server: merge custom preset aliases into existing HF cached model entries

[batyrrasulov]

Summary\n- when a custom section name differs from an already discovered cached model key but points to the same , merge into the existing model entry instead of creating a duplicate\n- keep the custom section name as an alias on the merged model so requests can still target it\n\n## Validation\n- -- Warning: ccache not found - consider installing it for faster compilation or disable this warning with GGML_CCACHE=OFF

-- CMAKE_SYSTEM_PROCESSOR: arm64
-- GGML_SYSTEM_ARCH: ARM
-- Could NOT find OpenMP_C (missing: OpenMP_C_FLAGS OpenMP_C_LIB_NAMES)
-- Could NOT find OpenMP_CXX (missing: OpenMP_CXX_FLAGS OpenMP_CXX_LIB_NAMES)
-- Could NOT find OpenMP (missing: OpenMP_C_FOUND OpenMP_CXX_FOUND)
-- Including CPU backend
-- Accelerate framework found
-- ARM detected
-- Checking for ARM features using flags:
-- -U__ARM_FEATURE_SVE
-- -mcpu=native+dotprod+i8mm+nosve+sme
-- Adding CPU backend variant ggml-cpu: -U__ARM_FEATURE_SVE;-mcpu=native+dotprod+i8mm+nosve+sme
-- BLAS found, Libraries: /Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX.sdk/System/Library/Frameworks/Accelerate.framework
-- BLAS found, Includes:
-- Including BLAS backend
-- Metal framework found
-- Including METAL backend
-- ggml version: 0.13.1
-- ggml commit: 9b2af95
-- OpenSSL found: 3.6.2
-- Generating embedded license file for target: llama-app
-- Configuring done (1.0s)
-- Generating done (0.6s)
-- Build files have been written to: /Users/batyr.rasulov/Documents/Codex/2026-05-31/need-you-to-make-open-source/work/llama.cpp/build\n- [ 2%] Building CXX object common/CMakeFiles/llama-common-base.dir/build-info.cpp.o
[ 2%] Built target cpp-httplib
[ 2%] Building C object ggml/src/CMakeFiles/ggml-base.dir/ggml.c.o
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[ 2%] Building C object ggml/src/CMakeFiles/ggml-base.dir/ggml-alloc.c.o
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[ 4%] Building CXX object ggml/src/CMakeFiles/ggml-base.dir/ggml-backend.cpp.o
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[ 6%] Building CXX object ggml/src/CMakeFiles/ggml-base.dir/gguf.cpp.o
[ 6%] Linking CXX shared library ../../bin/libggml-base.dylib
[ 6%] Built target ggml-base
[ 6%] Linking CXX shared library ../../../bin/libggml-blas.dylib
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[ 6%] Built target ggml-blas
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[100%] Linking CXX executable ../bin/test-arg-parser
[100%] Built target test-arg-parser\n- [ 1%] Built target llama-common-base
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[ 5%] Provisioning UI assets
-- UI: running npm install (first time)
[ 5%] Built target ggml-blas
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[ 16%] Built target ggml
-- UI: npm install failed (1)
-- stderr: npm error code EBADENGINE
npm error engine Unsupported engine
npm error engine Not compatible with your version of node/npm: @chromatic-com/storybook@5.0.0
npm error notsup Not compatible with your version of node/npm: @chromatic-com/storybook@5.0.0
npm error notsup Required: {"node":">=20.0.0","yarn":">=1.22.18"}
npm error notsup Actual: {"npm":"10.8.2","node":"v18.20.8"}
npm error A complete log of this run can be found in: /Users/batyr.rasulov/.npm/_logs/2026-06-01T02_25_02_261Z-debug-0.log

-- UI: downloading from b9445: https://huggingface.co/buckets/ggml-org/llama-ui/resolve/b9445
[ 70%] Built target llama
-- UI: download bundle.css from b9445 failed: "HTTP response code said error"
-- UI: downloading from latest: https://huggingface.co/buckets/ggml-org/llama-ui/resolve/latest
[ 81%] Built target llama-common
[ 81%] Linking CXX shared library ../../bin/libmtmd.dylib
[ 92%] Built target mtmd
-- UI: downloaded bundle.css
[ 96%] Built target server-context
-- UI: downloaded bundle.js
-- UI: downloaded index.html
-- UI: downloaded loading.html
-- UI: verifying checksums
-- UI: all checksums verified
-- UI: HF download succeeded, stamp updated (latest)
[ 96%] Built target llama-ui-assets
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[ 98%] Linking CXX shared library ../../bin/libllama-server-impl.dylib
[100%] Built target llama-server-impl
[100%] Linking CXX executable ../../bin/llama-server
[100%] Built target llama-server\n- ----- common params -----

-h, --help, --usage print usage and exit
--version show version and build info
-cl, --cache-list show list of models in cache
--completion-bash print source-able bash completion script for llama.cpp
-t, --threads N number of CPU threads to use during generation (default: -1)
(env: LLAMA_ARG_THREADS)
-tb, --threads-batch N number of threads to use during batch and prompt processing (default:
same as --threads)
-C, --cpu-mask M CPU affinity mask: arbitrarily long hex. Complements cpu-range
(default: "")
-Cr, --cpu-range lo-hi range of CPUs for affinity. Complements --cpu-mask
--cpu-strict <0|1> use strict CPU placement (default: 0)
--prio N set process/thread priority : low(-1), normal(0), medium(1), high(2),
realtime(3) (default: 0)
--poll <0...100> use polling level to wait for work (0 - no polling, default: 50)
-Cb, --cpu-mask-batch M CPU affinity mask: arbitrarily long hex. Complements cpu-range-batch
(default: same as --cpu-mask)
-Crb, --cpu-range-batch lo-hi ranges of CPUs for affinity. Complements --cpu-mask-batch
--cpu-strict-batch <0|1> use strict CPU placement (default: same as --cpu-strict)
--prio-batch N set process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime
(default: 0)
--poll-batch <0|1> use polling to wait for work (default: same as --poll)
-c, --ctx-size N size of the prompt context (default: 0, 0 = loaded from model)
(env: LLAMA_ARG_CTX_SIZE)
-n, --predict, --n-predict N number of tokens to predict (default: -1, -1 = infinity)
(env: LLAMA_ARG_N_PREDICT)
-b, --batch-size N logical maximum batch size (default: 2048)
(env: LLAMA_ARG_BATCH)
-ub, --ubatch-size N physical maximum batch size (default: 512)
(env: LLAMA_ARG_UBATCH)
--keep N number of tokens to keep from the initial prompt (default: 0, -1 =
all)
--swa-full use full-size SWA cache (default: false)
(more
info)
(env: LLAMA_ARG_SWA_FULL)
-fa, --flash-attn [on|off|auto] set Flash Attention use ('on', 'off', or 'auto', default: 'auto')
(env: LLAMA_ARG_FLASH_ATTN)
--perf, --no-perf whether to enable internal libllama performance timings (default:
false)
(env: LLAMA_ARG_PERF)
-e, --escape, --no-escape whether to process escapes sequences (\n, \r, \t, ', ", \)
(default: true)
--rope-scaling {none,linear,yarn} RoPE frequency scaling method, defaults to linear unless specified by
the model
(env: LLAMA_ARG_ROPE_SCALING_TYPE)
--rope-scale N RoPE context scaling factor, expands context by a factor of N
(env: LLAMA_ARG_ROPE_SCALE)
--rope-freq-base N RoPE base frequency, used by NTK-aware scaling (default: loaded from
model)
(env: LLAMA_ARG_ROPE_FREQ_BASE)
--rope-freq-scale N RoPE frequency scaling factor, expands context by a factor of 1/N
(env: LLAMA_ARG_ROPE_FREQ_SCALE)
--yarn-orig-ctx N YaRN: original context size of model (default: 0 = model training
context size)
(env: LLAMA_ARG_YARN_ORIG_CTX)
--yarn-ext-factor N YaRN: extrapolation mix factor (default: -1.00, 0.0 = full
interpolation)
(env: LLAMA_ARG_YARN_EXT_FACTOR)
--yarn-attn-factor N YaRN: scale sqrt(t) or attention magnitude (default: -1.00)
(env: LLAMA_ARG_YARN_ATTN_FACTOR)
--yarn-beta-slow N YaRN: high correction dim or alpha (default: -1.00)
(env: LLAMA_ARG_YARN_BETA_SLOW)
--yarn-beta-fast N YaRN: low correction dim or beta (default: -1.00)
(env: LLAMA_ARG_YARN_BETA_FAST)
-kvo, --kv-offload, -nkvo, --no-kv-offload
whether to enable KV cache offloading (default: enabled)
(env: LLAMA_ARG_KV_OFFLOAD)
--repack, -nr, --no-repack whether to enable weight repacking (default: enabled)
(env: LLAMA_ARG_REPACK)
--no-host bypass host buffer allowing extra buffers to be used
(env: LLAMA_ARG_NO_HOST)
-ctk, --cache-type-k TYPE KV cache data type for K
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_K)
-ctv, --cache-type-v TYPE KV cache data type for V
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_V)
-dt, --defrag-thold N KV cache defragmentation threshold (DEPRECATED)
(env: LLAMA_ARG_DEFRAG_THOLD)
--mlock force system to keep model in RAM rather than swapping or compressing
(env: LLAMA_ARG_MLOCK)
--mmap, --no-mmap whether to memory-map model. (if mmap disabled, slower load but may
reduce pageouts if not using mlock) (default: enabled)
(env: LLAMA_ARG_MMAP)
-dio, --direct-io, -ndio, --no-direct-io
use DirectIO if available. (default: disabled)
(env: LLAMA_ARG_DIO)
--numa TYPE attempt optimizations that help on some NUMA systems
- distribute: spread execution evenly over all nodes
- isolate: only spawn threads on CPUs on the node that execution
started on
- numactl: use the CPU map provided by numactl
if run without this previously, it is recommended to drop the system
page cache before using this
see #1437
(env: LLAMA_ARG_NUMA)
-dev, --device <dev1,dev2,..> comma-separated list of devices to use for offloading (none = don't
offload)
use --list-devices to see a list of available devices
(env: LLAMA_ARG_DEVICE)
--list-devices print list of available devices and exit
-ot, --override-tensor =,...
override tensor buffer type
(env: LLAMA_ARG_OVERRIDE_TENSOR)
-cmoe, --cpu-moe keep all Mixture of Experts (MoE) weights in the CPU
(env: LLAMA_ARG_CPU_MOE)
-ncmoe, --n-cpu-moe N keep the Mixture of Experts (MoE) weights of the first N layers in the
CPU
(env: LLAMA_ARG_N_CPU_MOE)
-ngl, --gpu-layers, --n-gpu-layers N max. number of layers to store in VRAM, either an exact number,
'auto', or 'all' (default: auto)
(env: LLAMA_ARG_N_GPU_LAYERS)
-sm, --split-mode {none,layer,row,tensor}
how to split the model across multiple GPUs, one of:
- none: use one GPU only
- layer (default): split layers and KV across GPUs (pipelined)
- row: split weight across GPUs by rows (parallelized)
- tensor: split weights and KV across GPUs (parallelized,
EXPERIMENTAL)
(env: LLAMA_ARG_SPLIT_MODE)
-ts, --tensor-split N0,N1,N2,... fraction of the model to offload to each GPU, comma-separated list of
proportions, e.g. 3,1
(env: LLAMA_ARG_TENSOR_SPLIT)
-mg, --main-gpu INDEX the GPU to use for the model (with split-mode = none), or for
intermediate results and KV (with split-mode = row) (default: 0)
(env: LLAMA_ARG_MAIN_GPU)
-fit, --fit [on|off] whether to adjust unset arguments to fit in device memory ('on' or
'off', default: 'on')
(env: LLAMA_ARG_FIT)
-fitt, --fit-target MiB0,MiB1,MiB2,...
target margin per device for --fit, comma-separated list of values,
single value is broadcast across all devices, default: 1024
(env: LLAMA_ARG_FIT_TARGET)
-fitc, --fit-ctx N minimum ctx size that can be set by --fit option, default: 4096
(env: LLAMA_ARG_FIT_CTX)
--check-tensors check model tensor data for invalid values (default: false)
--override-kv KEY=TYPE:VALUE,... advanced option to override model metadata by key. to specify multiple
overrides, either use comma-separated values.
types: int, float, bool, str. example: --override-kv
tokenizer.ggml.add_bos_token=bool:false,tokenizer.ggml.add_eos_token=bool:false
--op-offload, --no-op-offload whether to offload host tensor operations to device (default: true)
--lora FNAME path to LoRA adapter (use comma-separated values to load multiple
adapters)
--lora-scaled FNAME:SCALE,... path to LoRA adapter with user defined scaling (format:
FNAME:SCALE,...)
note: use comma-separated values
--control-vector FNAME add a control vector
note: use comma-separated values to add multiple control vectors
--control-vector-scaled FNAME:SCALE,...
add a control vector with user defined scaling SCALE
note: use comma-separated values (format: FNAME:SCALE,...)
--control-vector-layer-range START END
layer range to apply the control vector(s) to, start and end inclusive
-m, --model FNAME model path to load
(env: LLAMA_ARG_MODEL)
-mu, --model-url MODEL_URL model download url (default: unused)
(env: LLAMA_ARG_MODEL_URL)
-dr, --docker-repo [/][:quant]
Docker Hub model repository. repo is optional, default to ai/. quant
is optional, default to :latest.
example: gemma3
(default: unused)
(env: LLAMA_ARG_DOCKER_REPO)
-hf, -hfr, --hf-repo /[:quant]
Hugging Face model repository; quant is optional, case-insensitive,
default to Q4_K_M, or falls back to the first file in the repo if
Q4_K_M doesn't exist.
mmproj is also downloaded automatically if available. to disable, add
--no-mmproj
example: ggml-org/GLM-4.7-Flash-GGUF:Q4_K_M
(default: unused)
(env: LLAMA_ARG_HF_REPO)
-hff, --hf-file FILE Hugging Face model file. If specified, it will override the quant in
--hf-repo (default: unused)
(env: LLAMA_ARG_HF_FILE)
-hfv, -hfrv, --hf-repo-v /[:quant]
Hugging Face model repository for the vocoder model (default: unused)
(env: LLAMA_ARG_HF_REPO_V)
-hffv, --hf-file-v FILE Hugging Face model file for the vocoder model (default: unused)
(env: LLAMA_ARG_HF_FILE_V)
-hft, --hf-token TOKEN Hugging Face access token (default: value from HF_TOKEN environment
variable)
(env: HF_TOKEN)
--log-disable Log disable
--log-file FNAME Log to file
(env: LLAMA_ARG_LOG_FILE)
--log-colors [on|off|auto] Set colored logging ('on', 'off', or 'auto', default: 'auto')
'auto' enables colors when output is to a terminal
(env: LLAMA_ARG_LOG_COLORS)
-v, --verbose, --log-verbose Set verbosity level to infinity (i.e. log all messages, useful for
debugging)
--offline Offline mode: forces use of cache, prevents network access
(env: LLAMA_ARG_OFFLINE)
-lv, --verbosity, --log-verbosity N Set the verbosity threshold. Messages with a higher verbosity will be
ignored. Values:
- 0: generic output
- 1: error
- 2: warning
- 3: info
- 4: trace (more info)
- 5: debug
(default: 3)

                                    (env: LLAMA_ARG_LOG_VERBOSITY)

--log-prefix, --no-log-prefix Enable prefix in log messages
(env: LLAMA_ARG_LOG_PREFIX)
--log-timestamps, --no-log-timestamps Enable timestamps in log messages
(env: LLAMA_ARG_LOG_TIMESTAMPS)
--spec-draft-type-k, -ctkd, --cache-type-k-draft TYPE
KV cache data type for K for the draft model
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_SPEC_DRAFT_CACHE_TYPE_K)
--spec-draft-type-v, -ctvd, --cache-type-v-draft TYPE
KV cache data type for V for the draft model
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_SPEC_DRAFT_CACHE_TYPE_V)

----- sampling params -----

--samplers SAMPLERS samplers that will be used for generation in the order, separated by
';'
(default:
penalties;dry;top_n_sigma;top_k;typ_p;top_p;min_p;xtc;temperature)
-s, --seed SEED RNG seed (default: -1, use random seed for -1)
--sampler-seq, --sampling-seq SEQUENCE
simplified sequence for samplers that will be used (default:
edskypmxt)
--ignore-eos ignore end of stream token and continue generating (implies
--logit-bias EOS-inf)
--temp, --temperature N temperature (default: 0.80)
--top-k N top-k sampling (default: 40, 0 = disabled)
(env: LLAMA_ARG_TOP_K)
--top-p N top-p sampling (default: 0.95, 1.0 = disabled)
--min-p N min-p sampling (default: 0.05, 0.0 = disabled)
--top-nsigma, --top-n-sigma N top-n-sigma sampling (default: -1.00, -1.0 = disabled)
--xtc-probability N xtc probability (default: 0.00, 0.0 = disabled)
--xtc-threshold N xtc threshold (default: 0.10, 1.0 = disabled)
--typical, --typical-p N locally typical sampling, parameter p (default: 1.00, 1.0 = disabled)
--repeat-last-n N last n tokens to consider for penalize (default: 64, 0 = disabled, -1
= ctx_size)
--repeat-penalty N penalize repeat sequence of tokens (default: 1.00, 1.0 = disabled)
--presence-penalty N repeat alpha presence penalty (default: 0.00, 0.0 = disabled)
--frequency-penalty N repeat alpha frequency penalty (default: 0.00, 0.0 = disabled)
--dry-multiplier N set DRY sampling multiplier (default: 0.00, 0.0 = disabled)
--dry-base N set DRY sampling base value (default: 1.75)
--dry-allowed-length N set allowed length for DRY sampling (default: 2)
--dry-penalty-last-n N set DRY penalty for the last n tokens (default: -1, 0 = disable, -1 =
context size)
--dry-sequence-breaker STRING add sequence breaker for DRY sampling, clearing out default breakers
('\n', ':', '"', '*') in the process; use "none" to not use any
sequence breakers
--adaptive-target N adaptive-p: select tokens near this probability (valid range 0.0 to
1.0; negative = disabled) (default: -1.00)
(more info)
--adaptive-decay N adaptive-p: decay rate for target adaptation over time. lower values
are more reactive, higher values are more stable.
(valid range 0.0 to 0.99) (default: 0.90)
--dynatemp-range N dynamic temperature range (default: 0.00, 0.0 = disabled)
--dynatemp-exp N dynamic temperature exponent (default: 1.00)
--mirostat N use Mirostat sampling.
Top K, Nucleus and Locally Typical samplers are ignored if used.
(default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)
--mirostat-lr N Mirostat learning rate, parameter eta (default: 0.10)
--mirostat-ent N Mirostat target entropy, parameter tau (default: 5.00)
-l, --logit-bias TOKEN_ID(+/-)BIAS modifies the likelihood of token appearing in the completion,
i.e. --logit-bias 15043+1 to increase likelihood of token ' Hello',
or --logit-bias 15043-1 to decrease likelihood of token ' Hello'
--grammar GRAMMAR BNF-like grammar to constrain generations (see samples in grammars/
dir)
--grammar-file FNAME file to read grammar from
-j, --json-schema SCHEMA JSON schema to constrain generations (https://json-schema.org/), e.g.
{} for any JSON object
For schemas w/ external $refs, use --grammar +
example/json_schema_to_grammar.py instead
-jf, --json-schema-file FILE File containing a JSON schema to constrain generations
(https://json-schema.org/), e.g. {} for any JSON object
For schemas w/ external $refs, use --grammar +
example/json_schema_to_grammar.py instead
-bs, --backend-sampling enable backend sampling (experimental) (default: disabled)
(env: LLAMA_ARG_BACKEND_SAMPLING)

----- speculative params -----

--spec-draft-hf, -hfd, -hfrd, --hf-repo-draft /[:quant]
Same as --hf-repo, but for the draft model (default: unused)
(env: LLAMA_ARG_SPEC_DRAFT_HF_REPO)
--spec-draft-threads, -td, --threads-draft N
number of threads to use during generation (default: same as
--threads)
--spec-draft-threads-batch, -tbd, --threads-batch-draft N
number of threads to use during batch and prompt processing (default:
same as --threads-draft)
--spec-draft-cpu-mask, -Cd, --cpu-mask-draft M
Draft model CPU affinity mask. Complements cpu-range-draft (default:
same as --cpu-mask)
--spec-draft-cpu-range, -Crd, --cpu-range-draft lo-hi
Ranges of CPUs for affinity. Complements --cpu-mask-draft
--spec-draft-cpu-strict, --cpu-strict-draft <0|1>
Use strict CPU placement for draft model (default: same as
--cpu-strict)
--spec-draft-prio, --prio-draft N set draft process/thread priority : 0-normal, 1-medium, 2-high,
3-realtime (default: 0)
--spec-draft-poll, --poll-draft <0|1> Use polling to wait for draft model work (default: same as --poll)
--spec-draft-cpu-mask-batch, -Cbd, --cpu-mask-batch-draft M
Draft model CPU affinity mask. Complements cpu-range-draft (default:
same as --cpu-mask)
--spec-draft-cpu-strict-batch, --cpu-strict-batch-draft <0|1>
Use strict CPU placement for draft model (default: --cpu-strict-draft)
--spec-draft-prio-batch, --prio-batch-draft N
set draft process/thread priority : 0-normal, 1-medium, 2-high,
3-realtime (default: 0)
--spec-draft-poll-batch, --poll-batch-draft <0|1>
Use polling to wait for draft model work (default: --poll-draft)
--spec-draft-override-tensor, -otd, --override-tensor-draft =,...
override tensor buffer type for draft model
--spec-draft-cpu-moe, -cmoed, --cpu-moe-draft
keep all Mixture of Experts (MoE) weights in the CPU for the draft
model
(env: LLAMA_ARG_SPEC_DRAFT_CPU_MOE)
--spec-draft-n-cpu-moe, --spec-draft-ncmoe, -ncmoed, --n-cpu-moe-draft N
keep the Mixture of Experts (MoE) weights of the first N layers in the
CPU for the draft model
(env: LLAMA_ARG_SPEC_DRAFT_N_CPU_MOE)
--spec-draft-n-max N number of tokens to draft for speculative decoding (default: 3)
(env: LLAMA_ARG_SPEC_DRAFT_N_MAX)
--spec-draft-n-min N minimum number of draft tokens to use for speculative decoding
(default: 0)
(env: LLAMA_ARG_SPEC_DRAFT_N_MIN)
--spec-draft-p-split, --draft-p-split P
speculative decoding split probability (default: 0.10)
(env: LLAMA_ARG_SPEC_DRAFT_P_SPLIT)
--spec-draft-p-min, --draft-p-min P minimum speculative decoding probability (greedy) (default: 0.00)
(env: LLAMA_ARG_SPEC_DRAFT_P_MIN)
--spec-draft-backend-sampling, --no-spec-draft-backend-sampling
offload draft sampling to the backend (default: enabled)
(env: LLAMA_ARG_SPEC_DRAFT_BACKEND_SAMPLING)
--spec-draft-device, -devd, --device-draft <dev1,dev2,..>
comma-separated list of devices to use for offloading the draft model
(none = don't offload)
use --list-devices to see a list of available devices
--spec-draft-ngl, -ngld, --gpu-layers-draft, --n-gpu-layers-draft N
max. number of draft model layers to store in VRAM, either an exact
number, 'auto', or 'all' (default: auto)
(env: LLAMA_ARG_N_GPU_LAYERS_DRAFT)
--spec-draft-model, -md, --model-draft FNAME
draft model for speculative decoding (default: unused)
(env: LLAMA_ARG_SPEC_DRAFT_MODEL)
--spec-type none,draft-simple,draft-eagle3,draft-mtp,ngram-simple,ngram-map-k,ngram-map-k4v,ngram-mod,ngram-cache
comma-separated list of types of speculative decoding to use (default:
none)

                                    (env: LLAMA_ARG_SPEC_TYPE)

--spec-ngram-mod-n-min N minimum number of ngram tokens to use for ngram-based speculative
decoding (default: 48)
--spec-ngram-mod-n-max N maximum number of ngram tokens to use for ngram-based speculative
decoding (default: 64)
--spec-ngram-mod-n-match N ngram-mod lookup length (default: 24)
--spec-ngram-simple-size-n N ngram size N for ngram-simple speculative decoding, length of lookup
n-gram (default: 12)
--spec-ngram-simple-size-m N ngram size M for ngram-simple speculative decoding, length of draft
m-gram (default: 48)
--spec-ngram-simple-min-hits N minimum hits for ngram-simple speculative decoding (default: 1)
--spec-ngram-map-k-size-n N ngram size N for ngram-map-k speculative decoding, length of lookup
n-gram (default: 12)
--spec-ngram-map-k-size-m N ngram size M for ngram-map-k speculative decoding, length of draft
m-gram (default: 48)
--spec-ngram-map-k-min-hits N minimum hits for ngram-map-k speculative decoding (default: 1)
--spec-ngram-map-k4v-size-n N ngram size N for ngram-map-k4v speculative decoding, length of lookup
n-gram (default: 12)
--spec-ngram-map-k4v-size-m N ngram size M for ngram-map-k4v speculative decoding, length of draft
m-gram (default: 48)
--spec-ngram-map-k4v-min-hits N minimum hits for ngram-map-k4v speculative decoding (default: 1)
--draft, --draft-n, --draft-max N the argument has been removed. use --spec-draft-n-max or
--spec-ngram-mod-n-max
(env: LLAMA_ARG_DRAFT_MAX)
--draft-min, --draft-n-min N the argument has been removed. use --spec-draft-n-min or
--spec-ngram-mod-n-min
(env: LLAMA_ARG_DRAFT_MIN)
--spec-ngram-size-n N the argument has been removed. use the respective
--spec-ngram--size-n or --spec-ngram-mod-n-match
--spec-ngram-size-m N the argument has been removed. use the respective
--spec-ngram--size-m
--spec-ngram-min-hits N the argument has been removed. use the respective
--spec-ngram-*-min-hits

----- example-specific params -----

-lcs, --lookup-cache-static FNAME path to static lookup cache to use for lookup decoding (not updated by
generation)
-lcd, --lookup-cache-dynamic FNAME path to dynamic lookup cache to use for lookup decoding (updated by
generation)
-ctxcp, --ctx-checkpoints, --swa-checkpoints N
max number of context checkpoints to create per slot (default:
32)(more info)
(env: LLAMA_ARG_CTX_CHECKPOINTS)
-cms, --checkpoint-min-step N minimum spacing between context checkpoints in tokens (default: 256, 0
= no minimum)
(env: LLAMA_ARG_CHECKPOINT_MIN_SPACING_NT)
-cram, --cache-ram N set the maximum cache size in MiB (default: 8192, -1 - no limit, 0 -
disable)(more
info)
(env: LLAMA_ARG_CACHE_RAM)
-kvu, --kv-unified, -no-kvu, --no-kv-unified
use single unified KV buffer shared across all sequences (default:
enabled if number of slots is auto)
(env: LLAMA_ARG_KV_UNIFIED)
--cache-idle-slots, --no-cache-idle-slots
save and clear idle slots on new task (default: enabled, requires
unified KV and cache-ram)
(env: LLAMA_ARG_CACHE_IDLE_SLOTS)
--context-shift, --no-context-shift whether to use context shift on infinite text generation (default:
disabled)
(env: LLAMA_ARG_CONTEXT_SHIFT)
-r, --reverse-prompt PROMPT halt generation at PROMPT, return control in interactive mode
-sp, --special special tokens output enabled (default: false)
--warmup, --no-warmup whether to perform warmup with an empty run (default: enabled)
--spm-infill use Suffix/Prefix/Middle pattern for infill (instead of
Prefix/Suffix/Middle) as some models prefer this. (default: disabled)
--pooling {none,mean,cls,last,rank} pooling type for embeddings, use model default if unspecified
(env: LLAMA_ARG_POOLING)
-np, --parallel N number of server slots (default: -1, -1 = auto)
(env: LLAMA_ARG_N_PARALLEL)
-cb, --cont-batching, -nocb, --no-cont-batching
whether to enable continuous batching (a.k.a dynamic batching)
(default: enabled)
(env: LLAMA_ARG_CONT_BATCHING)
-mm, --mmproj FILE path to a multimodal projector file. see tools/mtmd/README.md
note: if -hf is used, this argument can be omitted
(env: LLAMA_ARG_MMPROJ)
-mmu, --mmproj-url URL URL to a multimodal projector file. see tools/mtmd/README.md
(env: LLAMA_ARG_MMPROJ_URL)
--mmproj-auto, --no-mmproj, --no-mmproj-auto
whether to use multimodal projector file (if available), useful when
using -hf (default: enabled)
(env: LLAMA_ARG_MMPROJ_AUTO)
--mmproj-offload, --no-mmproj-offload whether to enable GPU offloading for multimodal projector (default:
enabled)
(env: LLAMA_ARG_MMPROJ_OFFLOAD)
--image-min-tokens N minimum number of tokens each image can take, only used by vision
models with dynamic resolution (default: read from model)
(env: LLAMA_ARG_IMAGE_MIN_TOKENS)
--image-max-tokens N maximum number of tokens each image can take, only used by vision
models with dynamic resolution (default: read from model)
(env: LLAMA_ARG_IMAGE_MAX_TOKENS)
-a, --alias STRING set model name aliases, comma-separated (to be used by API)
(env: LLAMA_ARG_ALIAS)
--tags STRING set model tags, comma-separated (informational, not used for routing)
(env: LLAMA_ARG_TAGS)
--embd-normalize N normalisation for embeddings (default: 2) (-1=none, 0=max absolute
int16, 1=taxicab, 2=euclidean, >2=p-norm)
--host HOST ip address to listen, or bind to an UNIX socket if the address ends
with .sock (default: 127.0.0.1)
(env: LLAMA_ARG_HOST)
--port PORT port to listen (default: 8080)
(env: LLAMA_ARG_PORT)
--reuse-port allow multiple sockets to bind to the same port (default: disabled)
(env: LLAMA_ARG_REUSE_PORT)
--path PATH path to serve static files from (default: )
(env: LLAMA_ARG_STATIC_PATH)
--api-prefix PREFIX prefix path the server serves from, without the trailing slash
(default: )
(env: LLAMA_ARG_API_PREFIX)
--webui-config JSON [DEPRECATED: use --ui-config] JSON that provides default WebUI
settings (overrides WebUI defaults)
(env: LLAMA_ARG_WEBUI_CONFIG)
--ui-config JSON JSON that provides default UI settings (overrides UI defaults)
(env: LLAMA_ARG_UI_CONFIG)
--webui-config-file PATH [DEPRECATED: use --ui-config-file] JSON file that provides default
WebUI settings (overrides WebUI defaults)
(env: LLAMA_ARG_WEBUI_CONFIG_FILE)
--ui-config-file PATH JSON file that provides default UI settings (overrides UI defaults)
(env: LLAMA_ARG_UI_CONFIG_FILE)
--webui-mcp-proxy, --no-webui-mcp-proxy
[DEPRECATED: use --ui-mcp-proxy/--no-ui-mcp-proxy] experimental:
whether to enable MCP CORS proxy
(env: LLAMA_ARG_WEBUI_MCP_PROXY)
--ui-mcp-proxy, --no-ui-mcp-proxy experimental: whether to enable MCP CORS proxy - do not enable in
untrusted environments (default: disabled)
(env: LLAMA_ARG_UI_MCP_PROXY)
--tools TOOL1,TOOL2,... experimental: whether to enable built-in tools for AI agents - do not
enable in untrusted environments (default: no tools)
specify "all" to enable all tools
available tools: read_file, file_glob_search, grep_search,
exec_shell_command, write_file, edit_file, apply_diff, get_datetime
(env: LLAMA_ARG_TOOLS)
--webui, --no-webui [DEPRECATED: use --ui/--no-ui] whether to enable the Web UI
(env: LLAMA_ARG_WEBUI)
--ui, --no-ui whether to enable the Web UI (default: enabled)
(env: LLAMA_ARG_UI)
--embedding, --embeddings restrict to only support embedding use case; use only with dedicated
embedding models (default: disabled)
(env: LLAMA_ARG_EMBEDDINGS)
--rerank, --reranking enable reranking endpoint on server (default: disabled)
(env: LLAMA_ARG_RERANKING)
--api-key KEY API key to use for authentication, multiple keys can be provided as a
comma-separated list (default: none)
(env: LLAMA_API_KEY)
--api-key-file FNAME path to file containing API keys (default: none)
(env: LLAMA_ARG_API_KEY_FILE)
--ssl-key-file FNAME path to file a PEM-encoded SSL private key
(env: LLAMA_ARG_SSL_KEY_FILE)
--ssl-cert-file FNAME path to file a PEM-encoded SSL certificate
(env: LLAMA_ARG_SSL_CERT_FILE)
--chat-template-kwargs STRING sets additional params for the json template parser, must be a valid
json object string, e.g. '{"key1":"value1","key2":"value2"}'
(env: LLAMA_ARG_CHAT_TEMPLATE_KWARGS)
-to, --timeout N server read/write timeout in seconds (default: 3600)
(env: LLAMA_ARG_TIMEOUT)
--threads-http N number of threads used to process HTTP requests (default: -1)
(env: LLAMA_ARG_THREADS_HTTP)
--cache-prompt, --no-cache-prompt whether to enable prompt caching (default: enabled)
(env: LLAMA_ARG_CACHE_PROMPT)
--cache-reuse N min chunk size to attempt reusing from the cache via KV shifting,
requires prompt caching to be enabled (default: 0)
(card)
(env: LLAMA_ARG_CACHE_REUSE)
--metrics enable prometheus compatible metrics endpoint (default: disabled)
(env: LLAMA_ARG_ENDPOINT_METRICS)
--props enable changing global properties via POST /props (default: disabled)
(env: LLAMA_ARG_ENDPOINT_PROPS)
--slots, --no-slots expose slots monitoring endpoint (default: enabled)
(env: LLAMA_ARG_ENDPOINT_SLOTS)
--slot-save-path PATH path to save slot kv cache (default: disabled)
--media-path PATH directory for loading local media files; files can be accessed via
file:// URLs using relative paths (default: disabled)
--models-dir PATH directory containing models for the router server (default: disabled)
(env: LLAMA_ARG_MODELS_DIR)
--models-preset PATH path to INI file containing model presets for the router server
(default: disabled)
(env: LLAMA_ARG_MODELS_PRESET)
--models-max N for router server, maximum number of models to load simultaneously
(default: 4, 0 = unlimited)
(env: LLAMA_ARG_MODELS_MAX)
--models-autoload, --no-models-autoload
for router server, whether to automatically load models (default:
enabled)
(env: LLAMA_ARG_MODELS_AUTOLOAD)
--jinja, --no-jinja whether to use jinja template engine for chat (default: enabled)
(env: LLAMA_ARG_JINJA)
--reasoning-format FORMAT controls whether thought tags are allowed and/or extracted from the
response, and in which format they're returned; one of:
- none: leaves thoughts unparsed in message.content
- deepseek: puts thoughts in message.reasoning_content
- deepseek-legacy: keeps <think> tags in message.content while
also populating message.reasoning_content
(default: auto)
(env: LLAMA_ARG_THINK)
-rea, --reasoning [on|off|auto] Use reasoning/thinking in the chat ('on', 'off', or 'auto', default:
'auto' (detect from template))
(env: LLAMA_ARG_REASONING)
--reasoning-budget N token budget for thinking: -1 for unrestricted, 0 for immediate end,
N>0 for token budget (default: -1)
(env: LLAMA_ARG_THINK_BUDGET)
--reasoning-budget-message MESSAGE message injected before the end-of-thinking tag when reasoning budget
is exhausted (default: none)
(env: LLAMA_ARG_THINK_BUDGET_MESSAGE)
--chat-template JINJA_TEMPLATE set custom jinja chat template (default: template taken from model's
metadata)
if suffix/prefix are specified, template will be disabled
only commonly used templates are accepted (unless --jinja is set
before this flag):
list of built-in templates:
bailing, bailing-think, bailing2, chatglm3, chatglm4, chatml,
command-r, deepseek, deepseek-ocr, deepseek2, deepseek3, exaone-moe,
exaone3, exaone4, falcon3, gemma, gigachat, glmedge, gpt-oss, granite,
granite-4.0, granite-4.1, grok-2, hunyuan-dense, hunyuan-moe,
hunyuan-vl, kimi-k2, llama2, llama2-sys, llama2-sys-bos,
llama2-sys-strip, llama3, llama4, megrez, minicpm, mistral-v1,
mistral-v3, mistral-v3-tekken, mistral-v7, mistral-v7-tekken, monarch,
openchat, orion, pangu-embedded, phi3, phi4, rwkv-world, seed_oss,
smolvlm, solar-open, vicuna, vicuna-orca, yandex, zephyr
(env: LLAMA_ARG_CHAT_TEMPLATE)
--chat-template-file JINJA_TEMPLATE_FILE
set custom jinja chat template file (default: template taken from
model's metadata)
if suffix/prefix are specified, template will be disabled
only commonly used templates are accepted (unless --jinja is set
before this flag):
list of built-in templates:
bailing, bailing-think, bailing2, chatglm3, chatglm4, chatml,
command-r, deepseek, deepseek-ocr, deepseek2, deepseek3, exaone-moe,
exaone3, exaone4, falcon3, gemma, gigachat, glmedge, gpt-oss, granite,
granite-4.0, granite-4.1, grok-2, hunyuan-dense, hunyuan-moe,
hunyuan-vl, kimi-k2, llama2, llama2-sys, llama2-sys-bos,
llama2-sys-strip, llama3, llama4, megrez, minicpm, mistral-v1,
mistral-v3, mistral-v3-tekken, mistral-v7, mistral-v7-tekken, monarch,
openchat, orion, pangu-embedded, phi3, phi4, rwkv-world, seed_oss,
smolvlm, solar-open, vicuna, vicuna-orca, yandex, zephyr
(env: LLAMA_ARG_CHAT_TEMPLATE_FILE)
--skip-chat-parsing, --no-skip-chat-parsing
force a pure content parser, even if a Jinja template is specified;
model will output everything in the content section, including any
reasoning and/or tool calls (default: disabled)
(env: LLAMA_ARG_SKIP_CHAT_PARSING)
--prefill-assistant, --no-prefill-assistant
whether to prefill the assistant's response if the last message is an
assistant message (default: prefill enabled)
when this flag is set, if the last message is an assistant message
then it will be treated as a full message and not prefilled

                                    (env: LLAMA_ARG_PREFILL_ASSISTANT)

-sps, --slot-prompt-similarity SIMILARITY
how much the prompt of a request must match the prompt of a slot in
order to use that slot (default: 0.10, 0.0 = disabled)
--lora-init-without-apply load LoRA adapters without applying them (apply later via POST
/lora-adapters) (default: disabled)
--sleep-idle-seconds SECONDS number of seconds of idleness after which the server will sleep
(default: -1; -1 = disabled)
-mv, --model-vocoder FNAME vocoder model for audio generation (default: unused)
--tts-use-guide-tokens Use guide tokens to improve TTS word recall
--embd-gemma-default use default EmbeddingGemma model (note: can download weights from the
internet)
--fim-qwen-1.5b-default use default Qwen 2.5 Coder 1.5B (note: can download weights from the
internet)
--fim-qwen-3b-default use default Qwen 2.5 Coder 3B (note: can download weights from the
internet)
--fim-qwen-7b-default use default Qwen 2.5 Coder 7B (note: can download weights from the
internet)
--fim-qwen-7b-spec use Qwen 2.5 Coder 7B + 0.5B draft for speculative decoding (note: can
download weights from the internet)
--fim-qwen-14b-spec use Qwen 2.5 Coder 14B + 0.5B draft for speculative decoding (note:
can download weights from the internet)
--fim-qwen-30b-default use default Qwen 3 Coder 30B A3B Instruct (note: can download weights
from the internet)
--gpt-oss-20b-default use gpt-oss-20b (note: can download weights from the internet)
--gpt-oss-120b-default use gpt-oss-120b (note: can download weights from the internet)
--vision-gemma-4b-default use Gemma 3 4B QAT (note: can download weights from the internet)
--vision-gemma-12b-default use Gemma 3 12B QAT (note: can download weights from the internet)
--spec-default enable default speculative decoding config\n\nFixes #23931