aware agent workflows.
- V4 Pro’s strongest gains are in agentic coding benchmarks and end-to-end task completion; the article infers, but cannot confirm, that improved post-training drove much of the progress.
- Its advertised 1M-token context uses YaRN scaling from 64K, yet the authors retrieved all 10 facts planted across a 923,858-token test, including around the 902K position.
- DeepSeek’s Anthropic-compatible API can silently route
claude-sonnet,claude-haiku, and some older Claude model names to the smaller Flash model, so explicit model-variable overrides are needed for reliable Pro evaluation. - The open-source Harness emphasizes stable cache prefixes, strict control of tool-output size, and reproducible minimal-agent settings; Pro has relatively high token prices but low measured per-task cost due to efficient task completion and heavy cache reuse.
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万字长文拆解DeepSeek V4 Pro与Harness：从后训练到「代理自进化」，更大的变化在开源框架里
TL;DR - A hands-on analysis of DeepSeek V4 Pro and its open-source Harness argues that agent performance depends as much on post-training, model routing, context handling, and orchestration as on the base model. The Harness matters because it exposes the infrastructure used for official evaluations and enables longer-running, cost-aware agent workflows.
- V4 Pro’s strongest gains are in agentic coding benchmarks and end-to-end task completion; the article infers, but cannot confirm, that improved post-training drove much of the progress.
- Its advertised 1M-token context uses YaRN scaling from 64K, yet the authors retrieved all 10 facts planted across a 923,858-token test, including around the 902K position.
- DeepSeek’s Anthropic-compatible API can silently route
claude-sonnet,claude-haiku, and some older Claude model names to the smaller Flash model, so explicit model-variable overrides are needed for reliable Pro evaluation. - The open-source Harness emphasizes stable cache prefixes, strict control of tool-output size, and reproducible minimal-agent settings; Pro has relatively high token prices but low measured per-task cost due to efficient task completion and heavy cache reuse.