* cleanup: consolidate MXFP type aliases, fix SoA linker bug on 5 platforms
- Add GGML_TYPE_MXFP8 and GGML_TYPE_MXFP6 short aliases (matching
existing GGML_TYPE_MXFP4 pattern) and use short names consistently
throughout the codebase instead of mixing long/short forms.
- Fix missing SoA dequant symbols (dequantize_row_mxfp{4,8,6}_soa_cpu)
on loongarch, powerpc, riscv, s390, and wasm by adding proper aliases
to each arch section in arch-fallback.h. Previously these were only
defined under GGML_CPU_GENERIC, causing linker failures on those
platforms when using MXFP flash attention.
- Remove 10 files from the PR diff:
- 5 arch stub files replaced by arch-fallback.h aliases
- 5 rename-only files (sycl, opencl, repack, llama-quant) reverted
since the GGML_TYPE_MXFP4 compat alias handles them
* cleanup: DRY FP6 unpack, extract mxfp_kv_params + mxfp_dequant_head helper
- FP6 unpack: x86 and ARM SIMD versions now call ggml_mxfp_unpack_fp6x4()
from ggml-common.h instead of duplicating the scalar bit manipulation.
- Extract mxfp_kv_params sub-struct from mxfp_fa_params: the 7 symmetric
K/V fields (dequantize, multihead, soa_elems, qs_per_block,
head_qs_bytes, head_e8m0_offset, blocks_per_head) are now in a reusable
struct accessed as mxfp.k and mxfp.v.
- Add mxfp_dequant_head() helper: replaces 4 instances of the multihead
SoA extraction pattern (2x memcpy + dequant, with multihead/single-head
branching) with a single function call. Future backends get the pattern
for free.
* cleanup: extract mxfp_kv_params_init to DRY the K/V init blocks
The K and V initialization in mxfp_fa_params_init were structurally
identical 10-line blocks differing only by tensor/dimension. Extract
into mxfp_kv_params_init(type, D, nb2, ne2) so future MXFP formats
get the multihead SoA addressing logic automatically.
* cleanup: generic MSE round-trip, replace magic buffer sizes with constants
- Remove mse_error_fp8_e4m3 and mse_error_fp6_e2m3: these were identical
round-trip functions differing only by converter. mxfp_compute_e8m0_mse
now uses to_elem/to_float directly when mse_error is NULL (FP8/FP6).
MXFP4 keeps its custom decision-tree MSE. New formats get MSE for free
by just setting to_elem/to_float in their traits.
- Replace magic 1024/1088 buffer sizes in flash attention with named
constants MXFP_FA_MAX_D and MXFP_FA_SOA_BUF. One place to change if
max head dimension grows.
* cleanup: remove dead AoS vec_dot for MXFP8/MXFP6, unify SoA impls
MXFP8 and MXFP6 are KV-cache-only types that use SoA layout for flash
attention. The AoS vec_dot functions (scalar generic, AVX2, NEON) were
dead code — no matmul path uses them.
Removed:
- ggml_vec_dot_mxfp{8,6}_q8_0 from scalar, x86, ARM, quants.h
- ggml_vec_dot_mxfp_q8_0_impl shared helper
- arch-fallback.h aliases for vec_dot mxfp8/mxfp6 (12 lines)
- vec_dot/vec_dot_type registration in ggml-cpu.c
Also unified SoA quantize/dequant: the separate mxfp8_soa_impl and
mxfp6_soa_impl functions (4 functions, ~80 lines) are replaced by two
generic functions (quantize_row_mxfp_soa_impl, dequantize_row_mxfp_soa_impl)
that use traits->bits_per_elem and traits->qs_per_block to handle both
byte-aligned (FP8) and 6-bit packed (FP6) formats. New MXFP formats
get SoA for free by setting these trait fields.
* cleanup: remove all AoS MXFP8/MXFP6 quantize/dequant — SoA only
MXFP8 and MXFP6 are KV-cache-only types. All quantization and
dequantization goes through the SoA (Struct-of-Arrays) path for flash
attention. The AoS (block_mxfp8/block_mxfp6 struct) implementations
were dead code that should never have been added.
Removed:
- quantize_row_mxfp{8,6}_impl, dequantize_row_mxfp{8,6}_impl
- quantize_row_mxfp{8,6}_ref, dequantize_row_mxfp{8,6}
- quantize_mxfp{8,6} (ggml_quantize_chunk wrappers)
- All declarations from ggml-quants.h and quants.h
- to_float/from_float_ref registrations from ggml.c type traits
- from_float registration from ggml-cpu.c CPU traits
Block struct definitions (block_mxfp8, block_mxfp6) are retained for
sizeof() in type traits and validate_row_data.
* cleanup: fail fast in ggml_quantize_chunk for KV-cache-only types
Add explicit GGML_ABORT for MXFP8/MXFP6 in ggml_quantize_chunk —
these are KV-cache-only types that use SoA layout via from_float_soa.
Attempting AoS quantization through this entry point is a bug.
* misc : prefer ggml-org models in docs and examples
Prefer referring to known-good quantizations under ggml-org rather than
3rd-party uploaders.
* remove accidentally committed file
Add MXFP KV cache quantization for flash attention using Struct-of-Arrays
(SoA) memory layout exclusively. Three MX types: MXFP4 (E2M1), MXFP8
(E4M3), MXFP6 (E2M3), implementing the OCP Microscaling v1.0 spec.
SoA layout stores [qs contiguous][e8m0 contiguous] per row, enabling
aligned memory access patterns for GPU backends. All functions in the
flash attention pipeline — set_rows quantization, Q preprocessing, K/V
dequantization — use SoA end-to-end. The existing AoS block layout
remains for MUL_MAT weight quantization (untouched).
Q preprocessing applies Walsh-Hadamard rotation (block-32) before
quantize/dequant round-trip, distributing outlier energy across the
shared exponent group. This is essential for perplexity:
MXFP8: +0.22 PPL without rotation
MXFP6: +3.34 PPL without rotation
Hadamard is skipped for MLA models (DK != DV) where V is a view of K.
Shared infrastructure in ggml-common.h:
- Block structures (block_mxfp8: 33B, block_mxfp6: 25B per 32 elements)
- E8M0 MSE-optimal scale search with ±1 range
- Canonical element converters (FP8 E4M3/E5M2, FP6 E2M3/E3M2)
- FP6 tight packing (4 six-bit values in 3 bytes, 25% savings)
- IEEE-754 bit reconstruction constants for SIMD backends
- SoA layout macros, portable bit cast, type property queries
CPU implementation:
- Scalar reference + ARM NEON + x86 AVX2 optimized paths
- Both FA paths supported: one_chunk (scalar) and tiled (SIMD GEMM)
- Split-KV path extended for single-query decode
- Generic vec_dot via dequant-to-float for MUL_MAT compatibility
- Arch fallbacks for loongarch, powerpc, riscv, s390, wasm
KV cache integration:
- set_rows writes SoA with optional Hadamard (op_params[0] flag)
- K cache block-aligned to 16 for CUDA cp.async compatibility
- CLI: --cache-type-k/v with short aliases (mxfp4, mxfp6, mxfp8)
Tests:
- Flash attention: all 3 types at D=64/128, mixed K/V (mxfp8+mxfp4)
- SET_ROWS: Hadamard rotation for all types
- SoA-aware test initialization and comparison for MXFP tensors
- Quantize functions coverage for all types
Rename GGML_TYPE_MXFP4 → GGML_TYPE_MXFP4_E2M1 across all backends
(CPU, OpenCL, SYCL) for consistency with the MX type family naming.
* Set C locale for consistent float formatting across all binaries.
* Add C locale setting to all tools binaries
Add std::setlocale(LC_NUMERIC, "C") to all 16 binaries in the tools/
directory to ensure consistent floating-point formatting.
* Apply suggestion from @JohannesGaessler
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* bench : cache llama_context state at depth
* cont : handle failures to restore the old state
* cont : print information when the state is being reused
* implement --no-host to disable host buffer
* fix equal_mparams
* move no-host enumeration order together with other model params
---------
Co-authored-by: slaren <slarengh@gmail.com>
* rpc : add support for multiple devices
Allow rpc-server to expose multiple devices from a single endpoint.
Change RPC protocol to include device identifier where needed.
closes: #15210
* fixes
* use ggml_backend_reg_t
* address review comments
* fix llama-bench backend report
* address review comments, change device naming
* fix cmd order
* * 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
* ggml-backend : add GGML_BACKEND_DEVICE_TYPE_IGPU device type
ggml-backend : add device id to device props
llama : only use iGPU devices if there are no GPU devices
llama : do not use multiple devices from different backends with the same device id
Currently if RPC servers are specified with '--rpc' and there is a local
GPU available (e.g. CUDA), the benchmark will be performed only on the
RPC device(s) but the backend result column will say "CUDA,RPC" which is
incorrect. This patch is adding all local GPU devices and makes
llama-bench consistent with llama-cli.
Add no_warmup parameter to cmd_params struct and command-line parsing to allow users to skip warmup runs before benchmarking.
- Add no_warmup boolean field to cmd_params struct
- Add --no-warmup command-line argument parsing
- Add help text documentation for the new flag
- Wrap existing warmup logic in conditional check
- Maintain full backward compatibility (warmup enabled by default)
Addresses #14224
* llama : deprecate llama_kv_self_ API
ggml-ci
* llama : allow llama_memory_(nullptr)
ggml-ci
* memory : add flag for optional data clear in llama_memory_clear
ggml-ci
* threading: support for GGML_SCHED_PRIO_LOW, update thread info on Windows to avoid throttling
We talked about adding LOW priority for GGML threads in the original threadpool PR.
It might be useful for some cases to avoid contention.
Latest Windows ARM64 releases started parking (offlining) the CPU cores
more aggresively which results in suboptimal performance with n_threads > 4.
To deal with that we now disable Power Throttling for our threads for the NORMAL
and higher priorities.
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* threading: disable SetThreadInfo() calls for older Windows versions
* Update tools/llama-bench/llama-bench.cpp
Co-authored-by: Diego Devesa <slarengh@gmail.com>
---------
Co-authored-by: Diego Devesa <slarengh@gmail.com>
Tim Burke
ddh0
Aaron Teo
SamareshSingh
Julius Tischbein
Ruben Ortlam
o7si
Johannes Gäßler
Vishal Singh
Georgi Gerganov
Gadflyii
Radoslav Gerganov
ssweens
jacekpoplawski
Diego Devesa
Juk Armstrong
R0CKSTAR
bashayer hijji
Max Krasnyansky
David Huang