UPSTREAM PR #16901: Add a setting to display message generation statistics #27
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* feat: Add a setting to include model name used to generate the message * feat: UI improvements * feat: Save model info along with the database message entry creation * chore: Build webui static output
* feat: Improve code block theming * chore: update webui build output * chore: Update webui static build
…onditional rendering for Actions Dropdown for Chat Conversation Items (#16369) * fix: Render Conversation action dialogs as singletons from Chat Sidebar level * chore: update webui build output * fix: Render Actions Dropdown conditionally only when user hovers conversation item + remove unused markup * chore: Update webui static build * fix: Always truncate conversation names * chore: Update webui static build
* common: introduce http.h for httplib-based client This change moves cpp-httplib based URL parsing and client setup into a new header `common/http.h`, and integrates it in `arg.cpp` and `run.cpp`. It is an iteration towards removing libcurl, while intentionally minimizing changes to existing code to guarantee the same behavior when `LLAMA_CURL` is used. Signed-off-by: Adrien Gallouët <[email protected]> * tools : add missing WIN32_LEAN_AND_MEAN Signed-off-by: Adrien Gallouët <[email protected]> --------- Signed-off-by: Adrien Gallouët <[email protected]> Signed-off-by: Adrien Gallouët <[email protected]>
* CI: Properly install rocwmma for hip builds on windows we now windows install rocwmma from ubuntu pacakges * CI: update linux rocm docker build to use rocm 7.0
…16075) * Fix to use hidden_size_per_head * Fix num heads * Fix array * Fix loading weights * Support old GGUF converted by the previous version of llama.cpp * Update src/llama-model.cpp Co-authored-by: Sigbjørn Skjæret <[email protected]> * Move shared parameter definitions to the outside of loop * Not calculating n_embd_head_k,v by n_embd / n_head --------- Co-authored-by: Sigbjørn Skjæret <[email protected]>
…0 (#16221) * HIP: Disable ROCWMMA fatt on CDNA when compiled against ROCWMMA 2.0.0 rocwmma 2.0.0 includes a bug in the code fakeing fp16 accumulation on CDNA * CUDA: Fix volta condition in ggml_cuda_should_use_wmma_fattn
* update oneapi to 2025.2, use deep-learning-essentials to replace base-tool * update to 2025.2 use deeplearn essi to replace base toolkit * add missed dll * add deep learning essentials * add sycl-ls --------- Co-authored-by: Zhang Jianyu <[email protected]>
Signed-off-by: Xiaodong Ye <[email protected]>
* First attempt * No permute during convert (fixes qk tensors), proper norm application. * RoPE = NeoX * Coherence! * Migrate xielu params from tensors to hyperparameters * Simple CUDA kernel * Revert stupid LLM refactorings * Chat template support * configchecker / flake8 errors * Reorder unary.cu * I do conclude that LLMs are, in fact, stupid. * Fix after merge * Final newline * Make xIELU an UNARY_OP * Final newline * Correctly account for parameter shift * Argh. * Update ggml/src/ggml-cpu/unary-ops.cpp Co-authored-by: Georgi Gerganov <[email protected]> * Refactor: remove unused methods, inline and factorize softplus, add const modifiers * Revert CUDA changes, implement xIELU as a separate OP * Pesky newline * Add float2half / half2float for F16 inputs/outputs * CUDA variants, attempt 2 * Actually, attempt 3 * Update ggml/src/ggml-cuda/unary.cu Co-authored-by: Johannes Gäßler <[email protected]> * Missing convert header * Proper formula and reference for xIELU in the comments. * Modify unary-ops.cpp to add the functor-based logic besides the template system to retain optimizations * Apply suggestions from code review Co-authored-by: Sigbjørn Skjæret <[email protected]> * Add tensor mappings for Apertus to global list instead * Fix lazy on scalars * Update ggml/src/ggml-cuda/unary.cu Co-authored-by: Johannes Gäßler <[email protected]> * Add comment about the constraints on positive/negative alpha * Change `softplus` to `ggml_softplus` --------- Co-authored-by: Georgi Gerganov <[email protected]> Co-authored-by: Johannes Gäßler <[email protected]> Co-authored-by: Sigbjørn Skjæret <[email protected]>
* Add inplace softmax * Move rms_norm to split row approach * Update debug for supports_op * clean up debug statements * Update tests/test-backend-ops.cpp Co-authored-by: Georgi Gerganov <[email protected]> --------- Co-authored-by: Georgi Gerganov <[email protected]>
…389) * do not use more threads than physically available * ensure n_threads > 0 Co-authored-by: Jeff Bolz <[email protected]> --------- Co-authored-by: Jeff Bolz <[email protected]>
…rolling (#16356) Use <svelte:window bind:innerHeight> instead of manual resize listener Co-authored-by: Aleksander Grygier <[email protected]>
* fix: Include just the currently active message branches instead of all in chat completions request * chore: Build webui static output * chore: Formatting * chore: update webui build output
…GGML_KQ_MASK_PAD) (#16316)
…quest (#16405) * feat: Capture model name only after first token (streaming) or completed request (non-streaming) * chore: update webui build output * chore: update webui build output
This commit updates the macos-13 runners to macos-15-intel. The motivation for this changes is the macos-13 runners are scheduled to be retired on 2025-12-04. Refs: https://github.blog/changelog/2025-09-19-github-actions-macos-13-runner-image-is-closing-down/
When computing sinks, the cm1 shader was looping r from 0 to Br rather than to rows_per_thread. I must have copied this from the scalar path (where it is correct), and somehow it wasn't causing failures on current drivers.
…6354) * vulkan: Replace uses of maxMemoryAllocationSize and VK_WHOLE_SIZE Replace maxMemoryAllocationSize check with maxBufferSize when creating buffers. The maxMemoryAllocationSize limit is a "soft" limit and allocations can succeed beyond that limit. This allows > 4GB buffers to be allocated on some implementations (e.g. NVIDIA) and tensors this large can be used for im2col and mul_mat. For temporary buffers (prealloc_x/y/etc) check against maxStorageBufferRange. I'm not sure this check is ideal, but we always use these buffers as a single full size binding and the limit may be smaller than maxMemoryAllocationSize or maxBufferSize, so I think this is reasonable. Replace descriptor range uses of VK_WHOLE_SIZE with a manually computed range. The maxStorageBufferRange may be smaller than the maxBufferSize or maxMemoryAllocationSize (and the Vulkan spec warns about this in a note) and it's invalid usage if VK_WHOLE_SIZE computes a range larger than maxStorageBufferRange. With this change, it should be possible to generate videos using wan networks in stable-diffusion.cpp. * vulkan: Add env var GGML_VK_FORCE_MAX_BUFFER_SIZE and use stoull
* fix: resolve message disappearing issue when navigating between regenerated siblings by using current leaf nodes instead of cached sibling IDs * chore: update webui build output * chore: update webui build output
reallocation is needed if a single chunk grows in size, even if total allocation size stays the same or is lower
* initial commit for branch 3 * generalize `swa_checkpoint` to `ctx_checkpoint` this extends `llama-server`'s SWA checkpointing logic to include hybrid/recurrent models such as Jamba, Granite * oops * disable debug prints * keep backwards compat with `--swa-checkpoints` Co-authored-by: Georgi Gerganov <[email protected]> * update prompt re-processing message * fix off-by-one error per GG * keep `seq_rm` log per GG Co-authored-by: Georgi Gerganov <[email protected]> * server : fix checkpoint logic to support recurrent caches * server : cleanup and fixes --------- Co-authored-by: Georgi Gerganov <[email protected]>
* CUDA: add expert reduce kernel * contigous checks, better formatting, use std::vector instead of array * use vector empty instead of size Co-authored-by: Johannes Gäßler <[email protected]> --------- Co-authored-by: Johannes Gäßler <[email protected]>
* CUDA: Volta tensor core support for MMF * more generic checks for hardware support * Update ggml/src/ggml-cuda/mmf.cuh Co-authored-by: Aman Gupta <[email protected]> --------- Co-authored-by: Aman Gupta <[email protected]>
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Access the complete analysis in the LOCI Dashboard Performance Analysis Summary: LLaMA.cpp Critical FunctionsCritical Function Performance StatusCore Inference Functions - No Performance Changes
Memory and Batch Processing Functions - Stable
All critical functions show identical performance metrics between versions, with no modifications detected in the codebase. Key Performance Indicator Impact Analysis1. Tokens Per Second - No ImpactStatus: No changes detected in tokenization/inference functions
Reference Impact: Based on the provided benchmark (ollama://smollm:135m on 12th Gen Intel i7-1255U), a 2 ms increase in 2. Power Consumption - Minimal ChangeImpacted Binary:
Other Binaries: No change
3. Quantization Efficiency - No ImpactStatus: No changes in quantization-related functions
4. Memory Usage - No ImpactStatus: Memory management functions show no performance changes
5. Batch Processing - No ImpactStatus: Batch processing functions maintain identical performance
Performance Degradation Source AnalysisThe observed degradations are limited to C++ standard library functions:
These functions are used in grammar parsing components, not core inference paths. Action ItemsCode-Level Optimizations
Build System Improvements
ConclusionThe performance analysis reveals stable core inference functionality with no impact on critical KPIs. The minimal degradations observed (0.054-0.131%) are isolated to auxiliary grammar parsing components and do not affect the primary inference pipeline. Power consumption shows a negligible improvement, and all tokenization, memory management, and batch processing functions maintain identical performance characteristics. |
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Mirrored from ggml-org/llama.cpp#16901
Close #16179
Added a setting to display generation statistics for each assistant message — tokens/s, amount of tokens in a message and generation time.
New Setting in the General section
Statistics at the bottom of the assistant message