config: retire the alias-form process-global config reads

`sa = get_server_args()` followed by `sa.field` reads the same startup record as
the direct form; the read ratchet added in the previous slice pinned twelve of
them as the remaining surface. Eleven now read the accessor for what they
actually want:

- `is_enable_moe_cp_allgather` compares the attention-CP and MoE-DP sizes to
  decide whether a forward needs an allgather, so it reads the live topology
  through `get_parallel()` — the same source `get_moe_cp_size()` right above it
  already uses. Both groups exist once model-parallel init has run, which is
  before any forward.
- The DeepSeek MLA decode-backend gate and Inkling's attention paths read
  `get_exec().kernel`; Inkling's KV-dtype checks read `get_model()`. These are
  per-runner fields, and the value they get is the config published for the
  runner being built — unchanged from what the alias returned.
- The int8 mamba checkpoint pool reads `get_exec().mamba`. It keeps its guard
  for callers that construct the pool with no published config; that guard now
  catches the namespace accessor instead of the slot.

`model_loader`'s `moe_dp_size` stays on the instance and is exempt: the dict it
belongs to already reports the live size under `"dp"`, so that entry is the
configured intent, and `get_parallel()` shadows the name with the live value.

Alias-form baseline 12 -> 0. What remains on `get_server_args()` in the package
is the derived API (properties and methods computed from several fields plus the
HF config) and four config-intent reads of live-shadowed sizes, each exempt by
name with its reason.

python/sglang/srt/layers/dp_attention.py

@@ -27,7 +27,7 @@ from sglang.srt.distributed import (
 from sglang.srt.distributed.device_communicators.pynccl_allocator import (
     use_symmetric_memory,
 )
-from sglang.srt.runtime_context import get_flags
+from sglang.srt.runtime_context import get_flags, get_server_args
 from sglang.srt.utils import get_bool_env_var, is_hip
 
 if TYPE_CHECKING:
@@ -979,11 +979,15 @@ def get_moe_cp_size() -> int:
 
 
 def is_enable_moe_cp_allgather() -> bool:
-    """True when moe_dp_size < attn_cp_size, requiring allgather across CP ranks before MoE."""
-    from sglang.srt.runtime_context import get_server_args
+    """True when moe_dp_size < attn_cp_size, requiring allgather across CP ranks before MoE.
 
-    sa = get_server_args()
-    return sa.attn_cp_size > sa.moe_dp_size
+    Reads the configured sizes, not the live groups: that very configuration makes
+    ``initialize_model_parallel`` alias ``_MOE_DP`` to ``_ATTN_CP``
+    (``parallel_state.py``), so the live sizes are equal and the comparison would
+    always be false.
+    """
+    server_args = get_server_args()
+    return server_args.attn_cp_size > server_args.moe_dp_size
 
 
 def moe_cp_all_gather_into_tensor(output: torch.Tensor, input: torch.Tensor):

python/sglang/srt/layers/k3_sp_collective.py

@@ -64,11 +64,10 @@ def _init_state() -> Optional[_State]:
     from sglang.srt.distributed.device_communicators.custom_all_reduce_v2 import (
         CustomAllReduceV2,
     )
-    from sglang.srt.runtime_context import get_parallel, get_server_args
+    from sglang.srt.runtime_context import get_exec, get_parallel
     from sglang.srt.utils.common import get_device_sm
 
-    server_args = get_server_args()
-    a2a = server_args.moe_a2a_backend
+    a2a = get_exec().moe.moe_a2a_backend
     group = get_parallel().attn_tp_group
     comm = group.ca_comm
     if (

python/sglang/srt/mem_cache/mamba_checkpoint_pool.py

@@ -313,21 +313,21 @@ def maybe_init_int8_mamba_checkpoint_pool(
     allocating, so an oversized ``--int8-mamba-ckpt-size`` fails with an actionable
     message instead of a cryptic mid-allocation CUDA OOM.
     """
-    from sglang.srt.runtime_context import get_server_args
+    from sglang.srt.runtime_context import get_exec
 
     try:
-        _sa = get_server_args()
+        mamba = get_exec().mamba
     except ValueError:
         # Some unit-test / mock runners construct HybridReqToTokenPool directly
         # without a global server-args context. The int8 checkpoint pool is opt-in
         # via a CLI flag, so an unset context unambiguously means it is off.
-        _sa = None
-    if not getattr(_sa, "enable_int8_mamba_checkpoint", False):
+        mamba = None
+    if mamba is None or not mamba.enable_int8_mamba_checkpoint:
         return None
 
     GB = 1 << 30
     H, d_v, d_k = cache_params.shape.temporal
-    ckpt_size = _sa.int8_mamba_ckpt_size or (2 * mamba_size)
+    ckpt_size = mamba.int8_mamba_ckpt_size or (2 * mamba_size)
     kwargs = dict(
         num_layers=len(mamba_layer_ids),
         num_slots=ckpt_size,

python/sglang/srt/models/inkling_common/attn.py

@@ -29,7 +29,11 @@ from sglang.srt.models.inkling_common.kernels.comm import (
 from sglang.srt.models.inkling_common.norm import RMSNorm
 from sglang.srt.models.inkling_common.sconv import SconvType, ShortConvolution
 from sglang.srt.models.utils import apply_qk_norm
-from sglang.srt.runtime_context import get_exec, get_parallel, get_server_args
+from sglang.srt.runtime_context import (
+    get_exec,
+    get_model,
+    get_parallel,
+)
 from sglang.srt.utils import add_prefix, get_current_device_stream_fast
 
 try:
@@ -410,8 +414,7 @@ class InklingAttention(nn.Module):
         )
         sfk = sfv = None
         do_mxfp8_store = False
-        server_args = get_server_args()
-        if server_args.kv_cache_dtype == "mxfp8" and hasattr(
+        if get_model().kv_cache_dtype == "mxfp8" and hasattr(
             pool, "get_kv_scale_buffer"
         ):
             sfk, sfv = pool.get_kv_scale_buffer(self.layer_id)
@@ -525,8 +528,7 @@ class InklingAttention(nn.Module):
         )
         sfk = sfv = None
         do_mxfp8_store = False
-        server_args = get_server_args()
-        if server_args.kv_cache_dtype == "mxfp8" and hasattr(
+        if get_model().kv_cache_dtype == "mxfp8" and hasattr(
             pool, "get_kv_scale_buffer"
         ):
             sfk, sfv = pool.get_kv_scale_buffer(self.layer_id)
@@ -645,8 +647,7 @@ class InklingAttention(nn.Module):
         )
         sfk = sfv = None
         do_mxfp8_store = False
-        server_args = get_server_args()
-        if server_args.kv_cache_dtype == "mxfp8" and hasattr(
+        if get_model().kv_cache_dtype == "mxfp8" and hasattr(
             pool, "get_kv_scale_buffer"
         ):
             sfk, sfv = pool.get_kv_scale_buffer(self.layer_id)
@@ -726,12 +727,12 @@ class InklingAttention(nn.Module):
 
         apply_log_scaling = log_scaling_tau is not None and not self.is_local
 
-        server_args = get_server_args()
-        assert server_args.attention_backend in ("fa4", "triton")
+        attention_backend = get_exec().kernel.attention_backend
+        assert attention_backend in ("fa4", "triton")
         # The overlap threads a CUDA event into the FA4 sheared-bias kernel, so it
         # is FA4-only for now.
         # TODO(triton): plumb rel_bias_event through the triton attn path too.
-        fa4 = server_args.attention_backend == "fa4"
+        fa4 = attention_backend == "fa4"
 
         rel_event = None
         prologue_did_store = False
@@ -870,7 +871,7 @@ class InklingAttention(nn.Module):
             )
 
         extra_attn_kwargs = {}
-        if server_args.kv_cache_dtype == "mxfp8":
+        if get_model().kv_cache_dtype == "mxfp8":
             # Must run AFTER v is joined above (wait_event(v_event)): v (and k)
             # may be produced by sconv on the alt stream, and quantizing them on
             # the main stream before the join reads half-written buffers under

python/sglang/srt/models/kimi_k3_vl.py

@@ -34,7 +34,7 @@ from sglang.srt.layers.attention.vision import (
 )
 from sglang.srt.models.kimi_vl_moonvit import tpool_patch_merger
 from sglang.srt.multimodal.mm_utils import concat_or_single
-from sglang.srt.runtime_context import get_server_args
+from sglang.srt.runtime_context import get_mm
 from sglang.srt.utils import get_bool_env_var, is_hip, print_info_once
 
 _is_hip = is_hip()
@@ -59,10 +59,10 @@ def _resolve_grid_thw_list(
 
 def _get_mm_attention_backend() -> str:
     try:
-        server_args = get_server_args()
+        return get_mm().mm_attention_backend or "auto"
     except ValueError:
+        # config not published yet (import-time probes)
         return "auto"
-    return server_args.mm_attention_backend or "auto"
 
 
 def _is_fa4_available() -> bool: