* nit: extract app name into a constant value; remove unused onBackPressed callbacks
* UI: update AppContent to pass in correct navigation callbacks
* nit: polish ModelLoadingScreen UI
* core: throw Exception instead of returning null if model fails to load
* navigation: sink model loading state management from AppContent down into ModelLoadingScreen; pass ModelLoadingMetrics to Benchmark and Conversation screens
* gguf: add GGUF metadata data holder and its corresponding extractor implementation
* core: swap out hardcoded LlamaAndroid library loading
* core: add back OpenMP due to huge perf loss on TG128
* misc: reorg the pkg structure
* misc: rename LlamaAndroid related class to InferenceEngine prefixes
* [WIP] lib: move GgufMetadata into the lib submodule
* lib: expose GgufMetadataReader as interface only
* lib: replace the naive & plain SharedPreferences with DataStore implementation
* lib: hide the internal implementations, only expose a facade and interfaces
* lib: expose Arm features
* di: add a stub TierDetection; provide both actual impl and stub in AppModule
* UI: add visualizer UI for Arm features
* misc: UI polish
* lib: refactored InferenceEngineLoader; added a `NONE` Llama Tier
* UI: support `NONE` Llama Tier in general settings
* lib: optimize engine loader; always perform a fresh detection when cache is null
* remote: add HuggingFaceModelDetails data class
* remote: refine HuggingFaceModel data class
* nit: remove `trendingScore` field from HuggingFace model entities, weird...
* remote: refactor HuggingFaceApiService; implement download feature in HuggingFaceRemoteDataSource
* remote: fix the incorrect parse of HuggingFace's inconsistent & weird JSON response
* UI: scaffold Models Management screen and view model
* UI: implement a dialog UI to show fetched HuggingFace models.
* UI: use a broadcast receiver to listen for download complete events and show local import dialog.
* data: handle network exceptions elegantly
* pkg: restructure `data`'s packages
* data: extract local file info, copy and cleanup logics into LocalFileDataSource
* nit: minor UI patch; add missing comments
* bugfix: tapping "Home" in navigation drawer should simply close it without any navigation action.
* UI: improve autoscroll during token generation
* lib: tested on JFrog Artifactory for Maven publishing
* UI: show RAM warning if model too large
* UI: polish model management screen's error dialog
* util: add more items into the mapping table of ISO 639-1 language code to ISO 3166-1 country code
* llm: properly propagate error to UI upon failing to load selected model
* UI: avoid duplicated calculation of token metrics
* lib: read & validate the magic number from the picked source file before executing the import
* UI: add "Learn More" hyperlinks to Error dialog upon model import failures
* lib: refactor the GgufMetadataReader to take InputStream instead of absolute path as argument
* lib: fix the `SIMD` typo in Tier description
* core: verify model file path is readable
* lib: add UnsupportedArchitectureException for triaged error message
* util: split FormatUtils into multiple utils for better readability
* UI: change benchmark screen from raw markdown to table view
* bugfix: reset preselection upon running the preselected model
* misc: linter issue
* bugfix: fix the malfunctioning monitoring switch
* UI: update Arm features indicator; fix the broken hyperlinks
* UI: add quick action buttons to benchmark screen's result card
* UI: hide share fab after clearing all benchmark results
* UI: fix the model unload dialog message; elevate the model card and hide it by default on Conversation screen;
* UI: hide the stubbing actions in Conversation screen
* UI: add show/hide stats control to conversation screen's assistant message bubble; fix placeholder
* UI: add a info button to explain token metrics
* misc: remove the redundant `Companion` added due to refactoring
* UI: show corresponding system metrics detailed info upon tapping RAM / storage / temperature indicator
* UI: add info button to System Prompt switch; expand the model card by default
* UI: disable tag & language chips; add section headers to explain what they are
* misc: replace top bar indicator's spacer with padding
* UI: merge the Model Selection and Model Management into a unified Models screen
* UI: split the ModelsManagementViewModel from a unified ModelsViewModel due to huge complexity
* UI: add model loading in progress view; polish the empty model info view
* UI: polish the bottom bars and info view when no models found; show loading in progress while fetching models
* build: [BREAKING] bump the versions of libraries and plugins
* UI: fix the breaking build
* UI: add Tooltip on Import FAB for user onboarding
* UI: adds AppPreferences to track user onboarding status
* UI: tracks user's first success on importing a model
* data: add hand crafted rules to filter the models fetched from HuggingFace API
* UI: update app name & about; polish top bars' indicators & buttons
* UI: polish Hugging Face download dialog UI
* UX: implement onboarding tooltips for model import and onboarding
* misc: use sentence case for CTA button labels
* [WIP] UI: add Arm color palette from Philip.Watson3
* UI: address Rojin's UX feedbacks
* UI: address Rojin's UX feedbacks - part 2
* UI: update Arm color palette from Philip.Watson3
* data: make sure fetch preselected models in the same order of their IDs
* UI: fix UI issues in the generic settings screen and navigation drawer
* nit: address Rojin's feedbacks on model import message again
* nit: append `®` to all `Arm` labels
* UI: extract a reusable InfoAlertDialog
* core: support GGML_CPU_ALL_VARIANTS on Android!
* core: restructure Kleidi-Llama library
* core: organizing cmake arguments
* data: sort preselected models according to device's available RAM
* app: update adaptive + themed + legacy icons and app name
* UI: fix the font size auto scaling for ArmFeaturesVisualizer
* core: further improve the performance on native methods
* UI: minor color palette changes; emphasize the bottom bar FABs; fix Settings Screen menu item label
* UI: make more room for assistant message bubble's width
* UI: better usage of tertiary colors to highlight model cards but not for warnings
* UI: fix the layout issue on large font sizes
* lib: support x86-64 by dynamically set Arm related definitions
* lib: replace the factory pattern for deprecated tiered lib loading with single instance pattern
* llama: update the library name in JNI and CMake project
* llama: update the library's package name and namespace
* llama: update the app's package name and namespace
* app: bump ksp version
* app: remove deprecated SystemUIController from accompanist by migrating to EdgeToEdge
* app: extract AppContent from MainActivity to a separate file in ui package
* lib: add File version for GGUF Magic number verification
* lib: perform engine state check inclusively instead of exclusively
* lib: change `LlamaTier` to `ArmCpuTier`
* lib: remove kleidi-llama related namings
* cleanup: remove Arm AI Chat/Playground app source code; replace with the basic sample app from https://github.com/hanyin-arm/Arm-AI-Chat-Sample
Note: the full Google Play version of AI Chat app will be open will be open sourced in another repo soon, therefore didn't go through the trouble of pruning the history using `git filter-repo` here.
* [WIP] doc: update main and Android README docs; add self to code owners
* lib: revert System.load back to System.loadLibrary
* jni: introduce a logging util to filter different logging levels on different build types
* lib: enable app optimization
* doc: replace stub Google Play app URL with the actual link add screenshots; add my GitHub ID to maintainer list
Jeremy Demeule [Mon, 15 Dec 2025 14:14:49 +0000 (15:14 +0100)]
metal: use shared buffers on eGPU (llama/17866)
* metal: use shared buffers on eGPU
With #15906, I noticed on important regression when using metal backend on eGPU.
This commit restore the previous behavior and add an option to force its activation.
Jeff Bolz [Sat, 13 Dec 2025 09:04:29 +0000 (03:04 -0600)]
vulkan: Multi-pass softmax for large number of cols (llama/17892)
When the number of cols is large, split each row across multiple workgroups.
There are three phases that communicate partial results through temp buffers:
(1) compute max partials
(2) take max of partials, compute sum(exp(x-max)) partials
(3) sum partials, compute scaled result
Congcong Cai [Fri, 12 Dec 2025 14:37:38 +0000 (22:37 +0800)]
cmake : set `CMAKE_RUNTIME_OUTPUT_DIRECTORY` for non standalone build (#1394)
Some backend depends on CMAKE_RUNTIME_OUTPUT_DIRECTORY to create temporary file like metal backened.
Missing CMAKE_RUNTIME_OUTPUT_DIRECTORY will cause some cmake error like permission denied (try to copy file to root).
This PR wants to setup a default path for CMAKE_RUNTIME_OUTPUT_DIRECTORY when it does not exist.
Chenguang Li [Tue, 9 Dec 2025 09:53:23 +0000 (17:53 +0800)]
CANN: add support for partial RoPE and Vision mode (llama/17543)
* cann: add support for partial RoPE and Vision mode
Add support for two important RoPE variants: partial rotation (rope_dims < ne0)
and Vision mode rotation.
1. Support for partial RoPE (rope_dims < ne0):
- Split tensor into head (first rope_dims dimensions) and tail portions
- Apply rotation only to head portion using RotaryPositionEmbedding operator
- Copy unrotated tail portion directly from source to destination
- Handle both contiguous and non-contiguous tensor layouts
2. Support for Vision mode (GGML_ROPE_TYPE_VISION):
- Set rope_dims = ne0 for Vision mode to rotate entire tensor
- Vision mode pairs dimension i with dimension i+n_dims (where n_dims = ne0/2)
- No tail handling needed since entire tensor is rotated
Implementation details:
- Use has_tail flag to determine execution path: head/tail splitting when
rope_dims < ne0, or full tensor rotation when rope_dims == ne0
- Support both F32 and F16 data types with intermediate F32 conversion
- Copy non-contiguous tensors to contiguous buffers before calling
RotaryPositionEmbedding operator for compatibility
- Improve cache invalidation logic to include rope_dims and indep_sects
parameters
These enhancements enable CANN backend to handle various RoPE configurations
used in modern vision-language models and models with partial rotation.
wsbagnsv1 [Mon, 8 Dec 2025 09:41:08 +0000 (10:41 +0100)]
cuda: optimize SOLVE_TRI using registers and FMAF (llama/17703)
* ggml-cuda: optimize solve_tri_f32_fast and fix stride handling
- Switch from using shared memory for the RHS/solution matrix to a register-based approach (x_low, x_high), reducing shared memory pressure and bank conflicts.
- Implement explicit `fmaf` instructions for the reduction loop.
- Update kernel arguments to pass strides in bytes rather than elements to align with standard ggml tensor arithmetic (casting to `char *` before addition).
- Remove unused `MAX_K_FAST` definition.
* Small cleanup
* Remove comments in solve_tri.cu
* Update ggml/src/ggml-cuda/solve_tri.cu
Co-authored-by: Johannes Gäßler <redacted>
* Update ggml/src/ggml-cuda/solve_tri.cu
Co-authored-by: Johannes Gäßler <redacted>
* Update ggml/src/ggml-cuda/solve_tri.cu
Co-authored-by: Johannes Gäßler <redacted>
* Use const for variables in solve_tri.cu
Jeff Bolz [Sat, 6 Dec 2025 17:46:46 +0000 (11:46 -0600)]
vulkan: perf_logger improvements (llama/17672)
* vulkan: perf_logger improvements
- Move perf_logger from device to ctx.
- Add an env var to control the frequency we dump the stats. If you set a very
large value, it just dumps when the ctx is destroyed.
- Add a fusion info string to the tracking, only log one item per fused op.
- Fix MUL_MAT_ID flops calculation.
Jeff Bolz [Sat, 6 Dec 2025 10:12:26 +0000 (04:12 -0600)]
vulkan: Use one row per workgroup for f32 mmv (llama/17711)
The MoE models have a mul_mat_vec with very small m (32, 64, 128) right before
the topk_moe selection. Running multiple rows per wg doesn't utilize the SMs
well. I think even for larger m, f32 is so bandwidth-limited that running
multiple rows doesn't help.
Jeff Bolz [Fri, 5 Dec 2025 21:03:19 +0000 (15:03 -0600)]
vulkan: fix top_k bug when there are ties in the input (llama/17659)
* vulkan: Reduce temporary memory usage for TOP_K
- Compute row size for the temp buffer based on the output of the first pass.
- Update shader addressing math to use the output row size
- Pass the output row size as "ncols_output", what used to be "ncols_output" is now "k"
For the common case of K=40 and src0=(200000,1,1,1), this reduces the temporary buffer
from about 3.2MB to 500KB.
* vulkan: fix top_k bug when there are ties in the input
I noticed by inspection a bug in the vulkan top_k shader where if the least
value in the top_k appears multiple times we could end up writing those extra
copies out rather than some larger values (if the larger values are on higher
numbered threads).
I rewrote the test verification to handle this case, where the final index set
is not necessarily the same.
* Update tests/test-backend-ops.cpp
Co-authored-by: Georgi Gerganov <redacted>
---------
The XIELU operation was incorrectly using static_cast to convert
float parameters to uint32_t, which converted numeric values instead
of preserving IEEE 754 bit patterns. This caused incorrect values
to be interpreted by the GPU shader.
* Use reinterpret_cast to preserve float bit patterns when passing
through uint32_t params buffer
* Update WGSL shader parameter types from u32 to f32
* Re-enable XIELU support (was disabled due to numerical issues)
Fixes NMSE test failures for XIELU operation on WebGPU backend.
neg f16xf32xip builds and runs, havent actually ran a model that uses neg kernel yet though
Co-authored-by: James Contini <redacted> Co-authored-by: Neha Abbas <redacted> Co-authored-by: Abhijit Ramesh <redacted>
* Remove extra code and format
Gabe Goodhart [Thu, 4 Dec 2025 17:12:19 +0000 (10:12 -0700)]
metal: TRI, FILL, EXPM1, SOFTPLUS (llama/16623)
* feat(wip): Port initial TRI impl from pervious work
The kernel does not work and is not optimized, but the
code compiles and runs, so this will be the starting point
now that the core op has been merged.
Branch: ggml-cumsum-tri
Signed-off-by: Gabe Goodhart <redacted>
* fix: Remove argument for constant val override
This was added in the original draft, but later removed. With this, the
kernel now passes tests.
Branch: ggml-cumsum-tri
Signed-off-by: Gabe Goodhart <redacted>
* feat: Move the ttype conditional to templating to avoid conditional in kernel
Branch: ggml-cumsum-tri
Signed-off-by: Gabe Goodhart <redacted>
* fix: Type fixes
Signed-off-by: Gabe Goodhart <redacted> Co-authored-by: Georgi Gerganov <redacted> Co-authored-by: Georgi Gerganov <redacted>
* feat: Add softplus for metal
Branch: ggml-cumsum-tri
Signed-off-by: Gabe Goodhart <redacted>
* feat: Add EXPM1 for metal
Branch: ggml-cumsum-tri
Signed-off-by: Gabe Goodhart <redacted>
* feat: Add FILL for metal
Branch: ggml-cumsum-tri
Signed-off-by: Gabe Goodhart <redacted>
* refactor: Branchless version of tri using _ggml_vec_tri_cmp as a mask
Branch: ggml-cumsum-tri
Signed-off-by: Gabe Goodhart <redacted>
* fix: Remove unused arguments
Branch: ggml-cumsum-tri
Signed-off-by: Gabe Goodhart <redacted>
* refactor: Use select instead of branch for softplus non-vec
Branch: ggml-cumsum-tri
Signed-off-by: Gabe Goodhart <redacted>
---------
Signed-off-by: Gabe Goodhart <redacted> Co-authored-by: Georgi Gerganov <redacted>
Jeff Bolz [Tue, 2 Dec 2025 18:22:04 +0000 (12:22 -0600)]
vulkan: Reduce temporary memory usage for TOP_K (llama/17623)
- Compute row size for the temp buffer based on the output of the first pass.
- Update shader addressing math to use the output row size
- Pass the output row size as "ncols_output", what used to be "ncols_output" is now "k"
For the common case of K=40 and src0=(200000,1,1,1), this reduces the temporary buffer
from about 3.2MB to 500KB.