* model : add LiquidAI/LFM3-Audio-2B and LiquidAI/LFM3-Omni-2B
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Assisted-by: Claude Opus 5.5
* convert : read the LFM3-Audio config.json as released
A transformers that knows lfm3_audio rewrites the config into another layout (no lfm/encoder keys).
Assisted-by: Claude Opus 5.5
* mtmd : disable flash attention for the LFM3-Audio depthformer
Assisted-by: Claude Opus 5.5
* tts : add a voice option for LFM3-Audio and LFM3-Omni
The model card offers a female and a male voice; --tts-voice for llama-tts, "voice" for the server /tts.
Assisted-by: Claude Opus 5.5
* clean up template handling
* convert : detect LFM3-Audio and LFM3-Omni by model_type
Assisted-by: Claude Opus 5.5
* move banned tokens --> logits bias --> mtmd_helper
* leave mtmd-cli unchanged
* no more template_asr_system
* left over
* llama : keep the LFM3-Audio encoder convs and codec unquantized
Assisted-by: Claude Opus 5.5
* common, mtmd : shorten comments
Assisted-by: Claude Opus 5.5
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* server: add --models-memory-max parameter to allow dynamically unloading models when they exceed a memory size threshold
estimate with to-be-loaded model size included
use no_alloc to get memory requirements for model load
only set model memory_mb if not previously calculated
use memory margin instead of total size limit, apply to each device separately
add server memory debug logging
move llama_context_device_memory function to llama-ext.h
fix model count exceeded check
improve memory_per_device map naming
improve variable naming, fix style
also strip models memory margin from child processes
cont : clean-up
replace device memory map with buft memory map. Use llama_get_memory_breakdown
extract duplicated check into helper function
move model memory estimation to subprocess
precompute name->buft map, map GPU host types to CPU buft
cleanup unused variable
remove duplicated init calls
* adapt to upstream changes
* wip
* common_memory_reports internface
* SERVER_ROLE_MEASURE
* server-models-sched
* fix build
* server : fix memory accounting of measure children and claim spin
A measure child runs no_alloc, so the free memory it reports does not
include its estimate: subtracting self there erased the memory held by
other processes, down to zero with --fit on, and the next load could
overshoot the margin. Subtract self only for instance reports.
A queued load only checked --models-max before claiming, so when the
memory margin blocked it behind a busy model, load() threw and the
waiter retried in a tight loop. Refuse the claim while the limits are
exceeded and no idle model can be unloaded, so the waiter sleeps on
the condition variable until one goes idle.
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: Pascal <admin@serveurperso.com>
* init
* wip
* wire it up
* make it clear that it's experimental
* add props.connect_code
* nits
* fix windows build
* server: do not advertise a connect code without the tunnel
--connect-code on its own had no effect other than being served in
/props, so the Web UI showed a remote access code that no tunnel was
serving. Clear it when --connect is off, and say so once at startup.
The teardown comment claimed that terminate() closes the child stdout.
It does not: the log thread leaves fgets() only once every writer of
that pipe is gone, so a descendant of llama-connect would block the
join forever. Describe the real contract instead.
Also restore the --reasoning-preserve default in the generated docs.
* Update tools/connect/CMakeLists.txt
Co-authored-by: Adrien Gallouët <angt@huggingface.co>
* server: dial llama-connect on the bound port and a reachable host
Pass ctx_http.port so --port 0 and the GCP override work, pick the
dial host from --host (wildcards map to loopback, IPv6 is bracketed)
and refuse --connect when only unix sockets are bound.
---------
Co-authored-by: Pascal <admin@serveurperso.com>
Co-authored-by: Adrien Gallouët <angt@huggingface.co>
* server: save only restorable slot states to the prompt cache
The idle-slot save loop stores every idle slot whenever a task starts,
while only completion tasks restore from the prompt cache. Rerank,
embedding, decision and infill states fill the cache up to its limit
without ever being read back, and slots already cached are offered
again at every task start.
Each slot now tracks with cache_pending whether its state is restorable
and missing from the cache: a completion release or an explicit slot
restore sets it, prompt_save consumes it, prompt_clear resets it. Both
save paths share this rule, and the LRU path restores only for
completion tasks.
* server: test that decision slots skip the prompt cache
Decision tasks never mark their slot as cacheable, so starting new
tasks must not save their idle slots to the RAM prompt cache, with or
without a unified KV cache.
* server: restore any reusing task from the prompt cache
Embedding and rerank tasks never reuse their state, so their slots are
cleared on release like child slots and the cache only holds states
that a later task can restore. Infill and decision tasks now restore
from the cache too, which replaces the cache_pending flag.
Decision models disable the prompt cache unless --cache-ram is given,
since their states seldom repeat.
* common : add --spec-draft-n-ubatch
Allow configuring the physical batch size of the draft context. The
drafters feed it at most the drafted tokens per sequence and chunk larger
batches by its own n_ubatch, so it does not need the ubatch of the target.
A smaller value shrinks the draft compute buffer and leaves more VRAM for
the target KV cache (the draft is fitted together with the target).
The default 0 keeps the current behavior of following --n-ubatch.
Assisted-by: pi:llama.cpp/Qwen3.8-Flash-Next
* cont : remove comment
[no ci]
* examples : fix draft sampling and rejection handling
This commit fixes two issues in the speculative example which are
described in detail in the linked issue.
Resolves: https://github.com/ggml-org/llama.cpp/issues/29975
* examples : add kv-unified requirement for parallel > 1
* Make the drafter probabilistic and the target verify by rejection sampling
* Drop stale spec_draft_q before drafting
* Fallback to argmax sampling for grammar-constrained requests and adding flag for enabling probabilistic draft sampling. Default flag value is greedy.
* Support grammar-constrained requests in rejection sampling
* Fix - renormalize distribution after masking
* copy rng on sampler copy and re-accept drafted tokens on replay
* Fix draft sampler sharing the target's rng stream
* Simplify the rejection sampler's inputs and move replay to the server
* Truncate the draft candidates along with the draft
---------
Co-authored-by: praneshgo <227579474+praneshgo@users.noreply.github.com>
Co-authored-by: Pranesh Gonegandla <pgonegandla@nvidia.com>
- register --rpc unconditionally and call llama_supports_rpc() only from its handler
- print server "initialization ..." log after args are parsed
Assisted-by: pi:llama.cpp/MiMo-V2.6-Flash-RL
Allow configuring --temp, --top-p, --min-p, --repeat-penalty,
--presence-penalty and --frequency-penalty via LLAMA_ARG_* so
llama-server can be fully controlled from an EnvironmentFile
(e.g. systemd on Debian).
Use `llama-gen-docs` to regenerate the readme files.
* common, server : enable preserve_reasoning kwarg by default, log its effective state
If the preserve_reasoning chat template kwarg is not specified explicitly
via --reasoning-preserve / --no-reasoning-preserve, it is enabled by
default after argument processing. The server logs the effective state of
the kwarg, warns that it is enabled by default when the template supports
it, and only warns "has no effect" when it was enabled explicitly on a
template that does not support it. Setting the kwarg via
--chat-template-kwargs is deprecated.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* cont : update comment
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
---------
Co-authored-by: Xuan-Son Nguyen <son@huggingface.co>
Rename the --tensor-read-lazy CLI argument to --lazy-mode, to match the
internal lazy_mode parameter, and add a -lzm shorthand. Sync the READMEs.
Assisted-by: pi:llama.cpp/Qwen3.8-27B
* Add ctx-per-slot argument for unifid KV cache
* Swap out ctx fractions for ctx pool slots
* Formatting cleanup
* Remove ctx-pool-slots, make ctx-per-slot an int
* refactor it
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* Add benchmark-only synthetic speculative acceptance to llama-server and llama-cli
* Address review comments
* Address review comments
* Add some comments in the code
* common : dedupe --n-cpu-moe / --spec-draft-n-cpu-moe override loops
* common : add --n-cpu-ffn to CPU-offload dense FFN weights of first N layers
* common : generalize llm_ffn_block_regex over the FFN regex, drop TODO
* feat: add --mmproj-device arg & backwards compatible MTMD_BACKEND_DEVICE env var
* feat: load mmproj device backend immediately, add -mmdev shortflag
* fix: its a pointer now get the name
* clean up
* gen docs
* nits
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* ui: move get_datetime tool to frontend
* clarify docs
* server: drop the now unused ctime include
strftime() and gmtime_r() were the only users, both went away with the
get_datetime tool. Also make the renderer's catch inert: the browser
executor always emits JSON, so a non-JSON result is no longer a date to
display.
---------
Co-authored-by: Pascal <admin@serveurperso.com>
* chat: add reasoning_effort to common_chat_templates_inputs
Store OpenAI Chat Completions reasoning_effort and make it
available to jinja templates (with model specific translations
where required).
Assisted-by: llama.cpp:Muse-Glimmer-30B
* server : fixup reading reasoning effort from body
server_chat_convert_responses_to_chatcmpl already handles conversion of
Responses API reasoning.effort to reasoning_effort
* chat : expose reasoning effort
Assisted-by: Claude Opus 5
* chat : add reasoning_effort to generation_params
Assisted-by: Claude Opus 5
* chat : move reasoning_effort next to enable_thinking
Assisted-by: Claude Opus 5
* cont : mirror preserve_reasoning
* cont : pass context through analyze function
---------
Co-authored-by: Alde Rojas <hello@alde.dev>
* common : auto-detect spec type from draft GGUF metadata
When -md loads a local draft model without --spec-type, the sidecar
inference in common_models_handler_apply only checks HF repo sidecars
and misses local files. The draft model loads into VRAM but speculative
decoding never activates (types stays NONE).
Read general.architecture from the draft GGUF header and map:
dflash + markov_w1.weight tensor -> draft-dspark
dflash without markov head -> draft-dflash
Assisted-by: opencode
* common : address review feedback on spec-type auto-detect PR
- Fix comment spacing to match surrounding style (/* .x = */ not /*.x =*/)
- Add LOG_INF when auto-detection fires so users can see why spec decoding enabled
- Document single-file assumption for split-GGUF edge case
Addresses bot review feedback on #26814.
* common : move spec-type GGUF auto-detect into speculative module
- add common_speculative_types_from_gguf() in speculative.cpp/.h
- use gguf_context_ptr (RAII) from ggml-cpp.h
- reduce comments to a single line per AGENTS.md style
Addresses review feedback on #26814
* common : add doc note and join SPC_INF line in spec-type auto-detect
Assisted-by: opencode
* common: Add CLI > ENV > models-presets > INI precedence
1. CLI flags have the highest precedence
2. ENV vars have the second-highest precedence
3. System and User configs have the lowest precedence
- Linux/BSD/Mac
- /etc/llama.cpp/config.ini < ${XDG_CONFIG_HOME:-~/.config}/llama.cpp/config.ini
- Windows
- %PROGRAMDATA%\llama.cpp\config.ini < %APPDATA%\llama.cpp\config.ini
* fix UB
* use common_get_env
* ignore_unknown_keys
* nits
* add docs
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* cmake : introduce semantic versioning (wip)
This commit introduces semantic versioning to llama.cpp.
* squash! cmake : introduce semantic versioning (wip)
* cmake : update test-cmake README notes [no ci]
* include libmtmd in output so show its semversioned
* ci : add make-release workflow
* ci : fix build number check in build-cmake-pkg.yml
* examples : remove trailing whitespace
* ci : abort if upstream ggml version does not exist
* ci : extract step contents into scripts
* ci : add GGML_NATIVE=OFF to ubuntu job
* examples : remove CI build information from test-cmake [no ci]
This commit removes the nightly/release information that I added
previously to keep this focused only on using building and installing
llama.cpp with cmake and being able to quickly verify changes or
troubleshoot issues.
* ci : merge scripts into single script
* remove -dev-build_number support
This commit removes the incremental build number (versioning) support
that I added. This was incorrect and we should only use the semver for
the version. Releases will be tag a nightly build and package
maintainers/managers that build from source can use the tag and it is
therefor important that the correct version is reported. So a
nightly-build will report the semver without the build number. The build
number and commit as availble via cmake and test-cmake has been updated
to include an example of using them:
```console
$ ./build.sh
[test-cmake] version: 0.1.0, build: 10360 (08c69e381)
...
```
Refs: https://github.com/ggml-org/llama.cpp/pull/26839#discussion_r3755836969
* docs: add initial release.md documentation
* cmake : clean-up and add LLAMA_BUILD_IS_DEV option
* ci : remove version input from make-release job
* ci : add LLAMA_BUILD_IS_DEV=OFF to build-cmake-pkg.yml
Refs: https://github.com/danbev/llama.cpp/actions/runs/31576801921/job/94050639145
* docs : update release notes with LLAMA_BUILD_IS_DEV info [no ci]
* ci : add TODO to winget workflow [no ci]
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* llama: add new default load-mode auto which picks mmap unless a non-Metal iGPU is used
* Update ggml/src/ggml-hexagon/ggml-hexagon.cpp
Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com>
* set mmap_support to false on OpenCL backend
* fix order of load modes
* use -1 for auto
* resolve load mode auto earlier to correctly pick gpu host or cpu memory
* add load mode auto to llama-bench
* bump virtgpu api version, regenerate docs
---------
Co-authored-by: Piotr Wilkin (ilintar) <piotr.wilkin@syndatis.com>
Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* server: add an ssh transport to the tools runtime
--tools-runtime ssh:<target> runs the built-in tools on a remote host,
where target is whatever ssh already resolves, a user@host or a config
alias, so no credentials live in llama.cpp.
Only build_argv and upload differ from the docker transport: the remote
shell re-parses the command line, so the argv travels through
shell_quote_join, and files go over scp with the same quoting on the
remote path. Authentication is key-based and the host key must already
be trusted, since the tools run without a console and any prompt would
hang them.
The target is validated before use. The spec can reach us from the
x-tool-runtime header, and a leading dash would turn it into an ssh
option, which is enough to run a command back on the host.
Nothing is created and nothing is reclaimed, so an ssh spec goes
straight to the tool call instead of through the container runtime.
Note that this is remoting rather than isolation: the tools can do
whatever the target account can do, and the isolation is whatever runs
them on the far side.
* server: support podman in the tools runtime
docker and podman expose the same run, exec, cp and inspect verbs with the
same argument order, so a single implementation drives both and the engine
is carried by the spec prefix: podman:<image> and podman-container:<id> sit
next to the docker forms.
tools_io_docker becomes tools_io_container and the runtime spawner becomes
server_tools_container_runtime, both holding the client binary chosen at
parse time. A single parse_container_runtime() resolves every spec, so
adding another engine is one string in the table.
make_tools_io() now rejects the spawning forms. The spec also reaches it
from the x-tool-runtime header, which is client controlled, and only the
runtime that owns a container is allowed to create one: a tool call can
attach to a running container, nothing more.
* ./build/bin/llama-gen-docs
* server: simplify the tools runtime and drop the file copy step
A server_tools_runtime base with one virtual spec() replaces the
container runtime and the bare spec string that ssh needed next to it,
so server_tools is back to a single pointer and neither setup nor the
handler tests which of the two is set.
write_file used to spill its content into a temporary file on the host
and copy it in, because run_subprocess had no way to feed a child. It
now takes an optional stdin payload and creates the parent directory
and the file in a single round trip through a shell in the isolate.
That removes the upload virtual and both implementations: no more
container cp or scp, no second binary on the host, no sftp subsystem on
the target, no predictable temporary in a shared tmp, and none of the
content reaching an argv the remote shell re-parses. It also fixes
write_file over ssh, which never worked: scp speaks sftp and takes the
remote path literally, so quoting it kept the quotes in the file name.
Writing the payload before reading the output relies on the child
draining stdin as it goes, which holds for cat, its only user today.
* ./build/bin/llama-gen-docs
* server: harden the tools runtime against argv injection and a stdin stall
Validate the container id from x-tool-runtime and --tools-runtime the
same way the ssh target already is, so an id shaped like an option
(docker-container:--privileged) is rejected before it reaches the
engine's exec command line instead of running against a hardened
container. Feed the child's stdin after the watchdog is armed, so a
transport that stalls mid-write is terminated at the deadline rather
than blocking the request forever.
Cover both guards and fix the unknown-scheme test, which used ssh: as
its example and now names a real runtime.
* tests: exercise the tools runtime tests on podman as well as docker
Follow-up #26507. The container runtime drives docker and podman
through one implementation, so parametrize the availability helper,
the container fixture and the attach test on the engine, and cover
both engine prefixes in the container id injection test. Each engine
skips on its own when it is not installed.
The spawn cleanup test stays docker only: it recovers the spawned id
from the container hostname, which docker sets to the short id and
podman rootless does not guarantee. Podman keeps its coverage through
the attach path.
* server: release the container handle before respawning
Follow-up #26507. create() writes over the handle it is given, so a
respawn after the container died on its own leaked the pipes and the
process handle of the previous one.
* server: trim the tools runtime comments
* server: read tool output as raw bytes and harden the runtime on Windows
The stdout pipe is read with read() instead of fgets(), so a chunk
can hold any byte, including NUL, and still streams as soon as data
is available. Past the size cap the pipe keeps draining so the child
never blocks on a full pipe. Both pipe fds are forced to binary mode
on Windows, where the CRT defaults them to text mode and translates
line endings in both directions. Stdin is now always closed after
the feed: the child reads a deterministic EOF, and the Windows
docker and ssh clients stop outliving their command on a stdin pipe
that never closes.
The attach form of --tools-runtime has no lifecycle to own, so it
becomes a static target validated once at startup. This removes the
subprocess that ran on every tool call and
serialized calls behind a mutex; a stopped container now surfaces
the engine's own error at exec time.
The cidfile path is passed as UTF-8, matching the encoding the
subprocess layer expects for the CreateProcessW command line, so
the spawn form works from a non-ASCII Windows profile.
The SIGPIPE note in server.cpp now names the tools runtime children
as well as the MCP ones.
* clean up comments
* less pollute global scope
* nits
* tests: name the container image after both engines
---------
Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
* Resolve -1 to 1024 instead of ctx-len for samplers
Because of backend-sampling we initialize samplers before the complete
llama_context is there. Therefore, we cannot infer the resolved context
length yet at the time we construct the samplers.
* Shared default of 64 for history-based samplers, remove context_size
* server: add get_info tool
* fix --rpc in docs
* server: harden get_info probe result handling
Report the OS as unknown when the probe process fails to spawn or times
out, so the diagnostic text from run() is never returned as an OS name.
Strip the probe output on both ends, which also drops the blank line
that ver prints before the version on Windows. Name the output and
timeout limits, and report an unreadable working directory as unknown
instead of an empty string.
* server: simplify get_info result handling
Drop the named limits and the working directory error branch, keeping
the probe result handling to a single expression.
---------
Co-authored-by: Pascal <admin@serveurperso.com>
