feat(loader): native-BF16 dense loader for no-metadata Holo/Ornith checkpoints

[rsafier]

What

Adds a native-BF16 load path for no-metadata dense Qwen3.5-family checkpoints (Hcompany Holo-3.1-0.8B/4B/9B, Ornith dense). These ship plain BF16 .weight tensors with no quantization metadata, so today the loader hardwires them through the runtime BF16→NVFP4 requant path (Nvfp4Variant::Bf16Raw) — an uncalibrated, lossy quantization that degrades small-model quality (the BF16-source models exist precisely because no calibrated NVFP4/FP8 release does).

This keeps FFN, attention (Q/K/V/O), and the SSM in_proj_qkvz/out_proj in native BF16, dispatching the dense_gemv_bf16/dense_gemm_bf16 kernels already in the standard bundle (same path Gemma-4 dense uses). Loader-only; no new kernels.

• qwen35_dense.rs: BF16 arms for FFN (snapshot overlay), attention (BF16 dense q/k/v + set_o_dense_bf16), SSM (BF16 in_proj_qkvz + out_proj_dense), all gated on Bf16Raw. NVFP4 weights are still built + kept as the spec-decode/batched fallback (a null NVFP4 weight under w4a16 dispatch is the CUDA-700-at-concurrency footgun).
• ssm_batched.rs: extend the qkvz_ok gate so the pure-BF16 build engages the batched dense_gemm decode path instead of the per-seq loop.

Use-after-free fix (would-be CUDA-700)

The naive FFN overlay installs gate/up/down via dense_auto(), which returns the WeightStore cached BF16 pointer un-copied. But load_dense_ffn's Bf16Raw arm runtime-quantizes to NVFP4 first and gpu.free()s that same buffer (quantized_any, nvfp4_detect.rs), and the store never evicts — so the overlay would hand set_bf16_weights freed memory → dense_gemm_tc illegal access on the first prefill. Fixed by snapshotting fresh D2D copies before load_dense_ffn frees the originals.

Recommended serve flag

Pair with --lm-head-dtype bf16 to keep the 248K-vocab LM head lossless too (else it defaults to runtime-NVFP4).

Validation

Built + served Holo-3.1-4B on GB10 from this branch (cherry-picked onto current main, post-#229):

• Compiles clean; loads (dense weight loader: 32 layers, LM head kept as BF16).
• Coherent on short and 1.8K-token multi-chunk prefill; zero CUDA-700.
• Coexists with perf(qwen3.6-27b): NVFP4 W4A4 MMQ FFN + FlashInfer-GDN + Marconi tail checkpoints — cold prefill 1.24-1.75x over llama.cpp, warm multi-turn TTFT beats llama like-for-like #229 MMQ-finalize and perf(qwen3.6-27b): attn transposed NVFP4 copies in qwen35_dense loader (~1.3x prefill) #223 transposed-NVFP4 prefill (both variant-gated off on the BF16 path).
• Agentic multi-turn (3-task): 2/3, on par with the runtime-NVFP4-head baseline (the convert task is a flaky exact-value reasoning check; not a loader signal).

Notes

• Does not need an ATLAS_TARGET_QUANT=bf16 build (that strips the w4a16 stubs the dense loader still constructs) — use the standard bundle.
• Full Holo serving config (e.g. --target-kv-tokens) lives in the separate Holo-GB10 stack; this PR is just the loader capability, which main already routes via the qwen35_dense dispatch.

---

Related PRs — independent, all target main

Now that #229 is merged, these three each cherry-pick cleanly onto current main with zero conflicts and are independent (no stacking) — review/merge in any order:

• feat(loader): native-BF16 dense loader for no-metadata Holo/Ornith checkpoints #250 — native-BF16 dense loader (no-metadata Holo/Ornith dense)
• test(bench): --no-thinking / --thinking-budget toggles for bench_isl_osl #251 — bench_isl_osl thinking toggles
• fix(loader): native-FP8 SSM shadowed on modelopt-mixed-precision 35B #252 — native-FP8-SSM shadowing fix (modelopt 35B)

Follow-ups (not yet opened): Tier-2 FlashInfer-prefill + decode-concurrency reconciliation vs #229 FI (needs a merge, not a clean pick); and closing older stacked PRs folded into #229 (e.g. #220 FlashInfer-GDN AOT) after a rebase-diff confirms no outstanding delta.