1. 14 Oct, 2025 1 commit
    • Thomas Stocker's avatar
      Vulkan based on #9650 (#11835) · 2aba569a
      Thomas Stocker authored
      * implement the vulkan C backend
      
      * add support in gpu.go
      
      * add support in gen_linux.sh
      
      * it builds
      
      * fix segfault
      
      * fix compilation
      
      * fix free memory monitor
      
      * fix total memory monitor
      
      * update gpu.go
      
      * fix build
      
      * fix check_perfmon len
      
      * remove cap_get_bound check
      
      * fix vulkan handle releasing
      
      * fix build on federa 40
      
      * fix vulkan on windows
      
      * making amdgpu work on arm achitecutre with vulkan
      
      * add x86_64 lines in VulkanGlobs and capLinuxGlobs
      
      * add aarch64 lines in vulkanGlobs and capLinuxGlobs
      
      * Fix variable name
      
      * Add vulkan build patch from @jmorganca
      
      * Sync vendored ggml to add Vulkan support
      
      * Updated dockerfile
      
      https://github.com/whyvl/ollama-vulkan/issues/7#issuecomment-2660836871
      
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      
      * Installing rocm library
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      
      * This version works well
      
      built based on this: https://github.com/whyvl/ollama-vulkan/issues/7#issuecomment-2660836871
      
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      
      * Applied 00-fix-vulkan-building.patch
      
      Work done by McBane87 here: https://github.com/whyvl/ollama-vulkan/issues/7#issuecomment-2660836871
      
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      
      * Fixed the "detached head" issues
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      
      * Merged in the right direction
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      
      * Merging the latest stable (#2)
      
      * Applied 00-fix-vulkan-building.patch
      
      * Implemented vulkan backend based on the work done by whyvl, Dts0, McBane87 and others
      
      Tested on AMD Ryzen 7 8845HS w/ Radeon 780M Graphics with ROCm disabled
      
      ```
      [GIN-debug] POST   /v1/chat/completions      --> github.com/ollama/ollama/server.(*Server).ChatHandler-fm (6 handlers)
      [GIN-debug] POST   /v1/completions           --> github.com/ollama/ollama/server.(*Server).GenerateHandler-fm (6 handlers)
      [GIN-debug] POST   /v1/embeddings            --> github.com/ollama/ollama/server.(*Server).EmbedHandler-fm (6 handlers)
      [GIN-debug] GET    /v1/models                --> github.com/ollama/ollama/server.(*Server).ListHandler-fm (6 handlers)
      [GIN-debug] GET    /v1/models/:model         --> github.com/ollama/ollama/server.(*Server).ShowHandler-fm (6 handlers)
      time=2025-03-11T13:00:40.793Z level=INFO source=gpu.go:199 msg="vulkan: load libvulkan and libcap ok"
      time=2025-03-11T13:00:40.877Z level=INFO source=gpu.go:421 msg="error looking up vulkan GPU memory" error="device is a CPU"
      time=2025-03-11T13:00:40.878Z level=WARN source=amd_linux.go:443 msg="amdgpu detected, but no compatible rocm library found.  Either install rocm v6, or follow manual install instructions at https://github.com/ollama/ollama/blob/main/docs/linux.md#manual-install"
      time=2025-03-11T13:00:40.878Z level=WARN source=amd_linux.go:348 msg="unable to verify rocm library: no suitable rocm found, falling back to CPU"
      time=2025-03-11T13:00:40.879Z level=INFO source=types.go:137 msg="inference compute" id=0 library=vulkan variant="" compute=1.3 driver=1.3 name="AMD Radeon Graphics (RADV GFX1103_R1)" total="15.6 GiB" available="15.6 GiB"
      ```
      
      ```
       # ollama run phi4:14b
      >>> /set verbose
      Set 'verbose' mode.
      >>> how's it going?
      Hello! I'm here to help you with any questions or tasks you have. How can I assist you today? 😊
      
      
      
      total duration:       3.341959745s
      load duration:        18.165612ms
      prompt eval count:    15 token(s)
      prompt eval duration: 475ms
      prompt eval rate:     31.58 tokens/s
      eval count:           26 token(s)
      eval duration:        2.846s
      eval rate:            9.14 tokens/s
      >>>
      ```
      
      * This is no longer needed
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      
      * Fixes SIGSEGV: segmentation violation running gemma3 models on ollama 0.6.0 #21
      
      Patch provided by McBane87 on https://github.com/whyvl/ollama-vulkan/issues/21
      
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      
      * Applied 04-disable-mmap-vulkan.patch
      
      From: https://github.com/whyvl/ollama-vulkan/issues/7#issuecomment-2660836871
      
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      
      * Pulled new upstream code for ggml-bulkan backend
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      
      * Merged latest ollama 0.6.2 and nasrally's Flash Attention patches (#5)
      
      * readme: add Ellama to list of community integrations (#9800)
      
      * readme: add screenpipe to community integrations (#9786)
      
      * Add support for ROCm gfx1151 (#9773)
      
      * conditionally enable parallel pipelines
      
      * sample: make mutations in transforms explicit (#9743)
      
      * updated minP to use early exit making use of sorted tokens
      
      * ml/backend/ggml: allocate memory with malloc when loading model (#9822)
      
      * runner: remove cache prompt flag from ollama runner (#9826)
      
      We do not need to bypass the prompt caching in the ollama runner yet, as
      only embedding models needed to bypass the prompt caching. When embedding
      models are implemented they can skip initializing this cache completely.
      
      * ollamarunner: Check for minBatch of context space when shifting
      
      Models can specify that a group of inputs need to be handled a single
      batch. However, context shifting didn't respect this and could trigger
      a break anyways. In this case, we should instead trigger a context
      shift earlier so that it occurs before the grouped batch.
      
      Note that there still some corner cases:
       - A long prompt that exceeds the context window can get truncated
         in the middle of an image. With the current models, this will
         result in the model not recognizing the image at all, which is
         pretty much the expected result with truncation.
       - The context window is set less than the minimum batch size. The
         only solution to this is to refuse to load the model with these
         settings. However, this can never occur with current models and
         default settings.
      
      Since users are unlikely to run into these scenarios, fixing them is
      left as a follow up.
      
      * Applied latest patches from McBane87
      
      See this for details: https://github.com/whyvl/ollama-vulkan/issues/7#issuecomment-2708820861
      
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      
      * Add ability to enable flash attention on vulkan (#4
      
      )
      
      * discover: add flash attention handling for vulkan
      * envconfig: fix typo in config.go
      
      As part of the process some code was refactored and I added a new field
      FlashAttention to GpuInfo since the previous solution didn't allow for a
      granular check via vulkan extensions. As a side effect, this now allows
      for granular per-device FA support checking in other places
      
      ---------
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      Co-authored-by: default avatarzeo <108888572+zeozeozeo@users.noreply.github.com>
      Co-authored-by: default avatarLouis Beaumont <louis.beaumont@gmail.com>
      Co-authored-by: default avatarDaniel Hiltgen <dhiltgen@users.noreply.github.com>
      Co-authored-by: default avatarMichael Yang <mxyng@pm.me>
      Co-authored-by: default avatarParth Sareen <parth.sareen@ollama.com>
      Co-authored-by: default avatarJeffrey Morgan <jmorganca@gmail.com>
      Co-authored-by: default avatarBruce MacDonald <brucewmacdonald@gmail.com>
      Co-authored-by: default avatarJesse Gross <jesse@ollama.com>
      Co-authored-by: default avatarNikita <50599445+nasrally@users.noreply.github.com>
      
      * Revert Readme changes
      
      * Revert
      
      * Revert changes in amd_linux.go
      
      * Revert changes in amd_linux.go
      
      * Remove flashattention setting gpu.go
      
      * Revert whitespace changes in gpu.go
      
      * Revert changes in transforms_test.go
      
      * Revert changes in runner.go
      
      * Revert changes in Makefile.sync
      
      * Revert some unintented changes in Dockerfile
      
      * Revert vulkan copy changes in Dockerfile
      
      * Update Vulkan Code to de4c07f93783a1a96456a44dc16b9db538ee1618
      
      * Fixed duplicate sync in ggml.go
      
      * Revert changes in ggml.go
      
      * Revert chnages in ggml.go
      
      * enable falsh attention on vulkan
      
      * revert remove parenthesis
      
      * fixed flash attention logic enabling
      
      * vk_check_flash_attention 0 means supported
      
      * Update gpu.go
      
      * Add vulkan to Windows Build script
      
      * Remove commented out code
      
      * Enable Vulkan Flash attention in FlashAttentionSupported
      
      * Fix logging
      
      * Update Vulkan backend to e54d41befcc1575f4c898c5ff4ef43970cead75f
      
      * Removed libcap related code
      
      libcap is not directly related to Vulkan and should be added by its own PR. It adds additional library dependencies for building and also requires users to run setcap or run ollama as root, which is not ideal for easy use
      
      * Fix Unit Test (Add Vulkan Library)
      
      * Add vulkan to TestHomogeneousGPUs
      Test
      
      * vulkan: get GPU ID (ollama v0.11.5)
      Signed-off-by: default avatarXiaodong Ye <xiaodong.ye@mthreads.com>
      
      * disable mmap for vulkan
      
      * Reduce Changes remove TestHomogeneousGPUs (doesn't exist on master)
      
      * Update vulkan version to the version used in llama.cpp
      
      * rename gpu patch to correct number
      
      * added Vulkan API to get correct Device UUID
      
      current UUID from pipelineCacheUUID does not match CUDA
      
      * Fix GPU ID Patch
      
      * Remove Code not in llama.cpp
      
      * modified UUID code inside ggml
      
      * Fix Patch
      
      * Copied minimal definition from vulkan header
      
      * Fix compile error in Mac
      
      Metal is preferred so we're disabling Vulkan for now
      
      * Removed unused code
      
      Fix linter error in CI
      
      * Fix patches apply
      
      * fixing lint error
      
      * Removed unneeded function call
      
      Somehow removing this call fixed the crashing when Vulkan header was removed
      
      * added missing NL
      
      * Fixed missing members in Vulkan header
      
      also added zero clear for some structs
      
      * Fixed wrong structure ID
      
      * Fixed Vulkan header
      
      More aligned with official header definition now
      
      * buildvulkanAsSeperateFunction
      
      * Vulkan on Windows Test
      
      * temporarly comment out gate to run windows task
      
      * use temporarly windows-latest for build
      
      * Commenting out other presets to build vulkan
      
      * reenable cpu
      
      * commenting out error action stop
      
      * temporarly commenting out rocm
      
      * set vulkan path
      
      * comment out cude for faster turnaround
      
      * correct vulkan install
      
      * correct vulkan silent install
      
      * fixed install command
      
      * revert debugging changes (vulkan builds on windows)
      
      * revert windows-latest
      
      * trying to build vulkan for linux
      
      * temporarly disable cuda and rocm
      
      * try again linux build
      
      * fix version
      
      * trying to fix
      
      * trying again
      
      * trying again
      
      * fix version
      
      * fixed vulkan-sdk name
      
      * try again
      
      * trying again
      
      * try without version number
      
      * try again
      
      * add some more extra
      
      * trying to use version 1.4.313
      
      * revert debugging changes
      
      * Filter out already supported gpus
      
      * revert debug code
      
      * Use runners for GPU discovery
      
      This revamps how we discover GPUs in the system by leveraging the Ollama
      runner.  This should eliminate inconsistency between our GPU discovery and the
      runners capabilities at runtime, particularly for cases where we try to filter
      out unsupported GPUs.  Now the runner does that implicitly based on the actual
      device list.  In some cases free VRAM reporting can be unreliable which can
      leaad to scheduling mistakes, so this also includes a patch to leverage more
      reliable VRAM reporting libraries if available.
      
      Automatic workarounds have been removed as only one GPU leveraged this, which
      is now documented. This GPU will soon fall off the support matrix with the next
      ROCm bump.
      
      Additional cleanup of the scheduler and discovery packages can be done in the
      future once we have switched on the new memory management code, and removed
      support for the llama runner.
      
      * timing info for runner
      
      * WIP - wire up Vulkan with the new engine based discovery
      
      Not a complete implementation - free VRAM is better, but not accurate on
      windows
      
      * fix - trust the library paths from discovery when starting runner
      
      * fix index bug
      
      * fix vulkan ids to be underlying
      
      * fix - give bootstrapping more time on slow systems
      
      * Test if Vulkan device is supported
      
      * vk_check_flash_attention is not needed (coompat2 coopmapt and scalar implementation exist)
      
      * Handle GGML_VK_VISIBLE_DEVICES
      
      * ask for supported first
      
      * win: fix CPU query buffer handling
      
      Try in a short loop until we get the size right.
      
      * test: harden integration tests for slow start
      
      If the server takes a while to start up, block
      tests from starting until it's online to avoid
      setting large timeouts in individual test cases.
      
      * gofumpt fix
      
      * fix build
      
      * merge fixes
      
      * merge fixes
      
      * fixed build
      
      * merge fixes
      
      * fixing build
      
      * fixed build
      
      * fixed formatting
      
      * fixed build
      
      * fix vulkan gpu id patch
      
      * sync llama.cpp vulkan code
      
      * update build windows script
      
      * merge fixes
      
      * fix format
      
      * fixed vulkan casing
      
      * handle igpu as gpu
      
      * improve case
      
      * print out unknown library
      
      * rturn Vulkan for vulkan library
      
      * Revert "rturn Vulkan for vulkan library"
      
      This reverts commit 690461a12fd5e93295d174c97edefb2bc33285b1.
      
      * fixed patch number
      
      * return Library Name
      
      * remvoe debug code
      
      * return integrated in vulkan backend
      
      * Return pci Properties
      
      * update patch
      
      * directly get pci proeprties without parsing
      
      * workaround for filtering devices. Correct way is to have a LibraryPosition Parameter in the deviceInfo
      
      * Revert "directly get pci proeprties without parsing"
      
      This reverts commit 8e0624851f5ed7d9f74518f574dfb422e4dd4dc2.
      
      * Set FilteredID for Environment Filtering
      
      * ROCm Library is named ROCm
      
      * revert changes in patch
      
      * Create 0028-vulkan-pci-and-memory.patch
      
      * vulkan memory patch
      
      * casing fix
      
      * Add more pci properties
      
      * Added better memory management
      
      * Added better memory managament
      
      * fixed patch
      
      * Fixed patch
      
      * FilterID creation group by library
      
      * filter out vulkan supported by other gpu
      
      * fixing deviceid compare
      
      * Vulkan Fix FA coopmat1 invalid array indexing
      
      * Use everywhere the same Vulkan Version 1.4.321.1
      
      * Remove unneeded patch
      
      * vulkan update
      
      * sync vulkan glsl files
      
      * only use for vulkan the filteredid (numeric device number)
      
      * simplify code
      
      ---------
      Signed-off-by: default avatarVadim Grinco <vadim@grinco.eu>
      Signed-off-by: default avatarXiaodong Ye <xiaodong.ye@mthreads.com>
      Co-authored-by: default avatarpufferffish <github@bandersnatch.anonaddy.com>
      Co-authored-by: KOISHI KOMEIJI FROM TOUHOU 11 <fuck>
      Co-authored-by: default avatarDSLstandard <qgeneral35@gmail.com>
      Co-authored-by: default avatarpufferffish <me@windtfw.com>
      Co-authored-by: default avataryeongbba <yeongmo.lee@logpresso.com>
      Co-authored-by: default avatartomaThomas <tomathomas@mailbox.org>
      Co-authored-by: default avatarAntoine Viallon <antoine@lesviallon.fr>
      Co-authored-by: default avatarVadim Grinco <vadim@grinco.eu>
      Co-authored-by: default avatarzeo <108888572+zeozeozeo@users.noreply.github.com>
      Co-authored-by: default avatarLouis Beaumont <louis.beaumont@gmail.com>
      Co-authored-by: default avatarDaniel Hiltgen <dhiltgen@users.noreply.github.com>
      Co-authored-by: default avatarMichael Yang <mxyng@pm.me>
      Co-authored-by: default avatarParth Sareen <parth.sareen@ollama.com>
      Co-authored-by: default avatarJeffrey Morgan <jmorganca@gmail.com>
      Co-authored-by: default avatarBruce MacDonald <brucewmacdonald@gmail.com>
      Co-authored-by: default avatarJesse Gross <jesse@ollama.com>
      Co-authored-by: default avatarNikita <50599445+nasrally@users.noreply.github.com>
      Co-authored-by: default avatarMasato Nakasaka <masato.nakasaka@intel.com>
      Co-authored-by: default avatarXiaodong Ye <xiaodong.ye@mthreads.com>
      Co-authored-by: default avatarDaniel Hiltgen <daniel@ollama.com>
      2aba569a
  2. 13 Oct, 2025 1 commit
  3. 02 Oct, 2025 1 commit
    • Daniel Hiltgen's avatar
      Update GGML to b6646 (#12245) · c68f367e
      Daniel Hiltgen authored
      Notable EOLs with this change:
      - MacOS v12 and v13 are no longer supported (v14+ required)
      - AMD gfx900 and gfx906 are no longer supported
      c68f367e
  4. 01 Oct, 2025 1 commit
    • Daniel Hiltgen's avatar
      Use runners for GPU discovery (#12090) · bc8909fb
      Daniel Hiltgen authored
      This revamps how we discover GPUs in the system by leveraging the Ollama
      runner.  This should eliminate inconsistency between our GPU discovery and the
      runners capabilities at runtime, particularly for cases where we try to filter
      out unsupported GPUs.  Now the runner does that implicitly based on the actual
      device list.  In some cases free VRAM reporting can be unreliable which can
      leaad to scheduling mistakes, so this also includes a patch to leverage more
      reliable VRAM reporting libraries if available.
      
      Automatic workarounds have been removed as only one GPU leveraged this, which
      is now documented. This GPU will soon fall off the support matrix with the next
      ROCm bump.
      
      Additional cleanup of the scheduler and discovery packages can be done in the
      future once we have switched on the new memory management code, and removed
      support for the llama runner.
      bc8909fb
  5. 12 Sep, 2025 1 commit
    • tc-mb's avatar
      Fix image cannot be seen with slice image on llama engine · 05309218
      tc-mb authored
      Ollama's recent engine update, llama.cpp, caused all models requiring a slice schema to not display images. As a result, the value of numTokens isn't always the length of the sliced ​​image embed, but rather the end length of the schema. This causes the image embed to not be correctly included during all slice processing.
      05309218
  6. 14 Aug, 2025 2 commits
    • Jesse Gross's avatar
      llm: New memory management · d5a0d8d9
      Jesse Gross authored
      This changes the memory allocation strategy from upfront estimation to
      tracking actual allocations done by the engine and reacting to that. The
      goal is avoid issues caused by both under-estimation (crashing) and
      over-estimation (low performance due to under-utilized GPUs).
      
      It is currently opt-in and can be enabled for models running on the
      Ollama engine by setting OLLAMA_NEW_ESTIMATES=1. Behavior in other
      cases is unchanged and will continue to use the existing estimates.
      d5a0d8d9
    • Michael Yang's avatar
      update vendored llama.cpp and ggml (#11823) · 1a19df1f
      Michael Yang authored
      * TEMPORARY: Update the llama.cpp upstream to my fork's Granite Four branch
      
      This will be redone once my branch is merged upstream in llama.cpp
      
      * feat: Update all patches
      
      There are a number that are no longer needed at all:
      
      - 0003-embeddings: Embeddings entirely overhauled on master
      - 0008-ensure-KV-cache-is-fully-defragmented: KV caching entirely
          overhauled on master
      - 0019-metal-add-mean-kernel-14267: Merged upstream
      - 0020-CUDA-add-mean-operation-14313: Merged upstream
      
      * feat: Sync llama.cpp and ggml
      
      * fix: Update rsync-filter for all moved/new/removed files
      
      * fix: Add files missing from sync
      
      * fix: Update ggml rsync-filter for new ggml-cpu/arch subdirs
      
      * fix: Add ggml files missing from sync
      
      * fix: Narrow llama.cpp rsync-filter to not include mtmd main tool cpp files
      
      * fix: Remove mtmd main cpp files
      
      * fix: Add missing include in sampling_ext.cpp
      
      * fix: Update llama.go to use mtmd instead of clip/llava
      
      * fix: Add patch for mtmd_input_text
      
      * chore: Ignore *.patched in the patch directory
      
      * fix: Fix support for arch-specific ggml-cpu source files with new arrangement
      
      In https://github.com/ggml-org/llama.cpp/pull/13892, all arch-specific
      implementations were split out into a nested tree structure under
      ggml-cpu/arch. This conflicts with standard CGO layout where all
      arch-specific source files are expected to live in the same directory as
      the parent go module and use suffixes based on GOOS and GOARCH. As such,
      there were really two options for getting this to work:
      
      1. Add a patch on top of the GGML sync to rearrange the files to match the
      GO layout convention
      2. Use CGO directives to conditionally include the nested source files in
      the compilation units
      
      This commit does (2) in order to minimize the set of changes needed on top
      of the upstream file layout. To get this to work, there are two key things
      needed:
      
      1. In cpu.go, #cgo directives are added to explicitly set __${GOARCH}__ in
      the preprocessor directives
      2. In arch-impls.c|cpp, use an #ifdef | #elif defined | #endif chain to
      explicitly include the .c|.cpp files for the given architecture from the
      nested directory
      
      * fix: Use mtmd_helper to correctly load the bitmap for the image
      
      * fix: Apply patch for mtmd_text_input
      
      * fix: Add missing stb to llama.cpp rsync-filter
      
      * fix: Add sync'ed stb vendored header
      
      * fix: Use c++17 and include vendor for go wrapper modules
      
      * fix: Update patch 0015 for upstream implementation of uuid
      
      * feat: Bump to the latest tip of the branch
      
      * fix: Update patches for bump
      
      * feat: Bump back to the cenral repo and point at the latest master
      
      This includes granite 4 and a number of other model architectures!
      
      * fix: Revert changes to ggml export GPU UUID patch
      
      * fix: Add patch for GGML_VERSION and GGML_COMMIT constants
      
      * feat: Sync all patched code
      
      * build: Include cmake/common.cmake in ggml sync
      
      * build: Add top-level include for GNUINstallDirs in CMakeLists.txt
      
      This is used to populate CMAKE_INSTALL_BINDIR
      
      * fix: Add a patch to avoid power throttling API on non-msvc windows builds
      
      * fix: Sync patch changes for ggml-cpu.c
      
      * feat: Bump llama.cpp to 4a4f42
      
      This picks up support for Kimi K2 and PLaMO-2
      
      * feat: Sync llama.cpp
      
      * fix: Handle multi-chunk image encodings from mtmd
      
      * fix: Re-number patches after merge with `main`
      
      * feat: Bump to 41e78c in the makefile
      
      * fix: Fix Solar and argsort/copy patches after bump
      
      * fix: Remove Gemma3n CUDA Graphs patch
      
      It was implemented upstream:
      https://github.com/ggml-org/llama.cpp/pull/14741
      
      * feat: Sync llama.cpp / ggml after latest bump
      
      * build: Remove unnecessary CFLAGS definitions in cpu.go
      
      * fix: Remove unnecessary additions in the rsync-filter
      
      * fix: Remove unused vendored code for chat template parsing
      
      * Revert "fix: Remove Gemma3n CUDA Graphs patch"
      
      This reverts commit d724caced3ce21f08924d4b7801f94ce6638f6ea.
      
      * fix: Update 0020 CUDA Graphs for gemma3n to keep both llama.cpp and ollama fixes
      
      https://github.com/ollama/ollama/pull/11195#issuecomment-3137312394
      
      
      
      * fix: Sync ggml-cuda.cu after keeping both style cuda graph fixes for gemma3n
      
      * unwind mxfp4 patch
      
      Prepare to bump ggml with their impl for mxfp4
      
      * bump
      
      * fix windows build error
      
      * Convert tensors at load time
      
      Repack the mxfp4 tensors as ggmls kernels expect them to be.
      
      * convert mlp bf16 to f32
      
      * buffer the conversion better
      
      * reshape earlier
      
      * openai swiglu
      
      * add ids
      
      * split qkv, gate_up
      
      * fix nested alt tags
      
      * fast attention
      
      * remove debug messages
      
      * fix lint
      
      * remove redundant test
      
      * remap values only if source/target are different
      
      * add back i32->i32 copy
      
      * refactor cpu quants
      
      * clean up vendor
      
      * update patch instructions
      
      * clean up patches
      
      * remove webgpu
      
      * update mem
      
      * also handle gpt-oss
      
      * revert convert changes
      
      ---------
      Signed-off-by: default avatarGabe Goodhart <ghart@us.ibm.com>
      Co-authored-by: default avatarGabe Goodhart <ghart@us.ibm.com>
      Co-authored-by: default avatarDaniel Hiltgen <daniel@ollama.com>
      1a19df1f
  7. 23 May, 2025 1 commit
  8. 20 May, 2025 1 commit
  9. 16 May, 2025 1 commit
  10. 14 May, 2025 1 commit
  11. 12 May, 2025 1 commit
  12. 10 May, 2025 1 commit
  13. 08 May, 2025 1 commit
  14. 06 May, 2025 1 commit
    • Daniel Hiltgen's avatar
      Move quantization to new backend (#10363) · 42481045
      Daniel Hiltgen authored
      * Move quantization logic to GGML via new backend
      
      This moves the model aware logic to Go code and calls GGMLs quantization code for model creation.
      
      * Remove "add model quantizations"
      
      This is no longer needed now that quantization is implemented in Go+GGML code directly.
      42481045
  15. 05 May, 2025 2 commits
  16. 24 Apr, 2025 1 commit
  17. 16 Apr, 2025 1 commit
  18. 31 Mar, 2025 1 commit
    • Bruce MacDonald's avatar
      runner: clear cache when shift is not possible (#9433) · 66b25392
      Bruce MacDonald authored
      Clear KV cache when shift operation is not supported by model.
      Added KvCacheCanShift() check to handle models that can't perform cache shifts,
      falling back to full cache clear while preserving logical token history to
      maintain expected behavior when context window fills up.
      66b25392
  19. 10 Mar, 2025 1 commit
  20. 04 Mar, 2025 1 commit
    • Michael Yang's avatar
      ml/backend/ggml: consolidate system info logging · 05a01fde
      Michael Yang authored
      - output backend system info when initializing the backend. this ensures
        this information is always present without needing to be called
        explicitly
      - convert to structured logging
      - enumerate devices rather than backends since devices are ordered
      - track device indices grouped by device name
      05a01fde
  21. 28 Feb, 2025 1 commit
  22. 27 Feb, 2025 2 commits
  23. 06 Feb, 2025 1 commit
  24. 31 Jan, 2025 1 commit
  25. 30 Jan, 2025 1 commit
  26. 29 Jan, 2025 1 commit
    • Michael Yang's avatar
      next build (#8539) · dcfb7a10
      Michael Yang authored
      * add build to .dockerignore
      
      * test: only build one arch
      
      * add build to .gitignore
      
      * fix ccache path
      
      * filter amdgpu targets
      
      * only filter if autodetecting
      
      * Don't clobber gpu list for default runner
      
      This ensures the GPU specific environment variables are set properly
      
      * explicitly set CXX compiler for HIP
      
      * Update build_windows.ps1
      
      This isn't complete, but is close.  Dependencies are missing, and it only builds the "default" preset.
      
      * build: add ollama subdir
      
      * add .git to .dockerignore
      
      * docs: update development.md
      
      * update build_darwin.sh
      
      * remove unused scripts
      
      * llm: add cwd and build/lib/ollama to library paths
      
      * default DYLD_LIBRARY_PATH to LD_LIBRARY_PATH in runner on macOS
      
      * add additional cmake output vars for msvc
      
      * interim edits to make server detection logic work with dll directories like lib/ollama/cuda_v12
      
      * remove unncessary filepath.Dir, cleanup
      
      * add hardware-specific directory to path
      
      * use absolute server path
      
      * build: linux arm
      
      * cmake install...
      dcfb7a10
  27. 08 Jan, 2025 1 commit
  28. 13 Dec, 2024 1 commit
  29. 11 Dec, 2024 2 commits
    • Blake Mizerany's avatar
      llama: preserve field order in user-defined JSON schemas (#8002) · 9039c821
      Blake Mizerany authored
      Previously we decoded and re-encoded JSON schemas during validation,
      which served no purpose since json.RawMessage already validates JSON
      syntax. Worse, the re-encoding lost field ordering from the original
      schema, which affects inference quality during step-by-step reasoning.
      
      While fixing this ordering issue by using json.RawMessage directly,
      testing revealed that schema_to_grammar (from llama.cpp) also fails to
      preserve field order during grammar generation. This appears to be the
      root cause of inference degradation.
      
      This change prevents us from mangling the user's original schema order,
      but we still need to address the ordering issue in schema_to_grammar.
      That will be a separate change.
      
      Updates #7978
      9039c821
    • Jeffrey Morgan's avatar
      527cc978
  30. 10 Dec, 2024 2 commits
    • Daniel Hiltgen's avatar
      Remove unused runner CpuFeatures (#8032) · b9ccb374
      Daniel Hiltgen authored
      The final implementation of #7499 removed dynamic vector requirements
      in favor of a simpler filename based model, and this was left over logic that
      is no longer needed.
      b9ccb374
    • Daniel Hiltgen's avatar
      build: Make target improvements (#7499) · 4879a234
      Daniel Hiltgen authored
      * llama: wire up builtin runner
      
      This adds a new entrypoint into the ollama CLI to run the cgo built runner.
      On Mac arm64, this will have GPU support, but on all other platforms it will
      be the lowest common denominator CPU build.  After we fully transition
      to the new Go runners more tech-debt can be removed and we can stop building
      the "default" runner via make and rely on the builtin always.
      
      * build: Make target improvements
      
      Add a few new targets and help for building locally.
      This also adjusts the runner lookup to favor local builds, then
      runners relative to the executable, and finally payloads.
      
      * Support customized CPU flags for runners
      
      This implements a simplified custom CPU flags pattern for the runners.
      When built without overrides, the runner name contains the vector flag
      we check for (AVX) to ensure we don't try to run on unsupported systems
      and crash.  If the user builds a customized set, we omit the naming
      scheme and don't check for compatibility.  This avoids checking
      requirements at runtime, so that logic has been removed as well.  This
      can be used to build GPU runners with no vector flags, or CPU/GPU
      runners with additional flags (e.g. AVX512) enabled.
      
      * Use relative paths
      
      If the user checks out the repo in a path that contains spaces, make gets
      really confused so use relative paths for everything in-repo to avoid breakage.
      
      * Remove payloads from main binary
      
      * install: clean up prior libraries
      
      This removes support for v0.3.6 and older versions (before the tar bundle)
      and ensures we clean up prior libraries before extracting the bundle(s).
      Without this change, runners and dependent libraries could leak when we
      update and lead to subtle runtime errors.
      4879a234
  31. 05 Dec, 2024 1 commit
  32. 03 Dec, 2024 1 commit
  33. 20 Nov, 2024 1 commit
    • Jesse Gross's avatar
      runner.go: Retry decoding after defragmentation if needed · 7121dfa3
      Jesse Gross authored
      Fragmentation of the KV cache can occur due to cache shifting or
      different sequences getting processed. Decode uses a heuristic to
      decide if it should defrag. However, this heuristic isn't 100%
      accurate, so decoding can sometimes fail by surprise.
      
      For these cases, if decode indicates that there is no KV cache space,
      we should defrag and then try again.
      7121dfa3
  34. 19 Nov, 2024 1 commit
  35. 14 Nov, 2024 1 commit