* tests : add README for updating the per-backend fusion baselines
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* ci : trigger fusion on changes to test-llama-archs.cpp and src/models
the dummy models and their architectures drive the fusion baselines, so a
change to either can alter the per-fusion counters and should re-run the
fusion job.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* tests : merge the fusion build commands in the README
assisted-by: pi:llama.cpp/Qwen3.8-27B
* pi : require explicit permission before posting PR/issue comments
assisted-by: pi:llama.cpp/Qwen3.8-27B
Disable the ggml-cpu precompiled header and remove the
std::hardware_destructive_interference_size branch from CACHE_LINE_SIZE.
The PCH force-includes ggml-impl.h before ops.h, which pulls in <new>
via <array>/<vector> and defines __cpp_lib_hardware_interference_size.
This makes the C++ kernels use CACHE_LINE_SIZE = 256 (hardware
destructive interference size) while the C work-buffer sizing code in
ggml-cpu.c always uses the fallback 64. The mismatch undersizes the
rope work buffer by (CACHE_LINE_SIZE/4 - 16) * n_threads * 4 bytes,
causing a heap-buffer-overflow that corrupts the heap and later crashes
in ggml_compute_forward_rope_flt.
Disabling the ggml-cpu PCH restores the natural include order so
ops.h is processed before <new>, keeping CACHE_LINE_SIZE consistent.
Removing the std::hardware_destructive_interference_size branch makes
the value deterministic and include-order independent.
ref: https://github.com/ggml-org/llama.cpp/issues/28858
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-Vision-Exp
The workflow's push/pull_request path filters did not include the
ci/run.sh script that all of its jobs execute, so changes to it never
re-triggered the self-hosted CI.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
Move the EditorConfig Checker and Code Style Checker workflows from the
`[self-hosted, fast]` runners to `ubuntu-slim`, which is an established
runner label in the repo.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
- Clamp the -j parallelism to min(nproc, 2) so a single-core runner
uses -j 1 and multi-core runners use at most -j 2, instead of
unconditionally using $(nproc).
- Add a 3600s timeout to both test-backend-ops runs (the high-perf CPU
path and the default path) so a hung test cannot stall CI indefinitely.
- Note a TODO to reduce the timeout to 1800s in the future.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* ci : run test-backend-ops as a dedicated gg test
Run test-backend-ops as a separate gg test in ci/run.sh so it is executed outside ctest. With GG_BUILD_HIGH_PERF it keeps the existing CPU-only invocation (-b CPU); otherwise it runs all available backends without a backend filter.
Remove the dedicated backend-ops workflow and keep test-backend-ops as a built target that is not registered with ctest to avoid duplicate runs.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-Vision-Exp
* ci : run test-backend-ops earlier and enable high-perf on kleidiai
Move the test-backend-ops gg test before test-llama-archs.
Enable GG_BUILD_HIGH_PERF and LLAMA_ARG_THREADS on the Graviton4 KleidiAI job and use the standard self-hosted results/mnt paths.
Add TODO markers for decoupling tests from libllama.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-Vision-Exp
* ci : run test-backend-ops in parallel
Pass -j $(nproc) to test-backend-ops in both high-perf and all-backend modes.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-Vision-Exp
* ci : disable parallel tests for ROCm
* cont : disable parallel tests with MoltenVK
* metal : rework fusion patterns into a single table
All fusable op patterns for the Metal backend are now declared once in a
fusion table (ggml-metal-fuse.cpp) and consumed by both the graph optimizer
(ggml_metal_fuse_max, packing) and the op encoders (ggml_metal_fuse_next,
compute). The two phases share the same pattern table plus ggml_can_fuse_subgraph_ext
for the structural checks, and differ only in the mode used for the pattern
check (STRUCTURAL at optimize time, since tensors are not allocated yet, and
FULL at compute time, including Metal buffer placement). This also protects the
snake activation (MUL + SIN + SQR + MUL + ADD) from being reordered during graph
optimization, which was previously unprotected.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* metal : fix absolute output indices in fusion patterns
ggml_can_fuse_subgraph_ext expects the outputs array to contain absolute graph
node indices (it indexes cgraph->nodes[outputs[i]]), but the fusion table query
was passing a relative index (n_ops - 1). As a result the last node of every
pattern was not recognized as an output and was subjected to the elidable
use-count check, which failed for essentially all fusions. This silently
disabled the norm/MUL fusion and caused a ~5% token-generation regression.
Pass the absolute graph index of the last node instead.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* metal : fuse gated_delta_net with cache cpy
Add GGML_METAL_FUSE_GDN_CACHE to the fusion table: when the gated_delta_net
kernel is followed by a cpy that scatters its recurrent state snapshots into
the KV cache, the kernel writes the snapshots straight into the cache buffer
and the trailing cpy is elided.
The gdn output has other consumers (the attn scores view), so unlike the
elision-chain patterns this is not a simple chain: a 'raw' flag on the fusion
pattern skips the generic chain/shape and ggml_can_fuse_subgraph_ext checks,
making the pattern-specific check callback the sole validator. Packing
(ggml_metal_fuse_max) now matches on the same view-transparent node sequence
that the compute phase uses, so the gdn + cache cpy group is packed along with
any intermediate views and stays adjacent through the reorder.
The fused cpy is a view consumer of the gdn (it writes the cache directly),
so its mem-range is skipped in the encoder; the skip is restricted to CPY
nodes consuming the previous fused node through a view so other fusions are
unaffected.
Add test_gated_delta_net_cache_fusion and register 5 cases.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* metal : drop is_view_consumer mem-range skip
The is_view_consumer skip was carried over from the upstream gated_delta_net
cache-fusion draft, but it is not needed: keeping the elided cpy's mem-range in
the concurrency tracker only ever adds a (conservative) memory barrier at the
fusion point. It can never remove a barrier, so it cannot introduce a race. The
worst case is one spurious barrier per gdn+cache-cpy fusion, which is within
run-to-run noise on Qwen3.5-0.8B Q8_0.
Dropping the check keeps the mem-range loop uniform for all fused groups.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* metal : rename gated_delta_net fused state output args
Rename the fused cache-write kernel argument to match the rest of the kargs:
state_out_stride -> nb_out (and widen it to uint64_t), and the local buffer id
bid_state_out -> bid_out.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* metal : rename raw fusion flag to unsafe
raw did not convey that the flag opts a fusion pattern out of the generic
elision-chain safety net (ggml_can_fuse_subgraph_ext + chain/shape checks).
rename it to 'unsafe' to make explicit that the pattern's check callback is the
sole validator and must re-establish the safety guarantees itself.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* metal : tidy fusion pattern checks and table
- const-correct ggml_metal_fuse_outputs buffer
- annotate unused check-callback parameters
- drop a redundant size_t cast
- align the ops/table initializers and add blank-line separation
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* metal : add generic fusion stats via ad-hoc proc-address API
Add a device-owned fusion context that lets a test tool count how many
times each fusion pattern fires and toggle fusion. It is exposed through
the ad-hoc ggml_backend_reg_get_proc_address mechanism with generic names
so the testing tool is backend-agnostic:
- ggml_backend_fusion_stats_init: start collecting fusion stats; when a
context is created afterwards it registers the labels/counters and
encodes single-threaded (n_cb == 0) so the counters are race-free
- ggml_backend_fusion_stats_reset / _get_stats / _set_enabled
The context lives on the metal device (not on the last backend context),
so counters accumulate across contexts and reads are always consistent.
The enable/disable toggle is initialized from GGML_METAL_FUSION_DISABLE
and can be overridden by the test through set_enabled. Labels are
synthesized from the fuse table via ggml_metal_fuse_label (e.g.
"GATED_DELTA_NET+CPY").
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : add fusion count regression test with per-backend baseline
test-fusion runs every dummy model generated by test-llama-archs on a
single backend (single-threaded encoding, n_cb == 0) with fusion enabled
and disabled, and for each mode (prefill / decode) reports the per-fusion
counters and the NMSE between the fused and unfused logits, plus the NMSE
against a CPU reference.
A fusion pattern that silently stops matching (or fires when it should
not) is caught as a regression by comparing the counters against a
committed per-backend TSV baseline:
- --record writes the golden baseline, --check (default) validates it
- the unfused run doubles as a control: its counters must be all-zero
- NMSE is skipped when it is NaN or the arch is already broken on the
device (e.g. plamo2 on Metal), so the count check is the hard gate
- baseline counts depend only on graph structure, not weights (verified
stable across weight seeds)
- the fusion stats API is resolved through the ad-hoc get_proc_address
mechanism with generic names; a backend that does not export it makes
the test fail with an error
The committed MTL0.tsv baseline covers 110 dummy archs (298 rows).
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : rename fusion api helpers to match stats_init signature
Align the test with the ad-hoc fusion stats API: fusion_stats_init no
longer takes an enable bool (stats are turned on by calling it), so the
proc-address wrappers and typedefs are renamed to the api_* convention.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : rename backend to device in fusion test CLI
The fusion test operates on a compute device (e.g. MTL0), not a backend,
so rename the --backend argument to --device and the backend_name
variable to device_name. Keep "backend" where it refers to the ggml
backend interface (the ad-hoc proc-address mechanism).
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : add --model and --help to fusion test
--model FILE runs the fusion regression test over a single model file
instead of enumerating a --models DIR. --models and --model are mutually
exclusive. Also add a --help/-h option that prints the usage.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : use backend base name for fusion baseline output
The fusion test is invoked with a specific device name (e.g. MTL0), but
its output - the recorded baseline and the header it writes - should be
named after the backend base name (e.g. MTL, via ggml_backend_reg_name),
since the counters depend on the backend, not on the specific device
index. Rename the committed baseline to MTL.tsv.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : run fusion test from ci instead of ctest
The fusion test needs Metal and generates a lot of dummy models, so it
does not belong in the generic ctest suite. Move it to ci/run.sh as
gg_run_test_fusion, gated on GG_BUILD_METAL like
gg_run_test_llama_archs_tensor_split: it generates the dummy models with
test-llama-archs -o and then validates the fusion counts against the
committed baseline. test-fusion.cpp is still built (llama_build) but no
longer registered as a ctest.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : align fusion baseline TSV columns
Pad the TSV fields to fixed widths so the columns line up regardless of
the variable arch and fusion-label lengths, and trim each field on parse
so the padded file is still accepted. Regenerate the committed MTL.tsv
baseline in the padded format (data unchanged, verified identical modulo
padding).
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : widen label column and align fusion TSV header
Give the label column more room (28 chars) and fix the column header
widths so they match the data rows (moe/mode/label), keeping the header
aligned with the values. Regenerate the MTL.tsv baseline in the new
format (data unchanged).
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : switch fusion baseline from TSV to CSV
Use comma-separated values like the rest of the project, keeping the
padded, aligned columns. Split on ',' and trim on parse. Rename the
committed baseline to MTL.csv (data unchanged, verified identical modulo
padding/separator). Update the ci/run.sh check path accordingly.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* cont : rebase + update MTL stats
* tests : avoid graph reallocations for some archs
* metal : tidy fusion debugging context and op init
- simplify the shared fusion debugging context comments
- shorten the ggml_metal_fusion struct comment
- align the ggml_metal_fuse struct fields and comments
- move the fusion parameter of ggml_metal_op_init right after dev
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : dedup fusion baseline into any mode
prefill and decode always produce the same per-graph fusion count, so
store a single row per label with mode = "any" and the per-graph count
instead of two rows. this halves the baseline size and keeps the check
stable.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* ci : move fusion model generation to a separate step
the dummy models generated by test-llama-archs are reused by other tests,
so generate them once in their own step instead of inside test_fusion.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : bump nmse thold
* models : fix plamo2 graph
* tests : remove "skip" logic from test-fusion
* tests : set qwen3tts dummy vocab to codec head size
the dummy qwen3tts model used a vocab of 4096 while the codec head is
3072, so the graph padded the output with -inf which made the NMSE in
test-fusion produce NaN. use the exact codec head size instead so the
padding is not generated at all.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* tests : regen fusion baseline
reflect the plamo2 graph fix, which changed its fusion pattern split
(RMS_NORM+MUL 11->10, RMS_NORM+MUL+ADD 3->4; same total).
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* ci : skip dummy model generation on OpenVINO
test-llama-archs does not build on the OpenVINO platform, so do not try
to generate the dummy models there.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* cont : minor
* tests : enable test-llama-archs on windows
* cont : disable on windows + workaround
* metal : naming nits
* test-fusion : add instructions to update baseline
* context : fix Kimi-K3 graph reserve
* fusion : update MTL
* cont : fix naming
* metal : rework fusion info storage
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-Vision-Exp
* metal : align fusion info API
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-Vision-Exp
* metal : use opaque fusion handle in ad-hoc API
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-Vision-Exp
* ci : move fusion test to dedicated workflow
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-Vision-Exp
* cont : run only on ggml changes
* cont : simplify
* fusion : remove multi-output stuff for now
* ci : fix typo
* metal : support n_kv_max sparse mask hint in flash attention vec kernel
- add kernel_flash_attn_ext_vec_idx: compacts finite mask entries into
a per-row index list (Hillis-Steele scan, one threadgroup per row)
- extend vec FA kernel with optional sparse index gathering (FC slot 5)
- add host-side gate: sparse path when n_kv_max > 0, mask present,
supported head sizes / KV types, n_kv_max <= 4096
- new buffer region extra_idx for the index list
- pipeline getter extended with has_sparse param
- add test cases: head sizes, quant types, nb>1, nr23 variants,
sinks, ALiBi, softcap, permute, v_view_of_k, no-mask fallback
Note: multi-row (nb*nr23[1] > 1) cases still failing - rid mapping
in the store phase needs revisiting for the sparse path.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* metal : fix sparse flash attention row addressing
- kernel_flash_attn_ext_vec_idx: mask param is half* but nb31 is a byte
stride, so the per-row mask offset was scaled by 2x; cast to char*
before applying the byte strides
- kernel_flash_attn_ext_vec: sparse pidx param is char* so the per-row
element offset was under-scaled by sizeof(int); scale it by sizeof(int)
to get the correct byte offset
- fixes the multi-row (nb*nr23[1] > 1) sparse flash attention failures
Assisted-by: pi:llama.cpp/DeepSeek-v4-0731
* cont : use sparse vec FA for prefill
* metal : single-pass flash attention sparse index compaction
The idx kernel previously read the mask row twice: once to count the finite
entries (for the prefix scan) and again to recover their positions. Since the
kernel is memory-bound, this doubled the mask traffic.
Keep the finite positions in a per-thread register array during the count
pass and write them out directly, avoiding the second mask read. A dense
mask with more than NLOCAL finite entries in a slice falls back to re-reading
the mask to write the remaining positions.
Assisted-by: pi:llama.cpp/DeepSeek-v4-0731
* tests : add perf cases for sparse flash attention prefill
Measure the sparse vec FA kernel across KV sizes, n_kv_max hints and batch
sizes. Run with:
./build/bin/test-backend-ops -b MTL0 -o FLASH_ATTN_EXT -p "n_kv_max=[1-9]" perf
Assisted-by: pi:llama.cpp/DeepSeek-v4-0731
* qwen4 : enable sparse attention
* cont : adjust nsg
* cont : sync test-backend-ops
* cont : disable Qwen4 for now
* cont : clean-up + tests
* convert : skip bias_vl tensor in DeepSeek-V4 DSpark conversion
The DFLASH arch does not include FFN_EXP_PROBS_B_VL, so the DSpark
conversion failed when it tried to write the mtmd-only hash routing
tensor ffn.gate.bias_vl. Drop it like the tid2eid tensor; the DFLASH
draft only consumes ffn.gate.bias via FFN_EXP_PROBS_B.
Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-0731
* cont : fix
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
* common, server : enable preserve_reasoning kwarg by default, log its effective state
If the preserve_reasoning chat template kwarg is not specified explicitly
via --reasoning-preserve / --no-reasoning-preserve, it is enabled by
default after argument processing. The server logs the effective state of
the kwarg, warns that it is enabled by default when the template supports
it, and only warns "has no effect" when it was enabled explicitly on a
template that does not support it. Setting the kwarg via
--chat-template-kwargs is deprecated.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* cont : update comment
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
---------
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
Rename the --tensor-read-lazy CLI argument to --lazy-mode, to match the
internal lazy_mode parameter, and add a -lzm shorthand. Sync the READMEs.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
some backends (Metal, SYCL, WebGPU) require additional memory for
fleeting data for certain ops, which is reflected in their
get_alloc_size implementations.
add ggml_backend_op_alloc_size_may_expand() to the backend utils,
listing these ops, and assert in ggml_backend_buft_get_alloc_size
that a backend expanding the alloc size of a compute op only does so
for ops listed in the helper.
use the helper in the RPC backend to decide whether to query the
remote server for the actual alloc size, instead of a hardcoded list.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* metal : add fa-vec tunings for M5
This is a followup contribution to efeda76b94 as requested in https://github.com/ggml-org/llama.cpp/discussions/27668 to add support for additional Apple GPUs. I generated this output using the provided instructions:
```sh
git clone https://github.com/ggml-org/llama.cpp
cd llama.cpp
cmake -B build -DGGML_METAL=ON
cmake --build build --target ggml-metal-tuning -j
./build/bin/ggml-metal-tuning fa-vec --dtype f16,q8_0 > fa_vec_rows.txt 2> fa_vec_sweep.log
```
This ran on a machine with Apple M5.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* metal : add fa-vec tunings for M5 Pro
This adds fa_vec_tuned_table records for Apple M5 Pro to ggml-metal-tuning.cpp.
Contributed by SerayaEryn in https://github.com/ggml-org/llama.cpp/discussions/27668#discussioncomment-18157544 (F16, Q4_0, Q8_0; M5 Pro, 20 GPU cores).
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* metal : add fa-vec tunings for M3 Max
This adds fa_vec_tuned_table records for Apple M3 Max to ggml-metal-tuning.cpp.
Contributed by TeeAaTeeUu in https://github.com/ggml-org/llama.cpp/discussions/27668#discussioncomment-18175220 (F16, Q8_0; M3 Max, MacBook Pro 64GB, low power mode).
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* cont : whitespaces
* tests : run test-save-load-state across all architectures
test-save-load-state previously only ran in ctest against a single
downloaded model (tinyllamas/stories15M), i.e. only the llama arch.
Add a --models DIR mode to test-save-load-state that runs the full
save/load suite over every *.gguf in a directory, reporting a
per-model PASS/FAIL and exiting non-zero if any model fails, and wire
a ctest to run it over all architectures using the existing
generate-models fixture (test-llama-archs). The single-model -m mode
is preserved (still used by ci/run.sh).
Also bump the dummy-model training context in test-llama-archs from
128 to 256 so that the per-sequence context (which is padded up to a
multiple of 256) no longer exceeds n_ctx_train and emits the
"possible training context overflow" warning.
The test is expected to fail until the affected arches are fixed:
deepseek4 (host seq-copy), gemma2/gpt-oss/lfm2 (device seq-copy),
minimax-01 (state load). It aborts at the first arch that crashes.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* tests : match dummy DSA indexer to fused Lightning Indexer kernel
The dummy DSA indexer (deepseek32, glm-dsa, ...) used key_length=64 and head_count=1, so the fused Lightning Indexer op's q tensor was shaped [64, 1, ...]. The Metal fused kernel is fixed to DK=128, NH=64, so it rejected the op and the scheduler fell back to CPU, emitting a 'layer assigned to MTL but Lightning Indexer on CPU' warning. Bump key_length to 128 and the DSA head_count to 64 so the fused op runs on the GPU.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* tests : add --help and document -o in test-llama-archs
Add a --help/-h flag to test-llama-archs and list the existing -o/--out option in the usage text, which was previously missing.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* tests : use 64 indexer heads for deepseek4
deepseek4's indexer head count was set to n_head (8), which does not match the fused Lightning Indexer kernel's fixed NH=64, so the fused op fell back to the CPU backend and emitted a device-mismatch warning. Give it the same fixed 64 as the other indexer archs by dropping it from the n_head ternary (only minimax-m3 keeps n_head, since it does not use the fused Lightning Indexer op).
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* tests : fix dsv4 save-load n_stream mismatch
The dsv4 KV cache keeps per-sequence KV/state streams even in unified mode, so its n_stream equals n_seq_max. The test saved the state in the baseline with n_seq_max=1 but loaded it in the seq-copy tests with n_seq_max=2, so state_read threw an n_stream mismatch. Use n_seq_max=2 in the baseline and state-load tests so the save and load agree.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* context : relax on-device seq-copy chunk alignment
The on-device state seq copy (llama_state_seq_set_data with LLAMA_STATE_SEQ_FLAGS_ON_DEVICE) copied the write-side cpy tensors to the read-side targets 1:1 by index, requiring the writer and reader to emit the same number of chunks in the same order with the same per-chunk sizes. state_write_data chunks per cell-range while state_read_data chunks contiguous-or-per-cell, so the counts diverged for non-contiguous sources (dsv4, SWA) and the copy aborted with "memory buffer mismatch".
All state writers and readers enumerate the same logical data in the same order, differing only in chunking. Copy the flat write-side data into the read-side targets with a byte cursor that walks both tensor lists across their boundaries, so the chunking no longer needs to match. Keep the total-size guard; drop the n_tensors equality check.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* model : fix dangling hparams ref in minimax-01 LA graph input
llm_graph_input_la stored const llama_hparams & hparams, bound to the llm_graph_params temporary in llama_context::process_ubatch. The input object outlives that temporary (it is kept in llm_graph_result::inputs for graph reuse), so set_input() read destroyed stack memory on every graph reuse - test-save-load-state crashed for minimax-01 when the stack region was overwritten (n_layer_all read as 0, abort in llama_hparams::n_head). Store a copy like every other graph input class.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* context : handle "worst case" graph and add TODO
* ci : apply ccache-clear with older/min/dry-run to all ccache jobs
Assisted-by: llama.cpp:DeepSeek-v4-Flash-0731
* ci : install gh in ccache-clear if missing (container jobs)
The ccache-clear action relies on the gh CLI, which is not present in
container-based jobs. Install it on demand so those jobs can clear caches.
Assisted-by: llama.cpp:DeepSeek-v4-Flash-0731
* ci : install gh via apt repo in ccache-clear
The install.sh script used previously is no longer served (404). Switch to
the official GitHub CLI apt repository, which is still available.
Assisted-by: llama.cpp:DeepSeek-v4-Flash-0731
* ci : pass --repo to gh cache commands in ccache-clear
In container jobs gh cannot auto-detect the repository from git, so
gh cache list/delete fail with 'failed to run git: not a git repository'.
Pass the repository explicitly via --repo using GITHUB_REPOSITORY.
Assisted-by: llama.cpp:DeepSeek-v4-Flash-0731
* ci : drop -new suffix from vulkan ccache key
The -new suffix was only needed to force a fresh cache. With
ccache-clear now evicting stale caches, the original key can be used
again. The old ccache-vulkan-ubuntu-24.04-arm-new entries still match
the ccache-clear key prefix and are cleaned up automatically.
Assisted-by: llama.cpp:DeepSeek-v4-Flash-0731
* ci : fix ccache-clear date parsing on macOS (BSD date)
macOS ships BSD date, which has no -d option. The older cutoff check
was silently disabled there: 'date: illegal option -- d' errors in the
log and the loop was only stopped by the min limit, risking deletion
of caches not older than the cutoff (e.g. saved by a concurrent job).
Parse the ISO-8601 timestamps with GNU date when available and fall
back to BSD date otherwise (TZ=UTC, fractional seconds dropped).
Assisted-by: llama.cpp:DeepSeek-v4-Flash-0731
* ci : extract ccache-clear logic into scripts/ccache-clear.sh
The composite action now consists of a dedicated step that installs the
GitHub CLI when missing (e.g. in container jobs) and a thin step that
calls the new script. The script follows the make-release-checks.sh
conventions (usage/env header, set -euo pipefail, CLI flags) and only
checks that gh is available. The action inputs are unchanged, so the
workflow steps are untouched.
Assisted-by: llama.cpp:DeepSeek-v4-Flash-0731
* ci : remove unused apple ccaches
* readme : update links
* readme : update maintainer PRs list
Add the new members of the `ggml-org` `maintainers` team to the
author filter of the maintainer PRs link (nikwen, marty1885,
Titaniumtown), keeping the canonical team ordering. The list now
matches the team exactly (35 members).
Assisted-by: pi:llama.cpp/Qwen3.8-27B
Run test-llama-archs with 1 to 4 GGML_METAL_DEVICES, mirroring the
existing CUDA runs, and dispatch the job unconditionally since the
per-backend guards now decide what to run.
Assisted-by: llama.cpp:DeepSeek-v4-Flash-0731
* ci : add older, min and dry-run options to ccache-clear
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* pi : add note about not wrapping lines in PR descriptions
[no ci]
Assisted-by: pi:llama.cpp/Qwen3.8-27B
The 'Create release' step had no id, so steps.create_release.outputs.id
resolved to an empty string in the 'Upload nightly-tag.txt' step. The
uploadReleaseAsset call then hit /releases//assets and failed with HTTP
404 (Unhandled error: HttpError), e.g. run 32513839499.
Add id: create_release to the step; the action already exposes the id
output.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* ci : run ccache-clear as the last step of release jobs
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* update disabled job too to force rebase
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@huggingface.co>
Similar to ggml/scripts/release.sh: validates repo state, creates a
release candidate branch (llama-rc-vX.Y.Z), bumps LLAMA_VERSION_* in
CMakeLists.txt and commits the version bump.
Usage: ./scripts/release.sh [major|minor|patch] [--dry-run]
Assisted-by: pi:llama.cpp/Qwen3.8-27B
As agreed in ggml discussion #1579, the official semver releases now
include a nightly-tag.txt asset containing the tag of the corresponding
nightly release (e.g. b10485). The Web UI assets are published to the
HF bucket under the nightly tag, so this makes them discoverable for
each official release.
- make-release-desc.sh: expose the resolved nightly tag as a
nightly_tag output
- make-release.yml: create nightly-tag.txt from that tag, upload it
as a release asset (skipped on dry-run), mention it in the release
body and in the dry-run summary
Assisted-by: pi:llama.cpp/Qwen3.8-27B
Resolve the TODO in test_flash_attn_ext: the branch that creates V as a
sub-view of K (MLA-based models) was hardcoded for the 576/512 head shapes.
Add a v_is_view_of_k test case parameter (default false) and select the
sub-view branch on it; the existing 576/512 (DeepSeek MLA) cases now pass it
explicitly, so the test coverage is unchanged.
Also add more V-is-sub-view-of-K cases: the 320/256 (Mistral4 MLA) and
192/128 head shapes, and full views with equal head sizes (128/128 F16,
64/64 q8_0).
Assisted-by: pi:llama.cpp/Qwen3.8-27B
The Tensor API mat-mat path of kernel_mul_mm (GGML_METAL_HAS_TENSOR) fed a
static K=32 tile to the matmul2d op on every iteration. On the last, partial
K tile (ne00 % 32 != 0) the src1 slice extends past the K extent of the
tensor, and the op reads those out-of-bounds elements (undefined behavior per
the MSL specification, section 2.22.2). Depending on stale memory contents,
this corrupted the result or produced NaN.
Make the matmul2d op use dynamic_extent for K, and clamp the K extent of both
operand tensor views to the remaining valid K range (min(32, K - loop_k)) per
iteration, so the op reads exactly the valid K range on every iteration
(mirroring the tail handling of the MPP matmul2d examples). On K-aligned
inputs the clamp degenerates to the full 32-wide tile: the only difference
from the static-K op is that the dynamic-K op derives K from the operand
extents and edge-checks the tile against the tensor extents (a handful of
integer ops per iteration).
Add test-backend-ops MUL_MAT cases with K not a multiple of 32 to exercise
the unaligned K path.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* 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: https://github.com/ggml-org/llama.cpp/pull/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
build_attn with the llm_graph_input_attn_k_iswa input was using the cached K
tensor itself as V. Create V as a view of K (the first v_cur->ne[0] elements
of each row), like the other K-only build_attn overloads.
The deepseek4 MTP call site now passes the kv tensor as v_cur.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* xcframework : fix build
* mtmd : remove unused include path
* vendor : use vendor::hash alias target in cmake
CMake reserves "::" in target names for imported/alias targets, so the real
target keeps the name vendor-hash and a vendor::hash ALIAS target is added.
Consumers (mtmd, llama-gguf-hash) now link against the namespaced alias.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* vendor : add cmake targets for all vendored libs with vendor:: aliases
Add INTERFACE targets for the header-only vendor libs (miniaudio, nlohmann,
sheredom, stb) and ALIAS targets named vendor::<lib> for all of them,
including cpp-httplib and hash. Each exposes the vendor/ root so includes
are namespaced, e.g. <nlohmann/json.hpp>.
Consolidate the per-lib add_subdirectory calls into a single
add_subdirectory(vendor), keeping the cpp-httplib gate on LLAMA_BUILD_COMMON.
Consumers (llama-common, mtmd) now link the aliases instead of relying on
raw vendor/ include paths.
hash: consumers now include via "hash/hash.h"; the vendor/hash dir is kept
as a PRIVATE include so the synced upstream sources compile unmodified.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* readme : use foo/bar names in acknowledgements
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* ocd : fix valign
* ci : create pre-release with change log and nightly link in make-release
After pushing the tag, create a pre-release using
ggml-org/action-create-release. The release description is generated by
scripts/make-release-desc.sh: the change log between the current and
previous version (one line per commit), a link to the corresponding
nightly build when it exists, and a note that semantic versioning is
still work in progress.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* cmake : bump version to 0.1.2
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* ci : find the nightly tag by commit in make-release-desc.sh
The nightly release is guaranteed by the release checks to point at HEAD,
so instead of reconstructing its name (commit count, branch, hash) just
pick the b* tag pointing at HEAD. This also drops the RELEASE_BRANCH env
var from the workflow.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* ci : resolve the release commit from the version tag in make-release-desc.sh
The change log and nightly lookup now use the commit the version tag
points at (HEAD when the tag does not exist), instead of always HEAD.
This makes the script usable locally for older versions, e.g.
./scripts/make-release-desc.sh v0.1.1. The tag is resolved to a SHA
first, since --points-at does not peel annotated tags.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* ci : normalize the version argument in make-release-desc.sh
Accept the version with or without the leading v (0.1.1 == v0.1.1) and
reject anything else, instead of silently treating a bare version as a
non-existent tag name.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* cont : clean-up
Add a "Create and push git tag" step to the release job, right before
the "Create release" step. The tag is created with git tag and pushed
with the deploy key already configured by the Clone step, instead of
relying on the Releases API (action-create-release) to create it as a
side effect.
The tag is lightweight, matching all existing b<number> release tags.
The step is idempotent: if the tag already exists (e.g. on a re-run),
creation and push are skipped.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* ci : parallelize platform builds in build-xcframework.sh
The ios-xcode release job builds 7 platform/simulator configurations
sequentially, each with -j $(nproc). Run them with at most 3 concurrent
builds (the release runner has 3 cores), splitting the cores between the
builds (-j 1 each on the runner), so total CPU pressure is unchanged while
the build phase runs about 2.3x faster.
- convert the 7 build blocks into functions (flags unchanged)
- add a run_builds_parallel pool: 3-slot sliding window, per-build logs,
dumps the failing log and aborts on error (background job failures do
not trigger set -e)
- queue the 2-arch builds first so the slower builds occupy the slots early
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* pi : add guideline for comments
* cont : disable 5/7 builds
* ci : make build-xcframework.sh builds configurable via CLI args
The script now takes an optional list of builds to run
(ios-sim ios-device macos visionos visionos-sim tvos-sim tvos-device);
with no arguments it builds all of them, as before. The per-build
lists for the build pool, framework setup, static library combining
and xcframework creation are now driven by a single build_spec
lookup instead of four hardcoded (partially commented-out) lists.
release.yml builds only macos and ios-device to cut the build time.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* ci : allow make-release to target a specific commit
The make-release workflow now accepts an optional 'commit' input. When
set, that commit is checked out and the release checks verify that it
belongs to the branch selected in the "Run workflow" dialog and is not
older than 3 days from the branch tip. The check is part of
make-release-checks.sh (driven by the RELEASE_BRANCH env), so it follows
the same dry-run semantics as the other checks.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* cont : scan latest 100 relase workflow runs
* cont : do not check manually for release.yml success
* metal: add TQ2_0 support
Add support for the GGML_TYPE_TQ2_0 (ternary, 2 bits per element) type in
the Metal backend.
Assisted-by: llama.cpp:DeepSeek-v4-Flash-0731
* cont : optimize mul_mv kernel
- float ops over integer ops
- precalculate sums
- hoist coef out of the inner loop
- contiguous y loads
llama.cpp:DeepSeek-v4-Flash-0731
* Resolve -1 to 1024 instead of ctx-len for samplers
Because of backend-sampling we initialize samplers before the complete
llama_context is there. Therefore, we cannot infer the resolved context
length yet at the time we construct the samplers.
* Shared default of 64 for history-based samplers, remove context_size
Georgi Gerganov