5-Hour Local Coding Agent Session on Qwen3.8-27B: 97 tok/s Streaming, 70% Context Compaction
illgettheownerforyou · reddit · 2026-08-18
The author ran a real 5.32-hour multi-slice project development session with Qwen3.8-27B loaded locally via the NInfer inference engine plus the official DeepSeek Harness (Code Mode), on an RTX PRO 6000 Blackwell (95.59 GiB VRAM), Ryzen 9 9950X3D, and WSL2. The longest single autonomous turn ran 1.06 hours and completed normally.
Key numbers:
- Weighted streamed output 96.8 tok/s (median 104.4 per call); full-stack effective rate including queueing/HTTP/harness handling was 42.6 tok/s. A second shorter session hit 99.8 tok/s streamed, so results are repeatable.
- Totals: 144 model calls, 299,219 output tokens, 19.32M cumulative prompt tokens, 138 top-level tool calls, 336 nested Code Mode dispatches.
The standout result is automatic context compaction: DSH compacted twice within the same long turn — 201,785 → 83,285 tokens (58.7% reduction) and 208,730 → 64,159 (69.3% reduction), each taking 149 seconds, after which the agent retained implementation state and kept working. The author calls it the first local setup where genuinely long agent sessions feel practical instead of collapsing under their own context.
Note: since the unsloth NVFP4 safetensors couldn't load in NInfer at setup time, measurements used NInfer's internally built Qwen3.8-27B quantized artifact.
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