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

common/arg.cpp

@@ -3543,6 +3543,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             params.models_max = value;
         }
     ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_MODELS_MAX"));
+    add_opt(common_arg(
+        {"--models-memory-margin"}, "N",
+        string_format("for router server, MiB of memory to leave free, per device (default: %d, 0 = unlimited)", params.models_memory_margin),
+        [](common_params & params, int value) {
+            params.models_memory_margin = value;
+        }
+    ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_MODELS_MEMORY_MARGIN"));
     add_opt(common_arg(
         {"--models-autoload"},
         {"--no-models-autoload"},
@@ -3798,6 +3805,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             params.offline = true;
         }
     ).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD, LLAMA_EXAMPLE_TOKENIZE}).set_env("LLAMA_ARG_OFFLINE"));
+    add_opt(common_arg(
+        {"--measure-only"},
+        "Load the model to measure memory requirements, print to stdout, then exit",
+        [](common_params & params) {
+            params.measure_only = true;
+        }
+    ));
     add_opt(common_arg(
         {"-lv", "--verbosity", "--log-verbosity"}, "N",
         string_format("Set the verbosity threshold. Messages with a higher verbosity will be ignored. Values:\n"

common/common.h

@@ -525,6 +525,8 @@ struct common_params {
     int32_t control_vector_layer_start = -1; // layer range for control vector
     int32_t control_vector_layer_end   = -1; // layer range for control vector
     bool    offline                    = false;
+    bool    skip_download              = false; // skip model file downloading
+    bool    measure_only               = false; // load model with no_alloc to measure memory, print to stdout, then exit
 
     int32_t ppl_stride      = 0;     // stride for perplexity calculations. If left at 0, the pre-existing approach will be used.
     int32_t ppl_output_type = 0;     // = 0 -> ppl output is as usual, = 1 -> ppl output is num_tokens, ppl, one per line
@@ -666,6 +668,7 @@ struct common_params {
     std::string models_dir    = "";     // directory containing models for the router server
     std::string models_preset = "";     // directory containing model presets for the router server
     int models_max = 4;                 // maximum number of models to load simultaneously
+    int models_memory_margin = 1024;    // MiB of free memory to preserve per device (0 = disabled)
     bool models_autoload = true;        // automatically load models when requested via the router server
     std::string models_preset_hf = "";  // show a warning about remote presets on router loaded (if not empty)