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Metal: Optimize q8_0 KV - #25556

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Metal: Optimize q8_0 KV#25556
tarruda wants to merge 3 commits into
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tarruda:optimize-metal-q8_0-kv

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@tarruda

@tarruda tarruda commented Jul 11, 2026

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Overview

Suggesting some GPT 5.6 Sol improvements made to Metal KV q8_0

Additional information

More context in this thread: #25555 (comment)

Requirements

  • I have read and agree with the contributing guidelines
  • AI usage disclosure: Yes, 100% created by GPT 5.6 Sol xhigh. Submitting as a draft/RFC PR as suggested by @ggerganov in the linked discussion

tarruda added 3 commits July 10, 2026 21:20
Add a packed_char4 Q8_0 dequantization helper and use it for the 256-wide Metal
vector flash-attention specialization. Loading four signed cache bytes as one
packed vector reduces scalar indexing and conversion overhead while leaving
other head sizes on the generic helper, since applying the packed path broadly
regressed the 64-wide case.

Add Qwen 3.5 shaped FLASH_ATTN_EXT coverage for the 256-wide, GQA-16 cache
layout, including native and permuted views plus 10K and 20K operation
benchmarks.

Assisted-by: Codex
Generalize the Metal vector flash-attention kernel to process two adjacent GQA
query heads in one threadgroup so they can share each K/V load and
dequantization pass. Keep independent query, softmax, output, and reduction
state for both heads, and retain the one-head specialization as a fallback.

Add a block-parallel Q8_0-to-F16 conversion kernel that dequantizes and
transposes K and V into contiguous operation-local scratch. Route eligible
one-token, 256-wide, high-GQA attention with at least 1024 visible cache
positions through the existing F16 vector attention pipeline using effective
F16 buffers and strides. Account for F16 scratch and padding in Metal
allocation sizing, insert the producer-to-consumer barrier, and preserve
final-chunk padding and partial-result reduction.

Extend FLASH_ATTN_EXT correctness and performance coverage for short-context
fallback, contiguous and permuted scratch layouts, multiple streams, padding,
sinks, ALiBi, logit softcap, and exact Qwen 3.5 397B 10K/20K decode shapes. The
persistent KV cache remains Q8_0.

Assisted-by: Codex
Move the Q8_0-to-F16 conversion setup ahead of the vector/non-vector
flash-attention split so both decode and prompt processing can consume the same
temporary K/V representation. Extend materialization eligibility to prompt
batches with at least 64 queries while retaining the 256-wide, GQA, and
1024-position gates.

Allow the non-vector Metal pipeline helper to select the effective F16
specialization and contiguous F16 stride constants even though the persistent
tensors are Q8_0. Pass the scratch buffers and effective strides through
final-chunk padding and matrix-oriented attention, and omit quantized
threadgroup staging when scratch is active.

Add a permuted, unaligned 64-query correctness case and Q8_0/F16 performance
cases for 512-query prompts at 10K and 20K depth. Short prompts, small query
batches, unsupported shapes, and non-Q8_0 caches continue to use their existing
paths.

Assisted-by: Codex
@github-actions github-actions Bot added testing Everything test related ggml changes relating to the ggml tensor library for machine learning Apple Metal https://en.wikipedia.org/wiki/Metal_(API) labels Jul 11, 2026
@ggerganov ggerganov self-assigned this Jul 11, 2026
@forforever73

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Thanks for this — it's a really valuable PR, and you've identified the repeated dequant cost of Q8_0 KV very clearly.

Your H=2 GQA approach is quite close to the direction I explored in #23114 (though along a different axis — you're grouping query heads, whereas I was grouping query rows). From the discussion there with @ggerganov , one of the main concerns was the long-term maintainability of hardcoded optimization paths. That's why I've been working on a cross-device, generic approach in #25750 (still a work in progress), and I think the H dimension could potentially fit into that framework later as well.

The Q8_0 → F16 materialization also looks like it could be a solid standalone PR. It follows the same idea as what the CUDA backend already does in launch_fattn, so it would be quite natural to generalize it across different quantization formats and head sizes. If you don't have time to work on that, I'd be happy to pick it up in the future.

@tarruda

tarruda commented Jul 26, 2026

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and you've identified the repeated dequant cost of Q8_0 KV very clearly.

I wish I could take credit for this, but my only contribution was prompting GPT.

The Q8_0 → F16 materialization also looks like it could be a solid standalone PR

Feel free to take anything you need out of this PR and submit a new one with the relevant parts.

@anthonyalayo

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The performance lift with q8_0 is huge from this PR. I hope the llama.cpp team can prioritize merging it.

@tarruda

tarruda commented Aug 1, 2026

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@anthonyalayo it is pure AI code, and I've not put any effort into splitting or cleaning things up. I opened this with the hope that a metal kernel developer can extract the good parts and submit a proper contribution.

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That's fair. I made a fork with the branch so I can utilize it in the meantime.

ggerganov added a commit that referenced this pull request Aug 20, 2026
* metal: dequantize q8_0 KV to f16 before flash attention

Add a preprocessing pass for GGML_OP_FLASH_ATTN_EXT on the Metal backend:
when the KV cache is quantized (Q8_0 for now), dequantize K and V into a
contiguous F16 scratch buffer and run the existing F16 flash attention
kernels on it, instead of the in-kernel dequantization path.

- new kernel kernel_flash_attn_ext_dequant_to_f16<block_t, QK, deq_t4x4>:
  one thread per quant block (K then V), stride-aware so permuted KV is
  supported; instantiated for Q8_0 (extending to Q4_0/Q4_1/Q5_0/Q5_1 is
  one instantiation + one gate case)
- the gate is type-only: dequantize whenever the KV is quantized,
  regardless of head sizes, GQA ratio or n_kv; the attention kernels
  themselves are untouched
- the F16 copies live in the op's own scratch allocation
  (ggml_metal_op_flash_attn_ext_extra_dequant_f16); the KV pad kernel
  reads the dequantized buffers when the path is active
- the FA pipeline getters gain a use_f16_kv flag selecting the existing
  f16 kernels and contiguous strides
- ref: #25556

Verification (M2 Ultra):
- test-backend-ops test -o FLASH_ATTN_EXT: 4798/4798 pass, including the
  new q8_0 eval cases (decode/prompt, permuted, sinks+ALiBi+softcap,
  kv=113 pad path, kv=16384)
- llama-perplexity on Qwen2.5-0.5B with -ctk q8_0 -ctv q8_0 matches the
  f16 KV reference (PPL 1.0008 vs 1.0008)

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : launch the FA KV dequant kernel separately for K and V

Simplify kernel_flash_attn_ext_dequant_to_f16: it now dequantizes a single
tensor (its own ne/nb and dst) with no is_v branching, and the op dispatches
it twice with the same pipeline - once for K and once for V. The kargs
struct shrinks to a single ne/nb set plus nblocks.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : dequantize q4_0, q4_1, q5_0 and q5_1 KV to f16 before flash attention

The dequant pass now covers all quantized KV types supported by the Metal
flash attention kernels. The dequant kernel, kargs, scratch allocation and
dispatch are type-generic, so each type is one kernel instantiation plus one
gate case.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : skip the redundant V dequant when V is a view of K

In MLA-based models, the V of the FA op is a view of K (the first ne20
elements of each K row); the dequantized V is then a view of the dequantized
K, so skip the second dequant dispatch, do not reserve the V scratch region,
and let the pad and attention kernels read V from the K F16 buffer with K's
strides. The detection follows the CUDA backend:
V->view_src && (V->view_src == K || (V->view_src == K->view_src && V->view_offs == K->view_offs))

Also fix the FA pipeline getters: ns10/ns20 are function constants baked into
the kernels and must be the actual K/V row widths as seen by the kernel. The
dispatch now passes them explicitly (nb11_attn/nb10_attn, nb21_attn/nb20_attn)
instead of the getters assuming contiguous F16 KV (ns20 = dv), which was wrong
when V is read from K with K's row pitch (e.g. 576 vs 512).

New test cases: 576/512 q8_0 (MLA shape, V is a view of K) at kv=113 (KV pad),
nb=1 (vec) and nb=64 (non-vec).

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* test : remove backend-specific wording from test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* pi : avoid backend mentions in test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : rename the FA dequant_f16 identifiers to kv_f16

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* cont : clean-up

* cont : remove TODO
ggerganov added a commit to ggml-org/ggml that referenced this pull request Aug 21, 2026
…27390)

* metal: dequantize q8_0 KV to f16 before flash attention

Add a preprocessing pass for GGML_OP_FLASH_ATTN_EXT on the Metal backend:
when the KV cache is quantized (Q8_0 for now), dequantize K and V into a
contiguous F16 scratch buffer and run the existing F16 flash attention
kernels on it, instead of the in-kernel dequantization path.

- new kernel kernel_flash_attn_ext_dequant_to_f16<block_t, QK, deq_t4x4>:
  one thread per quant block (K then V), stride-aware so permuted KV is
  supported; instantiated for Q8_0 (extending to Q4_0/Q4_1/Q5_0/Q5_1 is
  one instantiation + one gate case)
- the gate is type-only: dequantize whenever the KV is quantized,
  regardless of head sizes, GQA ratio or n_kv; the attention kernels
  themselves are untouched
- the F16 copies live in the op's own scratch allocation
  (ggml_metal_op_flash_attn_ext_extra_dequant_f16); the KV pad kernel
  reads the dequantized buffers when the path is active
- the FA pipeline getters gain a use_f16_kv flag selecting the existing
  f16 kernels and contiguous strides
- ref: ggml-org/llama.cpp#25556

Verification (M2 Ultra):
- test-backend-ops test -o FLASH_ATTN_EXT: 4798/4798 pass, including the
  new q8_0 eval cases (decode/prompt, permuted, sinks+ALiBi+softcap,
  kv=113 pad path, kv=16384)
- llama-perplexity on Qwen2.5-0.5B with -ctk q8_0 -ctv q8_0 matches the
  f16 KV reference (PPL 1.0008 vs 1.0008)

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : launch the FA KV dequant kernel separately for K and V

Simplify kernel_flash_attn_ext_dequant_to_f16: it now dequantizes a single
tensor (its own ne/nb and dst) with no is_v branching, and the op dispatches
it twice with the same pipeline - once for K and once for V. The kargs
struct shrinks to a single ne/nb set plus nblocks.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : dequantize q4_0, q4_1, q5_0 and q5_1 KV to f16 before flash attention

The dequant pass now covers all quantized KV types supported by the Metal
flash attention kernels. The dequant kernel, kargs, scratch allocation and
dispatch are type-generic, so each type is one kernel instantiation plus one
gate case.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : skip the redundant V dequant when V is a view of K

In MLA-based models, the V of the FA op is a view of K (the first ne20
elements of each K row); the dequantized V is then a view of the dequantized
K, so skip the second dequant dispatch, do not reserve the V scratch region,
and let the pad and attention kernels read V from the K F16 buffer with K's
strides. The detection follows the CUDA backend:
V->view_src && (V->view_src == K || (V->view_src == K->view_src && V->view_offs == K->view_offs))

Also fix the FA pipeline getters: ns10/ns20 are function constants baked into
the kernels and must be the actual K/V row widths as seen by the kernel. The
dispatch now passes them explicitly (nb11_attn/nb10_attn, nb21_attn/nb20_attn)
instead of the getters assuming contiguous F16 KV (ns20 = dv), which was wrong
when V is read from K with K's row pitch (e.g. 576 vs 512).

New test cases: 576/512 q8_0 (MLA shape, V is a view of K) at kv=113 (KV pad),
nb=1 (vec) and nb=64 (non-vec).

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* test : remove backend-specific wording from test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* pi : avoid backend mentions in test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : rename the FA dequant_f16 identifiers to kv_f16

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* cont : clean-up

* cont : remove TODO
ggerganov added a commit to ggml-org/whisper.cpp that referenced this pull request Aug 21, 2026
…27390)

* metal: dequantize q8_0 KV to f16 before flash attention

Add a preprocessing pass for GGML_OP_FLASH_ATTN_EXT on the Metal backend:
when the KV cache is quantized (Q8_0 for now), dequantize K and V into a
contiguous F16 scratch buffer and run the existing F16 flash attention
kernels on it, instead of the in-kernel dequantization path.

- new kernel kernel_flash_attn_ext_dequant_to_f16<block_t, QK, deq_t4x4>:
  one thread per quant block (K then V), stride-aware so permuted KV is
  supported; instantiated for Q8_0 (extending to Q4_0/Q4_1/Q5_0/Q5_1 is
  one instantiation + one gate case)
- the gate is type-only: dequantize whenever the KV is quantized,
  regardless of head sizes, GQA ratio or n_kv; the attention kernels
  themselves are untouched
- the F16 copies live in the op's own scratch allocation
  (ggml_metal_op_flash_attn_ext_extra_dequant_f16); the KV pad kernel
  reads the dequantized buffers when the path is active
- the FA pipeline getters gain a use_f16_kv flag selecting the existing
  f16 kernels and contiguous strides
- ref: ggml-org/llama.cpp#25556

Verification (M2 Ultra):
- test-backend-ops test -o FLASH_ATTN_EXT: 4798/4798 pass, including the
  new q8_0 eval cases (decode/prompt, permuted, sinks+ALiBi+softcap,
  kv=113 pad path, kv=16384)
- llama-perplexity on Qwen2.5-0.5B with -ctk q8_0 -ctv q8_0 matches the
  f16 KV reference (PPL 1.0008 vs 1.0008)

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : launch the FA KV dequant kernel separately for K and V

Simplify kernel_flash_attn_ext_dequant_to_f16: it now dequantizes a single
tensor (its own ne/nb and dst) with no is_v branching, and the op dispatches
it twice with the same pipeline - once for K and once for V. The kargs
struct shrinks to a single ne/nb set plus nblocks.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : dequantize q4_0, q4_1, q5_0 and q5_1 KV to f16 before flash attention

The dequant pass now covers all quantized KV types supported by the Metal
flash attention kernels. The dequant kernel, kargs, scratch allocation and
dispatch are type-generic, so each type is one kernel instantiation plus one
gate case.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : skip the redundant V dequant when V is a view of K

In MLA-based models, the V of the FA op is a view of K (the first ne20
elements of each K row); the dequantized V is then a view of the dequantized
K, so skip the second dequant dispatch, do not reserve the V scratch region,
and let the pad and attention kernels read V from the K F16 buffer with K's
strides. The detection follows the CUDA backend:
V->view_src && (V->view_src == K || (V->view_src == K->view_src && V->view_offs == K->view_offs))

Also fix the FA pipeline getters: ns10/ns20 are function constants baked into
the kernels and must be the actual K/V row widths as seen by the kernel. The
dispatch now passes them explicitly (nb11_attn/nb10_attn, nb21_attn/nb20_attn)
instead of the getters assuming contiguous F16 KV (ns20 = dv), which was wrong
when V is read from K with K's row pitch (e.g. 576 vs 512).

New test cases: 576/512 q8_0 (MLA shape, V is a view of K) at kv=113 (KV pad),
nb=1 (vec) and nb=64 (non-vec).

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* test : remove backend-specific wording from test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* pi : avoid backend mentions in test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : rename the FA dequant_f16 identifiers to kv_f16

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* cont : clean-up

* cont : remove TODO
@tarruda

tarruda commented Aug 22, 2026

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Trying the same benchmarks I posted on #25555 using the latest master branch, I got much better prompt processing numbers:

% ./build/bin/llama-bench --mmap 1 -m ~/qwen-3.5-397b/Qwen3.5-397B-A17B-IQ3_XXS-00001-of-00004.gguf -fa 1 -d 0,10000,20000 -n 128 -p 512 -ctk q8_0 -c
tv q8_0
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.014 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name:   MTL0 (Apple M1 Ultra)
ggml_metal_device_init: GPU family: MTLGPUFamilyApple7  (1007)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal4  (5002)
ggml_metal_device_init: simdgroup reduction   = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory    = true
ggml_metal_device_init: has bfloat            = true
ggml_metal_device_init: has tensor            = false
ggml_metal_device_init: use residency sets    = true
ggml_metal_device_init: use shared buffers    = true
ggml_metal_device_init: recommendedMaxWorkingSetSize  = 134217.73 MB
DEPRECATED: -mmp and --mmap are deprecated in favour of --load-mode. Please use --load-mode mmap instead.
| model                          |       size |     params | backend    | threads | type_k | type_v |  fa |         lm |            test |                  t/s |
| ------------------------------ | ---------: | ---------: | ---------- | ------: | -----: | -----: | --: | ---------: | --------------: | -------------------: |
| qwen35moe 397B.A17B Q8_0       | 117.16 GiB |   396.35 B | MTL,BLAS   |      16 |   q8_0 |   q8_0 |   1 |       mmap |           pp512 |        188.18 ± 1.99 |
| qwen35moe 397B.A17B Q8_0       | 117.16 GiB |   396.35 B | MTL,BLAS   |      16 |   q8_0 |   q8_0 |   1 |       mmap |           tg128 |         22.56 ± 0.02 |
| qwen35moe 397B.A17B Q8_0       | 117.16 GiB |   396.35 B | MTL,BLAS   |      16 |   q8_0 |   q8_0 |   1 |       mmap |  pp512 @ d10000 |        161.85 ± 0.45 |
| qwen35moe 397B.A17B Q8_0       | 117.16 GiB |   396.35 B | MTL,BLAS   |      16 |   q8_0 |   q8_0 |   1 |       mmap |  tg128 @ d10000 |         13.45 ± 0.18 |
| qwen35moe 397B.A17B Q8_0       | 117.16 GiB |   396.35 B | MTL,BLAS   |      16 |   q8_0 |   q8_0 |   1 |       mmap |  pp512 @ d20000 |        139.66 ± 1.02 |
| qwen35moe 397B.A17B Q8_0       | 117.16 GiB |   396.35 B | MTL,BLAS   |      16 |   q8_0 |   q8_0 |   1 |       mmap |  tg128 @ d20000 |         10.42 ± 0.01 |

Token generation still takes a big hit, so I'm leaving this open for now

fishlikeX pushed a commit to fishlikeX/sm70-attn that referenced this pull request Aug 23, 2026
* metal: dequantize q8_0 KV to f16 before flash attention

Add a preprocessing pass for GGML_OP_FLASH_ATTN_EXT on the Metal backend:
when the KV cache is quantized (Q8_0 for now), dequantize K and V into a
contiguous F16 scratch buffer and run the existing F16 flash attention
kernels on it, instead of the in-kernel dequantization path.

- new kernel kernel_flash_attn_ext_dequant_to_f16<block_t, QK, deq_t4x4>:
  one thread per quant block (K then V), stride-aware so permuted KV is
  supported; instantiated for Q8_0 (extending to Q4_0/Q4_1/Q5_0/Q5_1 is
  one instantiation + one gate case)
- the gate is type-only: dequantize whenever the KV is quantized,
  regardless of head sizes, GQA ratio or n_kv; the attention kernels
  themselves are untouched
- the F16 copies live in the op's own scratch allocation
  (ggml_metal_op_flash_attn_ext_extra_dequant_f16); the KV pad kernel
  reads the dequantized buffers when the path is active
- the FA pipeline getters gain a use_f16_kv flag selecting the existing
  f16 kernels and contiguous strides
- ref: ggml-org/llama.cpp#25556

Verification (M2 Ultra):
- test-backend-ops test -o FLASH_ATTN_EXT: 4798/4798 pass, including the
  new q8_0 eval cases (decode/prompt, permuted, sinks+ALiBi+softcap,
  kv=113 pad path, kv=16384)
- llama-perplexity on Qwen2.5-0.5B with -ctk q8_0 -ctv q8_0 matches the
  f16 KV reference (PPL 1.0008 vs 1.0008)

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : launch the FA KV dequant kernel separately for K and V

Simplify kernel_flash_attn_ext_dequant_to_f16: it now dequantizes a single
tensor (its own ne/nb and dst) with no is_v branching, and the op dispatches
it twice with the same pipeline - once for K and once for V. The kargs
struct shrinks to a single ne/nb set plus nblocks.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : dequantize q4_0, q4_1, q5_0 and q5_1 KV to f16 before flash attention

The dequant pass now covers all quantized KV types supported by the Metal
flash attention kernels. The dequant kernel, kargs, scratch allocation and
dispatch are type-generic, so each type is one kernel instantiation plus one
gate case.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : skip the redundant V dequant when V is a view of K

In MLA-based models, the V of the FA op is a view of K (the first ne20
elements of each K row); the dequantized V is then a view of the dequantized
K, so skip the second dequant dispatch, do not reserve the V scratch region,
and let the pad and attention kernels read V from the K F16 buffer with K's
strides. The detection follows the CUDA backend:
V->view_src && (V->view_src == K || (V->view_src == K->view_src && V->view_offs == K->view_offs))

Also fix the FA pipeline getters: ns10/ns20 are function constants baked into
the kernels and must be the actual K/V row widths as seen by the kernel. The
dispatch now passes them explicitly (nb11_attn/nb10_attn, nb21_attn/nb20_attn)
instead of the getters assuming contiguous F16 KV (ns20 = dv), which was wrong
when V is read from K with K's row pitch (e.g. 576 vs 512).

New test cases: 576/512 q8_0 (MLA shape, V is a view of K) at kv=113 (KV pad),
nb=1 (vec) and nb=64 (non-vec).

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* test : remove backend-specific wording from test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* pi : avoid backend mentions in test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : rename the FA dequant_f16 identifiers to kv_f16

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* cont : clean-up

* cont : remove TODO
fishlikeX pushed a commit to fishlikeX/sm70-attn that referenced this pull request Aug 23, 2026
* metal: dequantize q8_0 KV to f16 before flash attention

Add a preprocessing pass for GGML_OP_FLASH_ATTN_EXT on the Metal backend:
when the KV cache is quantized (Q8_0 for now), dequantize K and V into a
contiguous F16 scratch buffer and run the existing F16 flash attention
kernels on it, instead of the in-kernel dequantization path.

- new kernel kernel_flash_attn_ext_dequant_to_f16<block_t, QK, deq_t4x4>:
  one thread per quant block (K then V), stride-aware so permuted KV is
  supported; instantiated for Q8_0 (extending to Q4_0/Q4_1/Q5_0/Q5_1 is
  one instantiation + one gate case)
- the gate is type-only: dequantize whenever the KV is quantized,
  regardless of head sizes, GQA ratio or n_kv; the attention kernels
  themselves are untouched
- the F16 copies live in the op's own scratch allocation
  (ggml_metal_op_flash_attn_ext_extra_dequant_f16); the KV pad kernel
  reads the dequantized buffers when the path is active
- the FA pipeline getters gain a use_f16_kv flag selecting the existing
  f16 kernels and contiguous strides
- ref: ggml-org/llama.cpp#25556

Verification (M2 Ultra):
- test-backend-ops test -o FLASH_ATTN_EXT: 4798/4798 pass, including the
  new q8_0 eval cases (decode/prompt, permuted, sinks+ALiBi+softcap,
  kv=113 pad path, kv=16384)
- llama-perplexity on Qwen2.5-0.5B with -ctk q8_0 -ctv q8_0 matches the
  f16 KV reference (PPL 1.0008 vs 1.0008)

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : launch the FA KV dequant kernel separately for K and V

Simplify kernel_flash_attn_ext_dequant_to_f16: it now dequantizes a single
tensor (its own ne/nb and dst) with no is_v branching, and the op dispatches
it twice with the same pipeline - once for K and once for V. The kargs
struct shrinks to a single ne/nb set plus nblocks.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : dequantize q4_0, q4_1, q5_0 and q5_1 KV to f16 before flash attention

The dequant pass now covers all quantized KV types supported by the Metal
flash attention kernels. The dequant kernel, kargs, scratch allocation and
dispatch are type-generic, so each type is one kernel instantiation plus one
gate case.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : skip the redundant V dequant when V is a view of K

In MLA-based models, the V of the FA op is a view of K (the first ne20
elements of each K row); the dequantized V is then a view of the dequantized
K, so skip the second dequant dispatch, do not reserve the V scratch region,
and let the pad and attention kernels read V from the K F16 buffer with K's
strides. The detection follows the CUDA backend:
V->view_src && (V->view_src == K || (V->view_src == K->view_src && V->view_offs == K->view_offs))

Also fix the FA pipeline getters: ns10/ns20 are function constants baked into
the kernels and must be the actual K/V row widths as seen by the kernel. The
dispatch now passes them explicitly (nb11_attn/nb10_attn, nb21_attn/nb20_attn)
instead of the getters assuming contiguous F16 KV (ns20 = dv), which was wrong
when V is read from K with K's row pitch (e.g. 576 vs 512).

New test cases: 576/512 q8_0 (MLA shape, V is a view of K) at kv=113 (KV pad),
nb=1 (vec) and nb=64 (non-vec).

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* test : remove backend-specific wording from test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* pi : avoid backend mentions in test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : rename the FA dequant_f16 identifiers to kv_f16

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* cont : clean-up

* cont : remove TODO
therealkenc pushed a commit to therealkenc/llama.cpp that referenced this pull request Aug 24, 2026
…rg#27390)

* metal: dequantize q8_0 KV to f16 before flash attention

Add a preprocessing pass for GGML_OP_FLASH_ATTN_EXT on the Metal backend:
when the KV cache is quantized (Q8_0 for now), dequantize K and V into a
contiguous F16 scratch buffer and run the existing F16 flash attention
kernels on it, instead of the in-kernel dequantization path.

- new kernel kernel_flash_attn_ext_dequant_to_f16<block_t, QK, deq_t4x4>:
  one thread per quant block (K then V), stride-aware so permuted KV is
  supported; instantiated for Q8_0 (extending to Q4_0/Q4_1/Q5_0/Q5_1 is
  one instantiation + one gate case)
- the gate is type-only: dequantize whenever the KV is quantized,
  regardless of head sizes, GQA ratio or n_kv; the attention kernels
  themselves are untouched
- the F16 copies live in the op's own scratch allocation
  (ggml_metal_op_flash_attn_ext_extra_dequant_f16); the KV pad kernel
  reads the dequantized buffers when the path is active
- the FA pipeline getters gain a use_f16_kv flag selecting the existing
  f16 kernels and contiguous strides
- ref: ggml-org#25556

Verification (M2 Ultra):
- test-backend-ops test -o FLASH_ATTN_EXT: 4798/4798 pass, including the
  new q8_0 eval cases (decode/prompt, permuted, sinks+ALiBi+softcap,
  kv=113 pad path, kv=16384)
- llama-perplexity on Qwen2.5-0.5B with -ctk q8_0 -ctv q8_0 matches the
  f16 KV reference (PPL 1.0008 vs 1.0008)

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : launch the FA KV dequant kernel separately for K and V

Simplify kernel_flash_attn_ext_dequant_to_f16: it now dequantizes a single
tensor (its own ne/nb and dst) with no is_v branching, and the op dispatches
it twice with the same pipeline - once for K and once for V. The kargs
struct shrinks to a single ne/nb set plus nblocks.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : dequantize q4_0, q4_1, q5_0 and q5_1 KV to f16 before flash attention

The dequant pass now covers all quantized KV types supported by the Metal
flash attention kernels. The dequant kernel, kargs, scratch allocation and
dispatch are type-generic, so each type is one kernel instantiation plus one
gate case.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : skip the redundant V dequant when V is a view of K

In MLA-based models, the V of the FA op is a view of K (the first ne20
elements of each K row); the dequantized V is then a view of the dequantized
K, so skip the second dequant dispatch, do not reserve the V scratch region,
and let the pad and attention kernels read V from the K F16 buffer with K's
strides. The detection follows the CUDA backend:
V->view_src && (V->view_src == K || (V->view_src == K->view_src && V->view_offs == K->view_offs))

Also fix the FA pipeline getters: ns10/ns20 are function constants baked into
the kernels and must be the actual K/V row widths as seen by the kernel. The
dispatch now passes them explicitly (nb11_attn/nb10_attn, nb21_attn/nb20_attn)
instead of the getters assuming contiguous F16 KV (ns20 = dv), which was wrong
when V is read from K with K's row pitch (e.g. 576 vs 512).

New test cases: 576/512 q8_0 (MLA shape, V is a view of K) at kv=113 (KV pad),
nb=1 (vec) and nb=64 (non-vec).

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* test : remove backend-specific wording from test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* pi : avoid backend mentions in test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : rename the FA dequant_f16 identifiers to kv_f16

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* cont : clean-up

* cont : remove TODO
ravel7524 pushed a commit to ravel7524/llama.cpp that referenced this pull request Aug 30, 2026
…rg#27390)

* metal: dequantize q8_0 KV to f16 before flash attention

Add a preprocessing pass for GGML_OP_FLASH_ATTN_EXT on the Metal backend:
when the KV cache is quantized (Q8_0 for now), dequantize K and V into a
contiguous F16 scratch buffer and run the existing F16 flash attention
kernels on it, instead of the in-kernel dequantization path.

- new kernel kernel_flash_attn_ext_dequant_to_f16<block_t, QK, deq_t4x4>:
  one thread per quant block (K then V), stride-aware so permuted KV is
  supported; instantiated for Q8_0 (extending to Q4_0/Q4_1/Q5_0/Q5_1 is
  one instantiation + one gate case)
- the gate is type-only: dequantize whenever the KV is quantized,
  regardless of head sizes, GQA ratio or n_kv; the attention kernels
  themselves are untouched
- the F16 copies live in the op's own scratch allocation
  (ggml_metal_op_flash_attn_ext_extra_dequant_f16); the KV pad kernel
  reads the dequantized buffers when the path is active
- the FA pipeline getters gain a use_f16_kv flag selecting the existing
  f16 kernels and contiguous strides
- ref: ggml-org#25556

Verification (M2 Ultra):
- test-backend-ops test -o FLASH_ATTN_EXT: 4798/4798 pass, including the
  new q8_0 eval cases (decode/prompt, permuted, sinks+ALiBi+softcap,
  kv=113 pad path, kv=16384)
- llama-perplexity on Qwen2.5-0.5B with -ctk q8_0 -ctv q8_0 matches the
  f16 KV reference (PPL 1.0008 vs 1.0008)

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : launch the FA KV dequant kernel separately for K and V

Simplify kernel_flash_attn_ext_dequant_to_f16: it now dequantizes a single
tensor (its own ne/nb and dst) with no is_v branching, and the op dispatches
it twice with the same pipeline - once for K and once for V. The kargs
struct shrinks to a single ne/nb set plus nblocks.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : dequantize q4_0, q4_1, q5_0 and q5_1 KV to f16 before flash attention

The dequant pass now covers all quantized KV types supported by the Metal
flash attention kernels. The dequant kernel, kargs, scratch allocation and
dispatch are type-generic, so each type is one kernel instantiation plus one
gate case.

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : skip the redundant V dequant when V is a view of K

In MLA-based models, the V of the FA op is a view of K (the first ne20
elements of each K row); the dequantized V is then a view of the dequantized
K, so skip the second dequant dispatch, do not reserve the V scratch region,
and let the pad and attention kernels read V from the K F16 buffer with K's
strides. The detection follows the CUDA backend:
V->view_src && (V->view_src == K || (V->view_src == K->view_src && V->view_offs == K->view_offs))

Also fix the FA pipeline getters: ns10/ns20 are function constants baked into
the kernels and must be the actual K/V row widths as seen by the kernel. The
dispatch now passes them explicitly (nb11_attn/nb10_attn, nb21_attn/nb20_attn)
instead of the getters assuming contiguous F16 KV (ns20 = dv), which was wrong
when V is read from K with K's row pitch (e.g. 576 vs 512).

New test cases: 576/512 q8_0 (MLA shape, V is a view of K) at kv=113 (KV pad),
nb=1 (vec) and nb=64 (non-vec).

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* test : remove backend-specific wording from test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* pi : avoid backend mentions in test-backend-ops comments

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* metal : rename the FA dequant_f16 identifiers to kv_f16

Assisted-by: pi:llama.cpp/Qwen3.8-27B

* cont : clean-up

* cont : remove TODO
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