Block a user
GC — pipeline / expert parallelism (contingency: 2-slot-bridge NVL only)
G7 — quantized weight load + fleet validation
G6 — batched decode engine + latent-cache snapshot wiring
G5 — tensor parallelism for MLA + DSA (TP=4/8 on H200)
G4 — decoder assembly + glm_moe_dsa config + registration
G3 — noaux_tc MoE block (sigmoid + correction bias)
G2 — DSA sparse-attention indexer (masked-dense → sparse kernel)
G1 — MLA attention + latent KV cache (single-GPU)
[epic] GLM 5.2 support: MLA + DSA (glm_moe_dsa) bring-up on neuron
27B derived context limit reports 128k — investigate which ceiling binds and whether 256k is reachable
Resolved the "which term binds" question and, along the way, root-caused an advertised context = 0 regression observed after the beast reboot. With the #127 observability line live, a healthy…
fix(neuron): context-limit observability + qwen3_next profile (#126)
fix(neuron): context-limit observability + qwen3_next profile (#126)
27B derived context limit reports 128k — investigate which ceiling binds and whether 256k is reachable
F4d — perf(neuron): continuous batching for agentic fan-out
F4d — perf(neuron): continuous batching for agentic fan-out
Bench gate: PASS. Measured live on beast (2× RTX 5090, TP-2, max_in_flight = 8), O5 concurrency scenario, batched build vs the fc95faa serialized baseline:
Qwen/Qwen3-Coder-Next (A3B…