fix(deepseek-v4): use vanilla RMSNorm weight semantics

[SeedSource]

Summary

DeepSeek-V4 ships vanilla RMSNorm weights (out = x * w / rms), including values far from 1. Atlas was applying the offset-from-1 storage convention to them: the loader pre-subtracted 1.0 and stored bf16(w - 1), so the offset-from-1 rms_norm kernel (out = x * (1 + w) / rms) would recover 1 + (w - 1) = w.

That round-trip is exact only when w is near 1. V4's norm weights are ≈ 0.03, so it stored ≈ −0.97, and BF16's rounding error there becomes a large relative error on the weight once 1 is added back — catastrophic cancellation. For weights that straddle zero it is worse than degradation: bf16(w - 1) rounds to exactly -1.0, so 1 + (-1.0) collapses the weight to zero, destroying sign and magnitude together.

This PR loads V4's norm weights exactly and dispatches the vanilla RMSNorm kernel — kernels/gb10/common/rms_norm_vanilla.cu, which already exists in-tree and is already used by the DFlash drafter for exactly this reason. V4 was simply wired to the wrong kernel.

Important

This is a correctness fix. It is NOT a resolution of the remaining DeepSeek-V4 parity gap.
On our frozen 8-question eval the score moved 12/40 → 15/40, but loop degeneration remained in 8/8 questions and every answer still finished on length rather than a clean stop. The dominant failure mode is unchanged and still under investigation. Please do not read this PR as "V4 is fixed."

Measured — all 249 norm tensors in the checkpoint

norm class	tensors	weight range	rel. err (mean / max)	sign flips	after this PR
attn_norm	46	0.0084 … 2.50	3.44 % / 16.4 %	0	0
q_norm	46	0.0098 … 0.240	3.52 % / 19.3 %	0	0
kv_norm	46	−0.0332 … 2.00	4.94 % / 100 %	23	0
ffn_norm	46	0.0259 … 0.797	0.49 % / 5.66 %	0	0
compressor.norm	62	−0.226 … 3.83	55.9 % / 100 %	423	0
final_norm	1	−0.0114 … 0.555	0.34 % / 31.6 %	0	0

The fix is exactly lossless: the checkpoint is already BF16, so bf16(w) == w and the new error is 0.00e+00 on every tensor.

Why this went unnoticed

The offset round-trip is bit-exact when w ≳ 0.63 — measured on-device, zero error across the near-one (0.63–0.99) and large (1.0–3.83) regimes. That describes every other model family Atlas serves, all of which store genuine offsets (initialised to 0) or weights near 1. DeepSeek-V4 is the first checkpoint whose norm weights sit near zero. A unit test pins this property in both directions so it cannot regress.

Scope

• Explicit model predicate — ships_vanilla_norm_weights(config) := config.model_type == "deepseek_v4". Not inferred from weight statistics.
• Every V4 checkpoint norm weight loads exactly (dense_auto); every launch consuming one dispatches rms_norm_vanilla — attn_norm, ffn_norm, q_norm, kv_norm, compressor.norm, the final norm, and the MTP norms.
• The unweighted q_b_norm normalize is deliberately left on the offset kernel. It is driven by a zero-filled weight buffer (1 + 0 = 1), so pointing it at the vanilla kernel would multiply the Q path by zero. Only the norms that consume a checkpoint weight are switched.
• V4 without the mHC highway now fails at load. Those fused residual_add_rms_norm / rms_norm_residual paths are offset-only, have no vanilla twin in-tree, and would silently apply x * (1 + w) to an exactly-loaded weight. Better to refuse than to serve wrong numbers.
• dense_minus_one is removed — V4 was its only caller. The offset loader existed solely for this model.
• No MoE, routing, attention, or other model family is touched. Models that genuinely store offsets (Qwen3-Next, init 0) keep dense + the offset kernel and are bit-exact unchanged.

Tests

Unit (norm_convention_tests, runs in CI — no GPU needed):

• only deepseek_v4 takes the vanilla path; qwen3_next / qwen3_5_moe / deepseek_v3 / llama / … all keep offset-from-1
• the offset round-trip is bit-exact for weights ≥ 0.63 (the regression guarantee for every other family)
• it is > 1 % wrong on real attn_norm values, ~20 % wrong at q_norm's tail
• it collapses a small negative compressor weight to exactly zero

Device (crates/spark-model/examples/rmsnorm_vanilla_microtest.rs) — the production kernels against an F64 host formula:

• 120 cells (6 weight regimes × 4 hidden dims × 5 seeds), 0 failures
• the offset path is bit-exact unchanged for non-V4 weights
• the unweighted q_b_norm normalize is bit-exact unchanged
• old vs new on V4's own distributions: old = 16.9 % / 20.1 % / 100 % max rel. error on q_norm / attn_norm / straddle-zero; new = 0 on all three

CI gates run locally, all green: cargo fmt --all --check, cargo clippy --workspace --tests, cargo test --workspace (0 failures).

Validation

Served EP=2 on 2× DGX Spark (GB10, SM121), native-MXFP4 DeepSeek-V4-Flash, dual-rail RoCE. Baseline and fixed images were built from the same Dockerfile and launcher, differing only in this change, with the spark binary sha256 verified inside the running container on both nodes.

🤖 Generated with Claude Code

https://claude.ai/code/session_015RxQjRmdoT6qfWofRnmqfw