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+# Attention Backend Selection Matrix Draft
+
+This Markdown file is for rough iteration and is not linked from the Sphinx
+toctree. It explores a decision-table presentation for PyTorch
+`DotProductAttention` backend support.
+
+Source target: `get_attention_backend()` and `nvte_get_fused_attn_backend()` on
+GitHub `main` commit `815bf369`, audited on 2026-06-04.
+
+## What Changed in This Iteration
+
+This iteration applies the layout recommendation from
+`attention_backend_selection_layout_experiment.md`:
+
+1. The main routing table uses configuration axes as columns.
+2. Backend families appear as candidate values in one cell.
+3. Each row points to the resolver tables that still need to be applied.
+4. Backend-family columns are reserved for smaller resolver tables where
+   side-by-side comparison is useful.
+
+The goal is to make the matrix read like a route:
+
+`hardware -> precision -> execution -> layout/pattern -> candidates -> resolver`
+
+## How to Read This Draft
+
+The routing table answers: which backend families are still plausible after
+matching the largest configuration axes?
+
+Candidate backends are not final selections. A candidate means the routing row
+has not ruled out that backend family. After matching a row:
+
+1. Apply global overrides.
+2. Apply the row's follow-up resolver tables.
+3. Apply cross-cutting modifiers for bias, dropout, softmax, determinism, head
+   geometry, `num_splits`, and `return_max_logit`.
+4. Apply final backend priority.
+
+Final priority still matters:
+
+- On Hopper and newer GPUs, if FlashAttention and FusedAttention both survive,
+  TE prefers FusedAttention.
+- Otherwise, TE prefers FlashAttention, then FusedAttention, then unfused.
+- `NVTE_FLASH_ATTN=0`, `NVTE_FUSED_ATTN=0`, and `NVTE_UNFUSED_ATTN=0` remove
+  those backend families before the rest of the checks.
+
+Backend names used below:
+
+| Name | Meaning |
+| --- | --- |
+| FA2 | FlashAttention 2 |
+| FA3 | FlashAttention 3 |
+| FA4 | FlashAttention 4 |
+| Fused F16 | cuDNN FusedAttention `NVTE_F16_arbitrary_seqlen` for FP16/BF16 |
+| Fused FP8 | cuDNN FusedAttention `NVTE_FP8` for FP8 DPA |
+| Unfused | `UnfusedDotProductAttention` |
+
+Resolver tables:
+
+| Resolver | Use it when |
+| --- | --- |
+| [FlashAttention support resolver](#flashattention-support-resolver) | A routing row leaves FA2, FA3, or FA4 as candidates. |
+| [Fused F16 cuDNN support resolver](#fused-f16-cudnn-support-resolver) | A routing row leaves Fused F16 as a candidate. |
+| [Fused FP8 cuDNN support resolver](#fused-fp8-cudnn-support-resolver) | A routing row leaves Fused FP8 as a candidate. |
+| [Cross-cutting modifier tables](#cross-cutting-modifier-tables) | Bias, ALiBi, dropout, non-vanilla softmax, determinism, head-geometry, `num_splits`, or `return_max_logit` modifiers are present. |
+
+## Global Overrides
+
+Apply these before using a routing row.
+
+| Override / modifier | Effect |
+| --- | --- |
+| `NVTE_FLASH_ATTN=0` | Removes FA2, FA3, and FA4 candidates. |
+| `NVTE_FUSED_ATTN=0` | Removes Fused F16 and Fused FP8 candidates. |
+| `NVTE_UNFUSED_ATTN=0` | Removes the Unfused candidate. |
+| Missing FlashAttention package | Removes the matching FA candidate; FA2 also needs a supported version range. |
+| `attn_mask_type="arbitrary"` | Removes FA2, FA3, FA4, Fused F16, and Fused FP8; Unfused remains for non-FP8. |
+| FP32 QKV | Removes FA2, FA3, FA4, Fused F16, and Fused FP8; Unfused remains. |
+| `return_max_logit=True` | Removes FlashAttention and Fused FP8; Fused F16 and Unfused remain only if other gates pass. |
+| `num_splits != 1` | Removes FA2, Fused F16, Fused FP8, and Unfused; FA3 remains, and FA4 remains only for SplitKV on `sm100+`. |
+| KV cache plus context parallelism | Removes every backend family. |
+| FP8 on `sm120` | Removes FlashAttention and Fused FP8; only FP8 emulation or ONNX-export Unfused paths can remain. |
+
+## Main Routing Table
+
+Rows are intentionally broad. The `Candidate backends` cell says what survives
+this routing row before resolver tables and modifiers are applied.
+
+| Hardware | Precision / recipe | Execution | Layout / pattern | Head geometry | Candidate backends | Excluded here | Follow-up |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| `sm < 80` | FP16/BF16 or FP32 | No CP, no KV cache | Any supported non-FP8 path | Any | Unfused | FA2, FA3, FA4, Fused F16, Fused FP8 | Modifiers |
+| `sm < 80` | Any | Context parallelism | Any | Any | None | All backend families | CP requires accelerated backends that are not available on `sm < 80` |
+| `sm < 80` | FP8 DPA | Any | Any | Any | Unfused only for FP8 emulation or ONNX export | FA2, FA3, FA4, Fused F16, Fused FP8 | FP8 recipe notes |
+| `sm80` / `sm89` | FP16/BF16 | No CP, no KV cache | BSHD/SBHD self-attention with `no_mask`, `padding`, `causal`, or `padding_causal`; no bias | MHA/GQA/MQA, dimensions normally multiple of 8 | FA2; FA4 if installed; Fused F16; Unfused | FA3; Fused FP8 | Flash resolver; Fused F16 resolver; modifiers |
+| `sm80` / `sm89` | FP16/BF16 | No CP, no KV cache | THD padding-style masks without padding between packed sequences | MHA/GQA/MQA | FA2; FA4 if installed; Fused F16; Unfused | FA3; Fused FP8 | Flash THD row; Fused F16 THD rows; modifiers |
+| `sm80` / `sm89` | FP16/BF16 | No CP, no KV cache | THD with padding between packed sequences | MHA/GQA/MQA | Fused F16 if cuDNN accepts THD; Unfused unless KV cache is present | FA2; FA3; FA4; Fused FP8 | Fused F16 THD rows; modifiers |
+| `sm80` / `sm89` | FP16/BF16 | No CP, no KV cache | Top-left causal cross-attention with unequal Q/KV sequence lengths | Any supported non-MLA or MLA shape | Fused F16; Unfused | FA2; FA3; FA4; Fused FP8 | Fused F16 mask rows; modifiers |
+| `sm80` / `sm89` | FP16/BF16 | No CP, no KV cache | Bottom-right causal cross-attention or sliding window attention | Any supported non-MLA or MLA shape | FA2; FA4 if installed; Fused F16; Unfused | FA3; Fused FP8 | Flash mask/SWA rows; Fused F16 mask/SWA rows; modifiers |
+| `sm80` / `sm89` | FP16/BF16 | Context parallelism | BSHD/SBHD, no bias, no bottom-right causal mask, not causal cross-attention | MHA/GQA/MQA | FA2; Fused F16 | FA3; FA4; Fused FP8; Unfused | Flash CP row; Fused F16 CP gates; modifiers |
+| `sm80` / `sm89` | FP16/BF16 | Context parallelism | THD with `cp_comm_type="all_gather"` or `"a2a+p2p"` | MHA/GQA/MQA | FA2 | FA3; FA4; Fused F16 on `815bf369`; Fused FP8; Unfused | Flash CP row; THD CP notes |
+| `sm80` / `sm89` | FP16/BF16 | KV cache | Paged or non-paged decode path | MHA/GQA/MQA | FA2; Fused F16 on `sm80`; Unfused | FA3; FA4; Fused F16 on `sm89`; Fused FP8 | Flash KV row; Fused F16 KV rows; modifiers |
+| `sm80` / `sm89` | FP8 DPA | Any | Any | Any | Unfused only for FP8 emulation or ONNX export | FA2, FA3, FA4, Fused F16, Fused FP8 | FP8 recipe notes |
+| `sm90` | FP16/BF16 | No CP, no KV cache | BSHD/SBHD self-attention with `no_mask`, `padding`, `causal`, or `padding_causal`; no bias | MHA/GQA/MQA, dimensions normally multiple of 8 | FA2; FA3 if installed; FA4 if installed and FA3 absent; Fused F16; Unfused | Fused FP8 | Flash resolver; Fused F16 resolver; Hopper priority |
+| `sm90` | FP16/BF16 | No CP, no KV cache | THD padding-style masks without padding between packed sequences | MHA/GQA/MQA | FA2; FA3 if installed; FA4 if installed and FA3 absent; Fused F16; Unfused | Fused FP8 | Flash THD row; Fused F16 THD rows; Hopper priority |
+| `sm90` | FP16/BF16 | No CP, no KV cache | THD with padding between packed sequences | MHA/GQA/MQA | FA3 if installed; Fused F16 if cuDNN accepts THD; Unfused unless KV cache is present | FA2; FA4; Fused FP8 | Flash THD row; Fused F16 THD rows |
+| `sm90` | FP16/BF16 | No CP, no KV cache | Top-left causal cross-attention with unequal Q/KV sequence lengths | Any supported non-MLA or MLA shape | Fused F16; Unfused | FA2; FA3; FA4; Fused FP8 | Fused F16 mask rows; modifiers |
+| `sm90` | FP16/BF16 | No CP, no KV cache | Bottom-right causal cross-attention or sliding window attention | Any supported non-MLA or MLA shape | FA2; FA3 if installed; FA4 if installed and FA3 absent; Fused F16; Unfused | Fused FP8 | Flash mask/SWA rows; Fused F16 mask/SWA rows; Hopper priority |
+| `sm90` | FP16/BF16 | No CP, no KV cache | MLA with unequal QK/V dimensions | Separate Q/K/V layout for Fused F16; selected MLA shapes for FA3/FA4 | FA3 if installed; FA4 if installed and FA3 absent; Fused F16; Unfused | FA2; Fused FP8 unless FP8 recipe is active | Flash head-dim rows; Fused F16 head/layout rows |
+| `sm90` | FP16/BF16 | Context parallelism | BSHD/SBHD, no bias, no bottom-right causal mask, not causal cross-attention | MHA/GQA/MQA | FA2; FA3 if installed; Fused F16 | FA4; Fused FP8; Unfused | Flash CP row; Fused F16 CP gates; modifiers |
+| `sm90` | FP16/BF16 | Context parallelism | THD with `cp_comm_type="all_gather"` or `"a2a+p2p"` | MHA/GQA/MQA | FA2; FA3 if installed | FA4; Fused F16 on `815bf369`; Fused FP8; Unfused | Flash CP row; THD CP notes |
+| `sm90` | FP16/BF16 | KV cache | Paged or non-paged decode path | MHA/GQA/MQA | FA2; FA3 if installed; Fused F16; Unfused | FA4; Fused FP8 for FP8 KV cache | Flash KV row; Fused F16 KV rows; modifiers |
+| `sm90` | FP8 delayed scaling | No CP, no KV cache | BSHD/SBHD, no bias, allowed mask | Dimensions accepted by cuDNN FP8 branch, commonly `head_dim_qk=head_dim_v=128` | Fused FP8; Unfused only for FP8 emulation or ONNX export | FA2; FA4; Fused F16; FA3 for training | Fused FP8 resolver |
+| `sm90` | FP8 delayed scaling | Context parallelism | Non-THD, no bias | Dimensions accepted by cuDNN FP8 branch | Fused FP8 if CP and cuDNN gates pass | FA2; FA3; FA4; Fused F16; Unfused | Fused FP8 CP row |
+| `sm90` | FP8 current scaling or MXFP8 | Any | Any | Any | Unfused only for FP8 emulation or ONNX export | FA2, FA3, FA4, Fused F16, Fused FP8 | Current scaling and MXFP8 require `sm100+` |
+| `sm100+` except `sm120` | FP16/BF16 | No CP, no KV cache | BSHD/SBHD or THD, common self-attention masks, no bias | MHA/GQA/MQA | FA2 with Blackwell version gate; FA4 if installed; Fused F16; Unfused | FA3; Fused FP8 | Flash resolver; Fused F16 resolver; Hopper+ priority |
+| `sm100+` except `sm120` | FP16/BF16 | No CP, no KV cache | Top-left causal cross-attention with unequal Q/KV sequence lengths | Any supported non-MLA or MLA shape | Fused F16; Unfused | FA2; FA3; FA4; Fused FP8 | Fused F16 mask rows; modifiers |
+| `sm100+` except `sm120` | FP16/BF16 | No CP, no KV cache | Bottom-right causal cross-attention or sliding window attention | Any supported non-MLA or MLA shape | FA2; FA4 if installed; Fused F16; Unfused | FA3; Fused FP8 | Flash mask/SWA rows; Fused F16 mask/SWA rows; Hopper+ priority |
+| `sm100+` except `sm120` | FP16/BF16 | No CP, no KV cache | MLA | Selected FA4 shapes or separate Q/K/V layout for Fused F16 | FA4 if installed; Fused F16; Unfused | FA2; FA3; Fused FP8 unless FP8 recipe is active | Flash head-dim rows; Fused F16 head/layout rows |
+| `sm100+` except `sm120` | FP16/BF16 | Context parallelism | No bottom-right causal mask, not causal cross-attention, no unsupported bias | MHA/GQA/MQA | FA2; Fused F16 | FA3; FA4; Fused FP8; Unfused | Flash CP row; Fused F16 CP gates |
+| `sm100+` except `sm120` | FP16/BF16 | KV cache | Paged or non-paged decode path | MHA/GQA/MQA | FA2; Fused F16; Unfused | FA3; FA4; Fused FP8 for FP8 KV cache | Flash KV row; Fused F16 KV rows |
+| `sm100+` except `sm120` | FP8 delayed scaling | No CP, no KV cache | Non-THD unless cuDNN FP8 gates say otherwise, no bias | Dimensions accepted by cuDNN FP8 branch | Fused FP8; Unfused only for FP8 emulation or ONNX export | FA2; FA3; FA4; Fused F16 | Fused FP8 resolver |
+| `sm100+` except `sm120` | FP8 current scaling | No CP, no KV cache | BSHD/SBHD/BHSD, no bias, allowed mask | Dimensions accepted by cuDNN FP8 current-scaling branch | Fused FP8; Unfused only for FP8 emulation or ONNX export | FA2; FA3; FA4; Fused F16 | Fused FP8 current-scaling row |
+| `sm100+` except `sm120` | MXFP8 | No CP, no KV cache | Non-THD, no bias | Dimensions accepted by cuDNN FP8 branch | Fused FP8; Unfused only for FP8 emulation or ONNX export | FA2; FA3; FA4; Fused F16 | Fused FP8 MXFP8 row |
+| `sm100+` except `sm120` | FP8 block scaling or NVFP4 | Any | Any | Any | Unfused only for FP8 emulation or ONNX export | FA2, FA3, FA4, Fused F16, Fused FP8 | FP8 recipe notes |
+| `sm120` | FP16/BF16 | No CP, no KV cache | Common non-FP8 attention paths | MHA/GQA/MQA and supported dimensions | FA2; FA4 if installed; Fused F16; Unfused | FA3; Fused FP8 | Flash resolver; Fused F16 `sm120` row; modifiers |
+| `sm120` | FP16/BF16 | KV cache | Decode path | MHA/GQA/MQA | Unfused | FA2; FA3; FA4; Fused F16; Fused FP8 | KV-cache notes; modifiers |
+| `sm120` | FP16/BF16 | Context parallelism | No bottom-right causal mask, not causal cross-attention | MHA/GQA/MQA | FA2; Fused F16 if CP and `sm120` gates pass | FA3; FA4; Fused FP8; Unfused | Flash CP row; Fused F16 CP and `sm120` rows |
+| `sm120` | FP8 DPA | Any | Any | Any | Unfused only for FP8 emulation or ONNX export | FA2, FA3, FA4, Fused F16, Fused FP8 | FP8 on `sm120` is disabled in Python selector |
+
+## Backend Resolver Tables
+
+<a id="flashattention-support-resolver"></a>
+
+### FlashAttention Support Resolver
+
+Use this table after a routing row leaves FA2, FA3, or FA4 as a candidate.
+Backend columns are useful here because readers often compare Flash variants
+directly.
+
+| Gate | FA2 | FA3 | FA4 |
+| --- | --- | --- | --- |
+| Installation and architecture | Requires supported `flash-attn` 2 and `sm80+`; Blackwell requires `flash-attn >= 2.7.3`. | Requires FA3 installed and `sm90`. | Requires FA4 installed and `sm80+`; on `sm90`, TE disables FA4 when FA3 is installed. |
+| Dtype | FP16/BF16. FP8 DPA is disabled. | FP16/BF16; selected FP8 inference paths exist, but FP8 training and FP8 CP are disabled. | FP16/BF16. FP8 DPA is disabled. |
+| THD with padding between packed sequences | No. | Yes. | No. |
+| KV cache | Supported with FA2 gates: paged requires `flash-attn >= 2.5` and page size multiple of 256; non-paged requires effective `max_seqlen_kv` divisible by 256. Disabled on `sm120`. | Supported; FP8 KV cache only for THD Q format. | Disabled for KV cache. |
+| Context parallelism | Candidate only for non-FP8, no bottom-right causal mask, no causal cross-attention, limited bias, and no THD bias. | Same family restrictions as FA2. | Disabled for context parallelism. |
+| Masks | `arbitrary` disables FA2. Top-left causal cross-attention with unequal sequence lengths disables FA2. Bottom-right causal masks are supported. | Same mask-family restrictions as FA2. | Same mask-family restrictions as FA2, plus FA4-specific validator/workaround gates. |
+| Bias and ALiBi | No explicit bias except ALiBi. ALiBi requires `flash-attn >= 2.4` and bottom-right alignment for cross-attention. | ALiBi and explicit bias are disabled. | ALiBi and explicit bias are disabled. |
+| Dropout | Supported. | Nonzero dropout disables FA3. | Nonzero dropout disables FA4. |
+| Head dimensions | Requires `head_dim_qk == head_dim_v`, divisible by 8, `<= 256`; `> 192` is restricted to selected architectures. MLA is disabled. | Requires `head_dim_qk <= 256`, `num_heads % num_gqa_groups == 0`, and selected MLA shapes. | Defers first-pass validation to FA4. TE also disables selected SM100 `head_dim=256` cross-attention and selected SM100 training MLA shapes. |
+| Determinism | Requires `flash-attn >= 2.4.1`. | Deterministic training with `max(head_dim_qk, head_dim_v) >= 256` is disabled. | Candidate if FA4 accepts the shape. |
+
+<a id="fused-f16-cudnn-support-resolver"></a>
+
+### Fused F16 cuDNN Support Resolver
+
+Use this table after a routing row leaves Fused F16 as a candidate. All
+applicable rows must pass for cuDNN to return `NVTE_F16_arbitrary_seqlen`.
+The rows below are scoped gates: match the input branch, apply the minimum
+cuDNN version and constraints, then continue to the next gate. This narrows a
+Fused F16 candidate instead of only listing what each cuDNN version introduced.
+
+#### F16 Always-On Gates
+
+| Axis | Requirement before version rows matter |
+| --- | --- |
+| Dtype | Q and KV dtype must be FP16 or BF16. |
+| Head dimensions | `head_dim_qk` and `head_dim_v` must be multiples of 8. Dimensions `<= 128` are the base case; wider dimensions need version rows below. |
+| Base layouts | BSHD, SBHD, and BHSD are base candidates. THD, split Q/KV groups, and paged KV need version rows below. |
+| Ragged offsets | THD cases that require 64-bit ragged offsets need cuDNN 9.5+. |
+| Bad cuDNN versions | cuDNN `< 8.9.0`, 9.10.0, and 9.10.1 return no F16 fused backend. |
+| Python pre-filters | `pre_scale_bias`, unsupported CP combinations, `num_splits != 1`, and FP32 QKV are removed before the cuDNN call. |
+
+#### F16 Platform Gate
+
+| Input branch | Minimum cuDNN | Narrowed scope if gate passes | Reject if |
+| --- | --- | --- | --- |
+| `sm < 80` | N/A | None | F16 fused requires `sm80+`. |
+| `sm80` or `sm90` | 8.9.0 | Continue to sequence, head, layout/mask, and modifier gates. | cuDNN `< 8.9.0` or known-bad 9.10.0/9.10.1. |
+| `sm89` or other `80 <= sm < 100` | 8.9.3 | Continue to sequence, head, layout/mask, and modifier gates. | cuDNN `< 8.9.3` or known-bad 9.10.0/9.10.1. |
+| `sm100+` except `sm120` | 9.7.0 | Continue to Blackwell-specific shape and determinism gates. | cuDNN `< 9.7.0` or known-bad 9.10.0/9.10.1. |
+| `sm120` | 9.18.1 | Continue only if non-deterministic training or inference and layout is not `t3hd`/`th3d`. | cuDNN `< 9.18.1`, deterministic training, or `t3hd`/`th3d`. |
+
+#### F16 Sequence and Head Gate
+
+| Input branch | Minimum cuDNN | Narrowed scope if gate passes | Reject if |
+| --- | --- | --- | --- |
+| General sequence lengths before cuDNN 9.0 | 8.9.0 | `max_seqlen_q` and `max_seqlen_kv` are both divisible by 64. | cuDNN `< 9.0.0` and either max sequence length is not divisible by 64. |
+| General sequence lengths on cuDNN 9.0+ | 9.0.0 | General divisibility gate is removed. | Bottom-right mask-specific rows below may still require divisibility before 9.7. |
+| MHA, `num_heads == num_gqa_groups` | 8.9.0 | Continue to layout/mask and head-dimension gates. | Other gates fail. |
+| GQA/MQA, `num_heads != num_gqa_groups` | 8.9.7 | Continue to layout/mask and head-dimension gates. | cuDNN `< 8.9.7`. |
+| Head dims multiple of 8 and both `<= 128` | 8.9.0 | Base head-dimension scope passes. | Either dimension is not a multiple of 8. |
+| Hopper fprop, head dims `<= 256` | 9.1.0 | Wider-dimension Hopper inference/fprop passes. | Training path with cuDNN `< 9.5.0`. |
+| Hopper bprop, head dims `<= 256` | 9.5.0 | Wider-dimension Hopper training passes unless MLA exclusion applies. | cuDNN `< 9.5.0`. |
+| Blackwell fprop, wider dims, non-paged `sq > 1` | 9.9.0 | Blackwell fprop wider-dim path passes. | Paged or `sq=1` branch before 9.10.2. |
+| Any arch fprop, wider dims, paged or selected `sq=1`/`sq>1` cases | 9.10.2 | Broad fprop wider-dim path passes. | cuDNN 9.10.0/9.10.1 or branch outside the paged/`sq` conditions. |
+| Blackwell bprop `(head_dim_qk, head_dim_v) = (192, 128)` | 9.11.0 | Blackwell training special case passes. | Other wider Blackwell bprop shape without support. |
+| Hopper training MLA with both dims `>=128`, unequal dims, not `(192, 128)` | N/A | None | Explicit cuDNN 9.11+ exclusion. |
+
+#### F16 Layout and Mask Gate
+
+| Input branch | Minimum cuDNN | Narrowed scope if gate passes | Reject if |
+| --- | --- | --- | --- |
+| BSHD/SBHD with `causal` | 8.9.0 | Base causal mask path passes. | Other gates fail. |
+| BSHD/SBHD with `no_mask`, `padding`, or `padding_causal` | 8.9.6 | Common dense layout masks pass. | `post_scale_bias` with `padding` or `padding_causal`. |
+| THD with `padding` or `padding_causal`, MHA | 9.1.0 | THD padding-style MHA path passes. | `sm < 90`, non-MHA before 9.6, or unsupported ragged offset. |
+| THD with `padding` or `padding_causal`, GQA/MQA | 9.6.0 | THD padding-style GQA/MQA path passes. | `sm < 90` or unsupported ragged offset. |
+| Split Q/KV layout combinations | 9.7.0 | Split layout group can continue through later gates. | cuDNN `< 9.7.0`. |
+| Paged KV layout with `padding` or `padding_causal` | 9.5.0 | Paged KV padding-style path passes. | cuDNN `< 9.5.0`. |
+| `causal_bottom_right`, BSHD/SBHD | 9.3.0 | Bottom-right causal passes with `sq <= skv`, 64-divisible lengths, no bias, zero dropout. | cuDNN `< 9.7.0` and bottom-right length constraints fail. |
+| `padding_causal_bottom_right`, BSHD/SBHD/THD | 9.6.0 | Padding bottom-right path passes with `sq <= skv`, no bias, zero dropout. | cuDNN `< 9.7.0` and bottom-right length constraints fail. |
+| Bottom-right masks on split, paged, or broader layout groups | 9.7.0 | Bottom-right path passes with `sq <= skv`; 64-divisibility relaxed. | Bias/dropout constraints fail. |
+| `arbitrary` mask | N/A | None | cuDNN F16 fused backend does not support arbitrary masks. |
+
+#### F16 Modifier Gate
+
+| Input branch | Minimum cuDNN | Narrowed scope if gate passes | Reject if |
+| --- | --- | --- | --- |
+| `no_bias` | 8.9.0 | Bias gate passes. | Other gates fail. |
+| ALiBi | 8.9.6 | Converts to non-trainable post-scale bias on `sm90+` for selected non-padding masks. | `sm < 90` or padding-style excluded masks. |
+| `post_scale_bias` on `sm90+` | 8.9.6 | Post-scale bias can pass if mask is not excluded. | `padding` or `padding_causal`; Python `111s` trainable dbias exclusion. |
+| `post_scale_bias` on `sm80+` | 9.0.0 | Post-scale bias can pass if mask is not excluded. | `padding` or `padding_causal`; Python `111s` trainable dbias exclusion. |
+| Sliding window, top-left BSHD/SBHD | 9.2.0 | SWA passes with no bias, zero dropout, `sq <= skv`. | THD/broader masks before 9.6. |
+| Sliding window, BSHD/SBHD/THD broader masks | 9.6.0 | SWA passes with no bias, zero dropout, `sq <= skv`. | cuDNN 9.14.0 with non-causal SWA and `max_seqlen_kv > 1024`. |
+| Non-vanilla softmax | 9.13.1 | cuDNN supports off-by-one and learnable softmax. | THD with cuDNN `< 9.18.0` due to Python pre-filter. |
+| CUDA graph training, BSHD/SBHD, non-padding mask, `max_seqlen_kv % 128 != 0` | 9.15.1 | Graph-captured training path passes. | cuDNN `<= 9.15.0`. |
+| Deterministic F16 training | 8.9.5 plus `sm90+` in Python | Passes only with no trainable attention bias; Blackwell deterministic training requires 9.18.1+, zero dropout, no bias. | `sm120` deterministic training; trainable bias gradients; older cuDNN. |
+
+<a id="fused-fp8-cudnn-support-resolver"></a>
+
+### Fused FP8 cuDNN Support Resolver
+
+Use this table after a routing row leaves Fused FP8 as a candidate. Python
+recipe filters run before the cuDNN FP8 sub-backend check. Unlike F16, FP8 is
+best represented as a small set of mutually narrowing recipe and cuDNN path
+rows.
+
+#### FP8 Always-On Gates
+
+| Axis | Requirement before version rows matter |
+| --- | --- |
+| Dtype | Q and KV dtype passed to cuDNN must be FP8. |
+| Architecture | `sm90+` is required, but Python disables FP8 attention on `sm120`. |
+| Bias and outputs | Bias must be `no_bias`, `return_max_logit=False`, and 64-bit ragged offsets must not be required. |
+| Bad cuDNN versions | cuDNN 9.10.0 is excluded for FP8 SDPA. |
+| Python FP8 recipe filters | Block scaling and NVFP4 recipes remove FusedAttention before cuDNN. |
+| Python feature filters | FP8 KV cache removes FusedAttention; FP8 CP removes FusedAttention for THD or any bias. |
+
+#### FP8 Recipe Gate
+
+| Input branch | Minimum cuDNN before cuDNN path | Narrowed scope if gate passes | Reject if |
+| --- | --- | --- | --- |
+| Delayed scaling, `fp8_dpa=True` | 9.2.1 | Continue to FP8 cuDNN path gate. | cuDNN `< 9.2.1`; deterministic `sm100+` with cuDNN `< 9.18.0`. |
+| Current scaling | 9.14.0 | Continue only on `sm100+`. | `sm < 100`, cuDNN `< 9.14.0`, or deterministic current scaling with cuDNN `< 9.18.0`. |
+| MXFP8 | 9.21.0 | Continue only on `sm100+`, `fp8_mha=False`, and non-THD QKV format. | `sm < 100`, cuDNN `< 9.21.0`, `fp8_mha=True`, or THD. |
+| Block scaling or NVFP4 | N/A | None | Python removes FusedAttention before cuDNN. |
+
+#### FP8 cuDNN Path Gate
+
+| Input branch | Minimum cuDNN | Narrowed scope if gate passes | Reject if |
+| --- | --- | --- | --- |
+| Early `sm90` delayed-scaling path | 9.2.1 | BSHD/SBHD, vanilla softmax, `no_mask` or `causal`, both sequence lengths divisible by 128, `head_dim_qk=head_dim_v=128`. | Padding masks, BHSD, non-vanilla softmax, non-128 head dims, or non-divisible sequence lengths. |
+| General FP8 path before 9.21 | 9.7.0 | BSHD/SBHD, vanilla softmax, `no_mask`, `causal`, `padding`, or `padding_causal`; head dims multiples of 16. On `sm90`, inference allows dims `<=256` and training requires both dims 128. On `sm100+`, dims must be `<=128`. | BHSD, non-vanilla softmax, bottom-right mask, unsupported dimensions. |
+| Current-scaling path | 9.14.0 | Same cuDNN path as 9.7 row, but Python now allows current scaling on `sm100+`. | Same exclusions as 9.7 row plus current-scaling recipe gate failures. |
+| Broad `sm100+` FP8 path | 9.21.0 | BSHD/SBHD/BHSD; vanilla, off-by-one, or learnable softmax; `no_mask`, `causal`, or `causal_bottom_right`; `head_dim_qk <= 192`, `head_dim_v <= 128`, dimensions multiple of 16. | THD, padding masks in the 9.21-only broad path, bias, `sm120`, unsupported dimensions. |
+| FP8 sliding window | 9.21.0 | SWA can pass only on `sm100+` after the broad path and Python SWA gates. | `sm < 100`, cuDNN `< 9.21.0`, bias, or unsupported dropout/mask combination. |
+| FP8 deterministic training | 9.19.0 | Deterministic training can pass after recipe and cuDNN path gates. | Training with deterministic mode and cuDNN `< 9.19.0`. |
+
+## Cross-Cutting Modifier Tables
+
+These modifiers should be applied after selecting the closest hardware,
+precision, execution, and layout branch.
+
+### Bias and ALiBi
+
+| Bias branch | FA2 | FA3 | FA4 | Fused F16 | Fused FP8 | Unfused |
+| --- | --- | --- | --- | --- | --- | --- |
+| No actual bias tensor, `core_attention_bias_shape=None` | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [F16 resolver](#fused-f16-cudnn-support-resolver). | Candidate; apply [FP8 resolver](#fused-fp8-cudnn-support-resolver). | Yes. |
+| ALiBi | Candidate; apply [Flash resolver](#flashattention-support-resolver) ALiBi row. | No. | No. | Candidate after conversion to non-trainable post-scale bias; apply [F16 resolver](#fused-f16-cudnn-support-resolver) bias rows. | No. | Yes. |
+| `pre_scale_bias` | No. | No. | No. | No. | No. | Yes. |
+| Non-trainable `post_scale_bias` | No. | No. | No. | Candidate; apply [F16 resolver](#fused-f16-cudnn-support-resolver) bias rows. | No. | Yes. |
+| Trainable `post_scale_bias` | No. | No. | No. | Only supported dbias shapes. Trainable `111s` disables FusedAttention; deterministic bias grad disables FusedAttention. | No. | Yes. |
+
+### Dropout, Softmax, Determinism
+
+| Modifier | FA2 | FA3 | FA4 | Fused F16 | Fused FP8 | Unfused |
+| --- | --- | --- | --- | --- | --- | --- |
+| Nonzero dropout | Candidate; apply [Flash resolver](#flashattention-support-resolver). | No. | No. | Candidate; apply [F16 resolver](#fused-f16-cudnn-support-resolver) dropout/mask/SWA rows. | Candidate; apply [FP8 resolver](#fused-fp8-cudnn-support-resolver). | Yes. |
+| `softmax_type != "vanilla"` | No. | No. | No. | Candidate; apply [F16 resolver](#fused-f16-cudnn-support-resolver) softmax row. | Candidate; apply [FP8 resolver](#fused-fp8-cudnn-support-resolver) softmax row. | Yes for non-FP8; no for FP8. |
+| Deterministic mode, no bias, vanilla softmax | Candidate; apply [Flash resolver](#flashattention-support-resolver) determinism row. | Candidate; apply [Flash resolver](#flashattention-support-resolver) determinism row. | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [F16 resolver](#fused-f16-cudnn-support-resolver) determinism row. | Candidate; apply [FP8 resolver](#fused-fp8-cudnn-support-resolver) determinism rows. | Yes. |
+| Deterministic trainable bias | No for explicit bias. | No for explicit bias. | No for explicit bias. | No when deterministic training needs bias gradients. | No. | Yes. |
+
+### Head Geometry
+
+| Geometry | FA2 | FA3 | FA4 | Fused F16 | Fused FP8 | Unfused |
+| --- | --- | --- | --- | --- | --- | --- |
+| MHA, `num_heads == num_gqa_groups` | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [F16 resolver](#fused-f16-cudnn-support-resolver) GQA/MQA row. | Candidate; apply [FP8 resolver](#fused-fp8-cudnn-support-resolver). | Yes. |
+| GQA/MQA | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [F16 resolver](#fused-f16-cudnn-support-resolver) GQA/MQA row. | Candidate; apply [FP8 resolver](#fused-fp8-cudnn-support-resolver). | Yes. |
+| MLA, `head_dim_qk != head_dim_v` | No. | Candidate; apply [Flash resolver](#flashattention-support-resolver) head-dimension row. | Candidate; apply [Flash resolver](#flashattention-support-resolver) head-dimension row. | Candidate only with separate Q/K/V layout; apply [F16 resolver](#fused-f16-cudnn-support-resolver) head-dimension rows. | Candidate only with no bias; apply [FP8 resolver](#fused-fp8-cudnn-support-resolver). | Yes. |
+| Head dimensions multiple of 8 and `<= 128` | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [Flash resolver](#flashattention-support-resolver). | Candidate; apply [F16 resolver](#fused-f16-cudnn-support-resolver) head-dimension rows. | Candidate; apply [FP8 resolver](#fused-fp8-cudnn-support-resolver) head-dimension rows. | Yes. |
+| Wider head dimensions up to 256 | Candidate; apply [Flash resolver](#flashattention-support-resolver) head-dimension row. | Candidate; apply [Flash resolver](#flashattention-support-resolver) head-dimension row. | Candidate; apply [Flash resolver](#flashattention-support-resolver) head-dimension row. | Candidate; apply [F16 resolver](#fused-f16-cudnn-support-resolver) head-dimension rows. | Candidate; apply [FP8 resolver](#fused-fp8-cudnn-support-resolver) head-dimension rows. | Yes. |
+| `head_dim_qk > 256` | No. | No. | Candidate only if FA4 validates it; apply [Flash resolver](#flashattention-support-resolver). | Candidate only for limited cuDNN branches; apply [F16 resolver](#fused-f16-cudnn-support-resolver). | Candidate only for limited cuDNN FP8 branches; apply [FP8 resolver](#fused-fp8-cudnn-support-resolver). | Yes. |
+
+## Probe Results Used While Drafting
+
+These selector-only checks were run on H100 (`sm90`), CUDA 13.2, cuDNN 9.21.0,
+FlashAttention 2.7.4.post1 installed, and no FA3 or FA4 installed:
+
+| Configuration | Selected backend | Candidate availability before priority |
+| --- | --- | --- |
+| BF16 causal BSHD MHA, no bias | Fused `NVTE_F16_arbitrary_seqlen` | `[1, 1, 1]` |
+| Same with `NVTE_FUSED_ATTN=0` | FlashAttention 2 | `[1, 0, 1]` |
+| GQA, 16 query heads and 4 K/V groups | Fused `NVTE_F16_arbitrary_seqlen` | `[1, 1, 1]` |
+| MQA, 16 query heads and 1 K/V group | Fused `NVTE_F16_arbitrary_seqlen` | `[1, 1, 1]` |
+| MLA with `head_dim_qk=64`, `head_dim_v=128` | Fused `NVTE_F16_arbitrary_seqlen` | `[False, 1, 1]` |
+| `arbitrary` mask | Unfused | `[False, False, 1]` |
+| Deterministic trainable `post_scale_bias` | Unfused | `[False, False, 1]` |
+| THD context parallelism with `cp_comm_type="all_gather"` | FlashAttention 2 | `[1, False, False]` |
+| Top-left causal cross-attention | Fused `NVTE_F16_arbitrary_seqlen` | `[False, 1, 1]` |
+| `causal_bottom_right` cross-attention | Fused `NVTE_F16_arbitrary_seqlen` | `[1, 1, 1]` |
+| FP8 delayed scaling, `head_dim_qk=head_dim_v=128` | Fused `NVTE_FP8` | `[False, 1, False]` |
+| FP8 current scaling, `head_dim_qk=head_dim_v=128` on `sm90` | No backend | `[False, False, False]` |