Commit Graph

6507 Commits

Author SHA1 Message Date
Georgi Gerganov
e58174cecb llama : bump max seq limit from 64 to 256 (#15916)
ggml-ci
b6507
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
b6506
2025-09-18 12:33:45 +03:00
Jhen-Jie Hong
e00f3fd8ff metal : avoid call free for non-owned buffer (#16067) b6505 2025-09-18 10:06:48 +03:00
Georgi Gerganov
f2f28380ea metal : handle nil cv during pipeline creation (#16065)
ggml-ci
b6504
2025-09-18 10:03:24 +03:00
Chenguang Li
62c3b645c5 CANN: Remove print (#16044)
Signed-off-by: noemotiovon <757486878@qq.com>
b6503
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>
b6502
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
b6501
2025-09-17 20:38:12 +03:00
Aleksander Grygier
a7a98e0fff SvelteKit-based WebUI (#14839) b6500 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
b6499
2025-09-17 19:18:21 +02:00
Johannes Gäßler
c959b676be CUDA: fix FA occupancy, optimize tile kernel (#15982) b6498 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
b6497
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
b6496
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>
b6494
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>
b6493
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>
b6492
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
b6491
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.
b6490
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.
b6488
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) b6484 2025-09-16 09:54:44 +07:00
Aman Gupta
6d758839ff Add LLaDA-7b-MoE diffusion model (#16003) b6483 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>
b6482
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
Diego Devesa
10d197409b releases : switch to rocWMMA develop branch, add gfx1151 (#15992)
* releases : switch to rocWMMA develop branch, add gfx1151

* remove unused variable ROCM_VERSION
b6480
2025-09-15 23:38:42 +02:00
yael-works
b907255f4b SYCL: Add COUNT_EQUAL operator support (#15991)
* SYCL: Add COUNT_EQUAL operator support (rebased on master)

* SYCL: remove duplicate op_count_equal definition

* tests: remove test_count_equal_typed and use test_count_equal for all cases

* tests: keep only I32 case for COUNT_EQUAL as suggested

* tests: keep only I32 case for COUNT_EQUAL as requested
b6479
2025-09-15 18:51:35 +02:00
Nikolay Popov
28c39da7c6 llama-run: Fix model download on Windows (#15988)
* llama-run: Fix model download on Windows
 * fix SSL error (SSL peer certificate or SSH remote key was not OK)
 * fix program crash on std::filesystem::rename

* llama-run: create a separate method to utilize RAII

* llama-run: handle rename exception
b6478
2025-09-15 11:08:30 +01:00
Aman Gupta
106220562a CUDA: some micro-optimizations in mmf.cuh for mul_mat_id (#15926) b6477 2025-09-15 17:35:11 +08:00
ddh0
a68f31edd7 fix KLD percentile output (#15999)
In `llama-perplexity`, when using `--kl-divergence`, the KL divergence statistics output mistakenly displays the 99th percentile twice. This change fixes that and correctly displays the 90th percentile as originally intended (presumably).
b6476
2025-09-15 09:54:57 +02:00
Sigbjørn Skjæret
b8e09f08b9 model : add grok-2 support (#15539)
* add grok-2 support

* type fix

* type fix

* type fix

* "fix" vocab for invalid sequences

* fix expert tensor mapping and spaces in vocab

* add chat template

* fix norm tensor mapping

* rename layer_out_norm to ffn_post_norm

* ensure ffn_post_norm is mapped

* fix experts merging

* remove erroneous FFN_GATE entry

* concatenate split tensors and add more metadata

* process all expert layers and try cat instead of hstack

* add support for community BPE vocab

* fix expert feed forward length and ffn_down concat

* commit this too

* add ffn_up/gate/down, unsure if sequence is right

* add ffn_gate/down/up to tensor names

* correct residual moe (still not working)

* mess--

* fix embedding scale being applied twice

* add built in chat template

* change beta fast for grok if default value

* remove spm vocab in favor of community bpe vocab

* change attention temp length metadata type to integer

* update attention temp length metadata

* remove comment

* replace M_SQRT2 with std::sqrt(2)

* add yarn metadata, move defaults to hparams
b6475
2025-09-14 23:00:59 +02:00
Sigbjørn Skjæret
6c019cb04e server : only attempt to enable thinking if using jinja (#15967) b6474 2025-09-14 21:17:04 +02:00
Georgi Gerganov
9dcd200d57 metal : remove memory pools (#15966)
* metal : remove mem pool usage

ggml-ci

* metal : remove mem pool implementation

ggml-ci

* metal : take into account the actual allocated memory of the tensor

ggml-ci

* cont : use ggml_backend_buft_get_alloc_size

ggml-ci

* cont : improve, comments

ggml-ci

* cont : add functions for the extra tensor sizes

* metal : add comments

ggml-ci

* metal : implement .get_alloc_size for the rest of the buffer types

ggml-ci

* metal : remove ggml_metal_heap

ggml-ci
b6473
2025-09-14 22:02:32 +03:00
Adam
0fa154e350 rocm.Dockerfile: added gfx1200,gfx1201 architectures to support AMD Radeon RX 9000 series (#15994)
* rocm.Dockerfile: added gfx1200,gfx1201 architectures to support  AMD Radeon RX 9000 series

https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.1/reference/system-requirements.html#rdna-os
states the Radeon RX 9000 series is supported support from Ubuntu 24.04.2, and the dockerfile is using 24.04 which is ROCm 6.4.

This fixed the `ROCm error: invalid device function` I was getting when trying to use the rocm container.
2025-09-14 20:43:54 +02:00
Ruben Ortlam
261e6a20ff Vulkan: Clean up mul_mm shader (#15987)
* vulkan: move mul_mm dequantization steps into a separate file and functions

* improve mul_mm vector load code

* fix debug mode issues and warnings
b6471
2025-09-14 16:56:28 +02:00
lcy
a0e13dcbe5 build: fix the build failures of Windows HIP release job (#15984)
* build: fix the cache keys for Windows HIP release job

Update the cache keys to include the HIP SDK version, preventing the
use of outdated ROCm installation caches.

* build: sync changes from release.yml to build.yml

- Update HIP SDK version to 25.Q3 and ROCm version to 6.4.2
- Update the cache keys to reflect the new versions

* build: remove Windows HIP release for gfx1151
since the current stable rocWMMA does not support gfx1151.
b6470
2025-09-14 07:20:35 -07:00
Georgi Gerganov
a14bd35014 metal : fix kernel requirements (#15983)
* metal : fix kernel requirements

ggml-ci

* cont : fix supports_op

* cont : fix supports_op for ARGMAX
b6469
2025-09-14 15:33:22 +03:00
Radoslav Gerganov
918b26f197 rpc : fix regression when --device is used (#15981)
Fix regression introduced with commit 50f4281a6
2025-09-14 12:28:18 +03:00
Diego Devesa
9ecb884346 releases : update ROCM, add gfx1200, gfx1201, gfx1151 (#15972)
* releases : update ROCM, add gfx1200, gfx1201, gfx1151

* releases : set target to 13.3 for macos-x64

* add hipblaslt.dll to release

* add hipblaslt/library to release
2025-09-14 02:21:59 -07:00
Radoslav Gerganov
d1c6f11f47 doc : update documentation for --tensor-split (#15980)
* doc : update documentation for --tensor-split

* Update tools/main/README.md

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

* Update tools/main/README.md

Co-authored-by: Diego Devesa <slarengh@gmail.com>

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
Co-authored-by: Diego Devesa <slarengh@gmail.com>
2025-09-14 12:10:07 +03:00
Aaron Teo
6380d6a3e7 ggml-zdnn: rm user mapped buffers (#15965)
* ggml-zdnn: rm user mapped buffers

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-zdnn: rm dead code

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-zdnn: attempt to fix missing extra data buffer free

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

---------

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
2025-09-14 13:37:03 +08:00
Jeff Bolz
aa0c461efe vulkan: fix failing dequant shaders (#15862)
* vulkan: fix failing dequant shaders

* add missing const
2025-09-13 17:29:43 +02:00
Jeff Bolz
b9c9c9f789 vulkan: initialize vulkan-hpp to allow using extension function pointers (#15705)
Use this to query register count for shader compiles on NVIDIA. Currently
this is only for performance debug, but it could eventually be used in some
heuristics like split_k.
2025-09-13 17:23:30 +02:00
Diego Devesa
50f4281a6f llama : allow using iGPUs with --device (#15951)
* llama : allow using iGPUs with --device

* mtmd : allow iGPU

* rpc-server : allow iGPU
2025-09-13 16:49:49 +02:00
Georgi Gerganov
55758b00ca metal : refactor kernel loading (#15964)
* metal : refactor bin kernels loading

ggml-ci

* metal : refactor rms kernel loading

ggml-ci

* ci : try to add memory leaks check

ggml-ci

* ci : try to enable memory leak detection for Mac

* cont : seems to be working
2025-09-13 16:24:22 +03:00
Georgi Gerganov
f161463a54 metal : allow ops to run concurrently (#15929)
* metal : run graphs ops concurrently

ggml-ci

* cont : add flags for debugging and disabling concurrency

ggml-ci

* cont : refactor and handle fusing

ggml-ci

* cont : simplify - no need to use GPU address

ggml-ci

* cont : prepare mem ranges for reuse + add ggml-metal-common.cpp

ggml-ci

* cont : avoid redundant keywords in cpp [no ci]

* metal : reorder graph for better concurrency

ggml-ci

* metal : fix race on mem pool buffers

ggml-ci

* cont : add env GGML_METAL_GRAPH_OPTIMIZE_DISABLE

ggml-ci

* cont : refactor, optimize, add comments

ggml-ci

* cont : refactor ggml-metal.m

ggml-ci

* minor : update logs [no ci]
2025-09-13 13:54:28 +03:00
Georgi Gerganov
84d7b2fca1 metal : fix memory leaks (#15962)
ggml-ci
2025-09-13 12:45:04 +03:00
Aaron Teo
40be51152d ggml-zdnn: fix #15414, activate FP16 and BF16 acceleration and incorrect zTensor free (#15839) 2025-09-13 02:39:52 +08:00