Ryan-directed model swap (kanban t_f5f7e9ad, 2026-08-16). Changes: - Replace [Qwen3.6-35B-A3B-UD-Q4_K_S] with [Qwen3.8-27B-Q4_K_M] in llama-server-router-preset.ini.j2 (production model slot). - Qwen3.8-27B: dense 27B VLM, Apache-2.0, Alibaba Aug 2026. Unsloth Dynamic V3.0 GGUF quantization. Q4_K_M chosen: 17,106,775,008 bytes, 17.1GB. Measured VRAM: 17,068 MiB at ctx=32768 (q4_0 KV cache). - ctx-size set to 32768 (32K) via new variable llm_router_qwen38_ctx_size. Native context is 262K; 32K chosen to maintain eviction headroom on 24GB RTX 3090. - models-max reduced 4 -> 2 in host_vars. Qwen3.8 (17.6GB) + nomic-embed (558MB) exhaust the 24GB card; no auxiliary model can co-reside with Qwen3.8. LRU eviction handles model switching with ~30-60s cold-load latency. - llm_router_expected_model_id updated to Qwen3.8-27B-Q4_K_M. - Qwen3.6 GGUF retained at /opt/models/Qwen3.6-35B-A3B-UD-Q4_K_S.gguf (not deleted — pending stable period and explicit cleanup task). - day2_swap_qwen38.yml playbook added for Ansible idempotent redeployment. Architecture note: Qwen3.8 uses Gated DeltaNet; llama.cpp 6ea215d logs 'fused Gated Delta Net (chunked) not supported, set to disabled'. Inference works correctly on the non-fused fallback. A llama.cpp update may improve throughput on the GDN layers. Smoke test passed: model responded via router endpoint (http://10.1.71.130:8002). VRAM: 17,630 MiB (Qwen3.8) + 5,928 MiB (Llama-8B concurrent) = 23,558 MiB. Also commits accumulated but unpushed changes: - nomic-embed batch-size/rope-scaling fix (t_openviking_embed_batch) - per-model ctx-size day2 playbook (day2_per_model_ctx_size.yml) - llama-server-router.service.j2 minor update
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