Commit Graph

6530 Commits

Author SHA1 Message Date
Georgi Gerganov 28baac9c9f
ci : migrate ggml ci to self-hosted runners (#16116)
* ci : migrate ggml ci to a self-hosted runners

* ci : add T4 runner

* ci : add instructions for adding self-hosted runners

* ci : disable test-backend-ops from debug builds due to slowness

* ci : add AMD V710 runner (vulkan)

* cont : add ROCM workflow

* ci : switch to qwen3 0.6b model

* cont : fix the context size
2025-09-21 16:50:45 +03:00
Giuseppe Scrivano 1eeb523c3e
vulkan: optimize UMA buffer operations and fix driver hangs (#16059)
* vulkan: optimize UMA buffer operations and fix driver hangs

The previous implementation was blocking the GPU for extended periods,
causing the i915 driver to reset the context due to the hangcheck
protection.

[32628.443070] i915 0000:00:02.0: [drm] GPU HANG: ecode 12:1:85dffffb, in llama-server [194114]
[32628.443091] i915 0000:00:02.0: [drm] llama-server[194114] context reset due to GPU hang

* vulkan: implement deferred_memset on UMA

---------

Signed-off-by: Giuseppe Scrivano <gscrivan@redhat.com>
2025-09-21 08:31:55 +02:00
Jeff Bolz 5bb4a3edec
vulkan: fix validation error about VK_PIPELINE_CREATE_CAPTURE_STATISTICS_BIT_KHR (#16086) 2025-09-21 08:23:37 +02:00
Georgi Gerganov 7f766929ca sync : ggml 2025-09-20 13:02:14 +03:00
Daniel Bevenius 405921dcef ggml : introduce semantic versioning (ggml/1336)
* ggml : introduce semantic versioning

This commit introduces semantic versioning for the GGML library.

The motivation for this is that the current versioning, using build
numbers, makes it difficult to track changes and releases for projects
that use ggml.

The release steps are the following:
1. Sync the changes from llama.cpp using sync-llama-am.sh and after the
   PR has been approved and merged move to step 2.
2. Run scripts/release.sh and specify the type of release, major, minor,
   or patch. This script will handle incrementing the version
   (major|minor|patch), create a new commit with the version change,
   create a tag for the version, and prepare for the next development
   iteration.
3. Inspect the commits/tag and push to master. This will trigger the
   github release workflow which is triggered for new tags which will
   then publish a new release on github.

Example usage:
```console
$ ./scripts/release.sh major --dry-run
[dry-run] - No changes will be made

Step 1: Reading current version...
Current version: 0.9.0-dev
New release version: 1.0.0

Step 2: Updating version in ggml/CMakeLists.txt...
  [dry-run] Would update GGML_VERSION_MAJOR to 1
  [dry-run] Would update GGML_VERSION_MINOR to 0
  [dry-run] Would update GGML_VERSION_PATCH to 0
  [dry-run] Would remove -dev suffix

Step 3: Committing version bump...
  [dry-run] Would commit: 'ggml : bump version to 1.0.0'

Step 4: Creating git tag...
  [dry-run] Would create tag: v1.0.0 with message 'Release version 1.0.0'

Step 5: Preparing for next development cycle...
  [dry-run] Would update GGML_VERSION_MINOR to 1
  [dry-run] Would add -dev suffix back

Step 6: Committing development version...
  [dry-run] Would commit: 'ggml : prepare for development of 1.1.0-dev'

[dry-run] Summary (no changes were made):
  • Would have released version: 1.0.0
  • Would have created tag: v1.0.0
  • Would have set next development version: 1.1.0-dev
```

Refs: https://github.com/ggml-org/ggml/issues/1333

* ggml: create branch for release candidate and check master

* ggml : sign the git tag
2025-09-20 13:02:14 +03:00
Gregor Jasny fa6383ca7e CUDA : conditionally add cuda architectures (ggml/1341) 2025-09-20 13:02:14 +03:00
Ruben Ortlam 803dac2e48
vulkan: use vec dot for matrix matrix multiplications (#16056)
* vulkan: Change the mul_mm shared memory and register caching system to use vec2 instead of scalars, to enable using dot2 instructions

* use fma instead of dot to fix Nvidia and Apple performance issues
2025-09-20 10:42:56 +02:00
Benni 459c0c2c1a
server: fix SSE and OpenAI compatibility for error messages when streaming (#16109)
* server: fix SSE and OpenAI compatibility for error messages when streaming

* server: remove obsolete event parameter and use required data fieldname instead
2025-09-20 07:56:30 +02:00
ssweens be79d9fdd9
llama-bench: add --devices and --list-devices support (#16039)
* * llama-bench: add --devices support
- Support --devices same as llama-server
- Provide for benchmarking different device combinations
- Include --list-devices like llama-server for convenience

* fix: field display ordering restored

* fix: integrated the rpc devices
- aimed to mimic the server as much as possible

* cleanup: defaults for list-devices
- handle dup device listing with RPC

* cleanup: remove dup device load calls

* docs: update llama-bench
- added the recently added n-cpu-moe option to the docs while in there

* llama-bench: rpc device simplification
* rpc servers unify with other devices earlier, simplifying code
* --list-devices made stateless and simpler
* various cleanup
2025-09-20 00:15:21 +02:00
shun095 f432d8d83e
chat: Fix streaming parser for granite models (#15682)
* fix(chat): fix streaming parser for granite models

* tests: add test cases for Granite models chat parser
2025-09-19 09:57:30 -06:00
Aleksander Grygier 4067f07fc5
feat: Improve mobile UI for Settings Dialog (#16084)
* feat: Improve mobile UI for Settings Dialog

* chore: update webui build output

* fix: Linting errors

* chore: update webui build output
2025-09-19 09:52:27 +02:00
Xuan-Son Nguyen 4b8560ab56
chat : fix build on arm64 (#16101) 2025-09-19 13:02:51 +07:00
Xuan-Son Nguyen 0dd58b6877
ggml : refactor forward_dup for cpu backend (#16062)
* ggml : refactor forward_dup for cpu backend

* clean up a bit

* add quant/dequant perf test
2025-09-19 06:31:56 +02:00
Adrien Gallouët 69ffd89163
ggml-amx : fix ggml_amx_init() on generic Linux (#16049)
Generalize Linux check to `__linux__` to support non-glibc systems (like musl).
Also, return `false` on unknown/untested OS.

Without this commit, the code compiles (with warnings) but fails:

    register_backend: registered backend CPU (1 devices)
    register_device: registered device CPU (Intel(R) Xeon(R) Platinum 8488C)
    build: 6487 (51c4cac6) with x86_64-linux-musl-gcc (GCC) 15.1.0 for x86_64-linux-musl (debug)
    system info: n_threads = 8, n_threads_batch = 8, total_threads = 16
    ....
    print_info: n_ctx_orig_yarn  = 262144
    print_info: rope_finetuned   = unknown
    print_info: model type       = 4B
    Illegal instruction (core dumped)

Signed-off-by: Adrien Gallouët <angt@huggingface.co>
2025-09-18 23:07:26 +02:00
Adrien Gallouët 246c0d9c79
cmake : fix static linking for OpenMP on Unix-like systems (#16031)
When compiling with GGML_STATIC=ON, the build process would produce a
binary that was still dynamically linked to OpenMP. This defeats the
purpose of a static build:

    $ cmake -B build \
            -DBUILD_SHARED_LIBS=OFF \
            -DLLAMA_CURL=OFF \
            -DGGML_CCACHE=OFF \
            -DGGML_NATIVE=OFF \
            -DGGML_STATIC=ON

    $ ldd llama-server
            linux-vdso.so.1 (0x0000e1a434e3b000)
            libgomp.so.1 => /lib/aarch64-linux-gnu/libgomp.so.1 (0x0000e1a4345a0000)
            libstdc++.so.6 => /lib/aarch64-linux-gnu/libstdc++.so.6 (0x0000e1a434300000)
            libm.so.6 => /lib/aarch64-linux-gnu/libm.so.6 (0x0000e1a434240000)
            libgcc_s.so.1 => /lib/aarch64-linux-gnu/libgcc_s.so.1 (0x0000e1a434200000)
            libc.so.6 => /lib/aarch64-linux-gnu/libc.so.6 (0x0000e1a434030000)
            /lib/ld-linux-aarch64.so.1 (0x0000e1a434df0000)

This commit resolves the issue by modifying `CMAKE_FIND_LIBRARY_SUFFIXES`
to prioritize `.a` files, forcing CMake to link the static version of
the library.

Signed-off-by: Adrien Gallouët <angt@huggingface.co>
2025-09-18 23:07:18 +02:00
Shawn Gu 3edd87cd05
opencl: optimize mxfp4 kernels (#16037)
- flatten mxfp4 and packed fp4->fp16 bit-wise convert function (replace lut)
- MoE kernel optimizations

---------

Co-authored-by: Li He <lih@qti.qualcomm.com>
2025-09-18 12:03:34 -07:00
Jeff Bolz c0b45097c3
rename optimize_graph to graph_optimize (#16082) 2025-09-18 13:46:17 -05:00
Bowen Han 38dbdf4c05
CUDA: Optimize PAD_REFLECT_1D (#15957)
* CUDA: Optimize PAD_REFLECT_1D
feat: add more test cases for PAD_REFLECT_1D

* use fast_div to improve performance

* Apply suggestion from JohannesGaessler

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Apply suggestion from JohannesGaessler

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* optimize

* use a concise expression to further speedup the cuda kernel

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2025-09-18 20:26:03 +02:00
Johannes Gäßler 368560a1e3
CUDA: fix compilation on CC 6.0 (#16091) 2025-09-18 19:28:32 +02:00
Eric Curtin 4ca088b036
Add resumable downloads for llama-server model loading (#15963)
- Implement resumable downloads in common_download_file_single function
- Add detection of partial download files (.downloadInProgress)
- Check server support for HTTP Range requests via Accept-Ranges header
- Implement HTTP Range request with "bytes=<start>-" header
- Open files in append mode when resuming vs create mode for new downloads

Signed-off-by: Eric Curtin <eric.curtin@docker.com>
2025-09-18 16:22:50 +01:00
Georgi Gerganov 703f9e32c4
metal : use function constants for mul_mv_ext kernels (#16074)
* metal : use function constants for mul_mv_ext kernels

ggml-ci

* metal : remove NW template argument

ggml-ci

* metal : adjust constants

ggml-ci
2025-09-18 16:28:41 +03:00
Sigbjørn Skjæret ad6bd9083b
cuda : add missing F32<->I32 entries in ggml_cuda_cpy_fn (#16060) 2025-09-18 13:28:22 +02:00
Radoslav Gerganov 2b6b55a59f
server : include usage statistics only when user request them (#16052)
* server : include usage statistics only when user request them

When serving the OpenAI compatible API, we should check if
{"stream_options": {"include_usage": true} is set in the request when
deciding whether we should send usage statistics

closes: #16048

* add unit test
2025-09-18 10:36:57 +00:00
Georgi Gerganov e58174cecb
llama : bump max seq limit from 64 to 256 (#15916)
ggml-ci
2025-09-18 12:47:56 +03:00
Georgi Gerganov b213fce89b
metal : improve F32, F16 and BF16 mat-vec multiplication (#16057)
* metal : improve F32, F16 and BF16 mat-vec multiplication

ggml-ci

* metal : make the NSG a function constant in mul_mv kernels

ggml-ci
2025-09-18 12:33:45 +03:00
Jhen-Jie Hong e00f3fd8ff
metal : avoid call free for non-owned buffer (#16067) 2025-09-18 10:06:48 +03:00
Georgi Gerganov f2f28380ea
metal : handle nil cv during pipeline creation (#16065)
ggml-ci
2025-09-18 10:03:24 +03:00
Chenguang Li 62c3b645c5
CANN: Remove print (#16044)
Signed-off-by: noemotiovon <757486878@qq.com>
2025-09-18 09:26:33 +08:00
Reese Levine d304f459d8
GGML WebGPU: Support for ADD, MUL, RMS_NORM, GET_ROWS operators (#16018)
* Add paramater buffer pool, batching of submissions, refactor command building/submission

* Add header for linux builds

* Free staged parameter buffers at once

* Format with clang-format

* Fix thread-safe implementation

* Use device implicit synchronization

* Update workflow to use custom release

* Remove testing branch workflow

* some f32 tests passing

* Disable set_rows until it's implemented

* f32 add all tests passing

* Begin work on set_rows

* Work on set rows

* Add error buffers for reporting unsupported SET_ROWS indices

* Remove extra comments

* Add templated addition, clean up code

* Get addition and multiplication working

* Implement rms_norm

* Add get_rows implementation

* Add new get_rows files

* Refactor use of wg size entry

* Fix compilation

* Try manually unrolled q4_0 quant

* Revert "Try manually unrolled q4_0 quant"

This reverts commit 77f8b96515.

* Move to constant max wg size

* Check for tensor size in supports_op

* Vectorize f32 and change default workgroup size

* Move f32 get_rows from < 4 to % 4 != 0

* fix linter errors

* Add in-place tests

---------

Co-authored-by: Neha Abbas <nehaabbas@ReeseLevines-MacBook-Pro.local>
2025-09-17 13:09:40 -07:00
Georgi Gerganov 0320ac5264
metal : refactor + optimize v2 (#15995)
* metal : improve naming

* metal : refactor device

ggml-ci

* cont : props

ggml-ci

* metal : apply ggml_mem_ranges_t

ggml-ci

* metal : remove GGML_METAL_USE_BF16

ggml-ci

* metal : refactor device buffer

ggml-ci

* cont : fix naming

* metal : sync before destroying the backend

ggml-ci

* metal : refactor context

ggml-ci

* metal : migrate ggml-metal.m to ggml-metal.cpp

ggml-ci

* metal : adjust ops API

ggml-ci

* metal : use C++ to store piplienes

ggml-ci

* metal : migrate ops to separate functions

ggml-ci

* metal : add ggml_metal_library_t

ggml-ci

* metal : improve naming

ggml-ci

* metal : cleanp

ggml-ci

* metal : add support for GGML_OP_LOG

ggml-ci

* metal : fix error handling

ggml-ci
2025-09-17 20:38:12 +03:00
Aleksander Grygier a7a98e0fff
SvelteKit-based WebUI (#14839) 2025-09-17 19:29:13 +02:00
Xuan-Son Nguyen 8f8f2274ee
convert : add Llama4ForCausalLM (#16042)
* convert : add Llama4ForCausalLM

* handle swa

* half working version

* fix use_kq_norm

* fix use_kq_norm
2025-09-17 19:18:21 +02:00
Johannes Gäßler c959b676be
CUDA: fix FA occupancy, optimize tile kernel (#15982) 2025-09-17 15:32:42 +02:00
David Ribeiro Alves cd08fc3ecc
common : Fix corrupted memory error on json grammar initialization (#16038)
Initalizing RESERVED_NAME in is_reserved_name() is not thread
safe and leads to corrupted memory when used from multiple threads
as can be seen in the asan trace below. This fixes the initialization
to make it thread-safe.

    #0 0x000100abd018 in std::__1::pair<std::__1::__hash_iterator<std::__1::__hash_node<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, void*>*>, bool> std::__1::__hash_table<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::hash<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::equal_to<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::allocator<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>>::__emplace_unique_key_args<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&>(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&) __hash_table:1565
    #1 0x000100ab0320 in SchemaConverter::visit(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&) json-schema-to-grammar.cpp:802
    #2 0x000100aafc48 in std::__1::__function::__func<build_grammar(std::__1::function<void (common_grammar_builder const&)> const&, common_grammar_options const&)::$_2, std::__1::allocator<build_grammar(std::__1::function<void (common_grammar_builder const&)> const&, common_grammar_options const&)::$_2>, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> (std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)>::operator()(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&) function.h:319
    #3 0x000100a2c938 in std::__1::__function::__func<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0::operator()(common_grammar_builder const&) const::'lambda'(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&), std::__1::allocator<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0::operator()(common_grammar_builder const&) const::'lambda'(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)>, void (nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)>::operator()(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&) function.h:319
    #4 0x000100a139f8 in foreach_function(nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&, std::__1::function<void (nlohmann::json_abi_v3_12_0::basic_json<nlohmann::json_abi_v3_12_0::ordered_map, std::__1::vector, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, bool, long long, unsigned long long, double, std::__1::allocator, nlohmann::json_abi_v3_12_0::adl_serializer, std::__1::vector<unsigned char, std::__1::allocator<unsigned char>>, void> const&)> const&) chat.cpp:762
    #5 0x000100a2a7f4 in std::__1::__function::__func<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0, std::__1::allocator<common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool)::$_0>, void (common_grammar_builder const&)>::operator()(common_grammar_builder const&) function.h:319
    #6 0x000100aa98f4 in build_grammar(std::__1::function<void (common_grammar_builder const&)> const&, common_grammar_options const&) json-schema-to-grammar.cpp:982
    #7 0x0001009c9314 in common_chat_params_init_llama_3_x(minja::chat_template const&, templates_params const&, bool) chat.cpp:1110
    #8 0x0001009b8afc in common_chat_templates_apply_jinja(common_chat_templates const*, common_chat_templates_inputs const&) chat.cpp:1992
    #9 0x0001009b533c in common_chat_templates_apply(common_chat_templates const*, common_chat_templates_inputs const&) chat.cpp:2074
    #10 0x000100810120 in llamacpp_apply_chat_template+0x724 (predict_oai-98384e17fb94e863:arm64+0x100090120)
    ...

==45482==Register values:
 x[0] = 0x00006020004147f8   x[1] = 0x00006080000013c8   x[2] = 0x0000000000000000   x[3] = 0x0000604006289738
 x[4] = 0x0000000000000002   x[5] = 0x0000000000000001   x[6] = 0x04034000004b4000   x[7] = 0x0000000000000001
 x[8] = 0xbebebebebebebebe   x[9] = 0x17d7d7d7d7d7d7d7  x[10] = 0x00000c04000828ff  x[11] = 0x0000000000000001
x[12] = 0x000000002018d383  x[13] = 0x0000000000000000  x[14] = 0xfa0000000000fafa  x[15] = 0x000010700001ffff
x[16] = 0x000000019dc012c0  x[17] = 0x00000001021284f8  x[18] = 0x0000000000000000  x[19] = 0x00000001700acdc0
x[20] = 0x0000000000000002  x[21] = 0x000000002018d384  x[22] = 0x16dd16fd2e731151  x[23] = 0x0000007000020000
x[24] = 0x0000000100c69c08  x[25] = 0x0000000100c69c20  x[26] = 0x00006080000013c7  x[27] = 0x0000000100c69c00
x[28] = 0x00000001700acd60     fp = 0x00000001700aceb0     lr = 0x0000000100abce30     sp = 0x00000001700acd60
AddressSanitizer can not provide additional info.
SUMMARY: AddressSanitizer: SEGV __hash_table:1565 in std::__1::pair<std::__1::__hash_iterator<std::__1::__hash_node<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, void*>*>, bool> std::__1::__hash_table<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::hash<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::equal_to<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>, std::__1::allocator<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>>>::__emplace_unique_key_args<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&>(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>> const&)
Thread T5 created by T0 here:
    #0 0x0001020b99d4 in pthread_create+0x5c (libclang_rt.asan_osx_dynamic.dylib:arm64e+0x359d4)
    #1 0x000100873910 in std::sys::pal::unix:🧵:Thread:🆕:h77254fdd87a28e05+0x118 (predict_oai-98384e17fb94e863:arm64+0x1000f3910)
    #2 0x0001007c7a1c in test::run_test::haeb3c2bcd5ed6cf6+0x76c (predict_oai-98384e17fb94e863:arm64+0x100047a1c)
    #3 0x0001007aedb0 in test::console::run_tests_console::he9d142d704f3a986+0x149c (predict_oai-98384e17fb94e863:arm64+0x10002edb0)
    #4 0x0001007c5758 in test::test_main::hf86a5e20735245b9+0x118 (predict_oai-98384e17fb94e863:arm64+0x100045758)
    #5 0x0001007c5da0 in test::test_main_static::h61ee9c8fd30abca0+0x54 (predict_oai-98384e17fb94e863:arm64+0x100045da0)
    ...

==45482==ABORTING
2025-09-17 11:08:02 +03:00
Eve cb5bb6cc05
vulkan: automatically remove unsupported devices (#15976)
* remove unsupported vulkan devices

* make this happen during selection instead

* pass by reference
2025-09-17 09:35:37 +02:00
Daniel Bevenius a91d035b90
ci : revert back to macos-13 for macOS-latest-cmake-x64 (#16040)
This commit reverts the change of the runs-on parameter for the
macOS-latest-cmake-x64 job back to macos-13 that was make in
Commit 51abc96bdc ("ci : update
macos-latest* jobs to use macos-latest (#15938)").

The motivation for this is that using macos-latest will cause an ARM
based runner to be used, and not an x64 based runner.

Refs: https://github.com/ggml-org/llama.cpp/pull/15938#issuecomment-3300805127
2025-09-17 09:34:09 +02:00
Jie Fu (傅杰) 745cbcf2fe
llama-quant : fix the verification of attention layers for encoder-decoder models (#16023)
Signed-off-by: Jie Fu <jiefu@tencent.com>
2025-09-17 09:30:55 +02:00
Jie Fu (傅杰) 1cbd80f8cf
examples : support encoder-decoder models in the simple example (#16002)
Signed-off-by: Jie Fu <jiefu@tencent.com>
2025-09-17 10:29:00 +03:00
Shane A 85286f3548
model : add OLMo3 support (#16015)
* Add HF to gguf conversion logic for Olmo3

* Add Olmo3 implementation

* Update rope comment

* Fix indentation

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

* Apply suggestion from @CISC

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
2025-09-17 09:01:58 +02:00
Chenguang Li d5fabe3682
CANN: Optimize ggml_cann_set_device (#15935)
* CANN: Fix ggml_cann_set_device to avoid redundant device switches

- Added a check to skip aclrtSetDevice if the current device is already set.
- Prevents unnecessary context switches while keeping thread/device consistency.

* CANN: add device default id
2025-09-17 14:33:08 +08:00
jacekpoplawski 8ff206097c
llama-bench: add --n-cpu-moe support (#15952)
* llama-bench: add --n-cpu-moe support

Support --n-cpu-moe in llama-bench the same way it is supported by
llama-server.
2025-09-16 16:17:08 +02:00
Daniel Bevenius 77475530b8
ci : use macos-latest for arm64 webgpu build (#16029)
This commit updates the runs-on field for the macOS arm64 webgpu build
job to use macos-latest instead of just latest.

The motivation for this is that this job can wait for a runner to pick
up the job for a very long time, sometimes over 7 hours. This is an
attempt to see if this change can help reduce the wait time.

Refs: https://github.com/ggml-org/llama.cpp/actions/runs/17754163447/job/50454257570?pr=16004
2025-09-16 15:27:52 +02:00
Daniel Bevenius 3913f8730e
ggml : fix padding in timestep embedding kernels (#15932)
* ggml : remove adding extra dim timestep embedding

This commit updates the ggml_timestep_embedding function to no longer
add an extra dimension when the specified dimension is odd.

The motivation for this change is that this introduces an unnecessary
dimension when the dimension is odd, which caused an issue in the
kernels which were not expecting this extra dimension and it resulted in
uninitialized memory for the second to last dimension.

* ggml-cuda : fix padding in timestep embedding kernel

This commit removes the zeroing out of the last dimension now that we
are not adding the extra padding dimension.

* ggml-metal : fix padding in timestep embedding kernel

This commit fixes the zero padding for odd dimensions in
the timestep embedding kernel

* ggml-opencl : fix padding in timestep embedding kernel

This commit fixes the zero padding for odd dimensions in
the timestep embedding kernel.

* ggml-sycl : fix padding in timestep embedding kernel

This commit fixes the zero padding for odd dimensions in
the timestep embedding kernel.

* ggml-vulkan : fix padding in timestep embedding kernel

This commit fixes the zero padding for odd dimensions in
the timestep embedding kernel.

* ggml-cpu : fix padding in timestep embedding function

This commit removes the zeroing out of the last dimension now that we
are not adding the extra padding dimension.
2025-09-16 15:25:57 +02:00
Daniel Bevenius 76888d202e
ci : upload xcframework artifact from ios-xcode-build job (#16010)
This commit updates the github workflows build.yml file to include steps
for uploading and downloading the xcframework artifact. The
macos-latest-swift job now depends on the ios-xcode-build job and
downloads the xcframework artifact produced by it.

The motivation for this changes is that it takes a long time to build
the xcframework and we are currently doing this twice in the workflow.
With this change, we only build it once and reuse the artifact.
2025-09-16 13:41:38 +02:00
Bowen Han f1fbffb5c0
fix: apply clang-format to CUDA macros (#16017)
clang-format previously broke long CUDA macros (e.g. __launch_bounds__) into
unreadable line breaks inside template declarations, such as:

  template<int D, int ncols, int nwarps, int VKQ_stride,
           typename KQ_acc_t, bool use_logit_softcap>
      __launch_bounds__(nwarps*ggml_cuda_get_physical_warp_size(), 1)

This change adjusts formatting rules so that CUDA macros remain consistent
and aligned with the surrounding template syntax.
2025-09-16 08:59:19 +02:00
Daniel Bevenius 51abc96bdc
ci : update macos-latest* jobs to use macos-latest (#15938)
* ci : update macos-latest* jobs to use macos-latest

This commit updates the jobs that are named macos-latest* to use the
macos-latest label instead explicit versions.

The motivation for this is that there is currently a mixuture of
versions in this workflow and there are jobs that are failing because
they require a newer version.

Refs: https://github.com/ggml-org/llama.cpp/actions/runs/17644792595/job/50140010907#step:5:1759

* ci : add xcodebuild -downloadPlatform iOS command
2025-09-16 05:57:16 +02:00
Yuri Khrustalev 07808ebb07
cmake : Do not install tools on iOS targets (#15903) 2025-09-16 09:54:44 +07:00
Aman Gupta 6d758839ff
Add LLaDA-7b-MoE diffusion model (#16003) 2025-09-16 10:38:28 +08:00
Jake Karnes 3d4053f77f
CUDA: fix im2col_3d to respect non-contiguous inputs (views) (#15956)
* fix im2col_3d to respect non-contiguous inputs (views)

The CUDA 3D im2col kernel computed source addresses assuming compact layout (products of dims), ignoring nb[] strides. 

This patch switches im2col_3d source indexing to use true strides derived from src1->nb[] (in elements), mirroring the approach used in the 2D CUDA im2col path. Destination indexing is unchanged.

* use ggml_element_size() for src strides

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2025-09-16 00:28:31 +02:00
Diego Devesa dc381aa9a6
docker : enable rocWMMA in ROCm images, add gfx1151 (#15997) 2025-09-15 23:38:52 +02:00