fix(llama-cpp): terminate tensor/kv override vectors after passthrough

The tensor_buft_overrides padding and the kv/draft override terminators
ran before the generic option passthrough, so a passthrough flag
(--cpu-moe, --override-tensor, --override-kv, ...) appended a real entry
after the null sentinel - tripping the model loader's
back().pattern == nullptr assertion (crash) or being silently dropped.
Move all three termination/padding blocks to the end of params_parse,
after both the named-option loop and common_params_parse have pushed
their real entries. Also widen the exit()-flag skip list so --version,
--license, --list-devices and --cache-list cannot terminate the backend.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

backend/cpp/llama-cpp/grpc-server.cpp

@@ -37,6 +37,7 @@
 #include "backend.pb.h"
 #include "backend.grpc.pb.h"
 #include "common.h"
+#include "arg.h"
 #include "chat-auto-parser.h"
 #include <getopt.h>
 #include <grpcpp/ext/proto_server_reflection_plugin.h>
@@ -592,6 +593,10 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
     params.checkpoint_min_step = 256;
 #endif
 
+    // Raw upstream llama-server flags collected from any option entry that
+    // starts with '-'. Applied once after the loop via common_params_parse.
+    std::vector<std::string> extra_argv;
+
      // decode options. Options are in form optname:optvale, or if booleans only optname.
     for (int i = 0; i < request->options_size(); i++) {
         std::string opt = request->options(i);
@@ -1080,6 +1085,31 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
                 } catch (...) {}
             }
 
+        // --- main model MoE on CPU (upstream --cpu-moe / --n-cpu-moe) ---
+        } else if (!strcmp(optname, "cpu_moe")) {
+            // Bool-style flag: keep all MoE expert weights on CPU.
+            const bool enable = (optval == NULL) ||
+                optval_str == "true" || optval_str == "1" || optval_str == "yes" ||
+                optval_str == "on" || optval_str == "enabled";
+            if (enable) {
+                params.tensor_buft_overrides.push_back(llm_ffn_exps_cpu_override());
+            }
+        } else if (!strcmp(optname, "n_cpu_moe")) {
+            if (optval != NULL) {
+                try {
+                    int n = std::stoi(optval_str);
+                    if (n < 0) n = 0;
+                    // Keep override-name storage alive for the lifetime of the
+                    // params struct (mirrors upstream arg.cpp's function-local static).
+                    static std::list<std::string> buft_overrides_main;
+                    for (int i = 0; i < n; ++i) {
+                        buft_overrides_main.push_back(llm_ffn_exps_block_regex(i));
+                        params.tensor_buft_overrides.push_back(
+                            {buft_overrides_main.back().c_str(), ggml_backend_cpu_buffer_type()});
+                    }
+                } catch (...) {}
+            }
+
         // --- draft model tensor buffer overrides (upstream --spec-draft-override-tensor) ---
         } else if (!strcmp(optname, "draft_override_tensor") || !strcmp(optname, "spec_draft_override_tensor")) {
             // Format: <tensor regex>=<buffer type>,<tensor regex>=<buffer type>,...
@@ -1111,6 +1141,30 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
                 else { cur.push_back(c); }
             }
             if (!cur.empty()) flush(cur);
+
+        // --- generic passthrough: any entry starting with '-' is a raw
+        //     upstream llama-server flag, forwarded verbatim to the parser. ---
+        } else if (optname[0] == '-') {
+            std::string flag = optname;
+            // These flags make upstream's parser exit() (printing usage /
+            // completion), which would kill the backend process. Skip them.
+            if (flag == "-h" || flag == "--help" || flag == "--usage" ||
+                flag == "--version" || flag == "--license" ||
+                flag == "--list-devices" || flag == "-cl" ||
+                flag == "--cache-list" ||
+                flag.rfind("--completion", 0) == 0) {
+                fprintf(stderr,
+                    "[llama-cpp] ignoring passthrough flag that would exit: %s\n",
+                    flag.c_str());
+            } else {
+                extra_argv.push_back(flag);
+                // Preserve the whole value after the first ':' so embedded
+                // colons (e.g. host:port) survive strtok's truncation of optval.
+                auto colon = opt.find(':');
+                if (colon != std::string::npos) {
+                    extra_argv.push_back(opt.substr(colon + 1));
+                }
+            }
         }
     }
 
@@ -1146,27 +1200,6 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
         }
     }
 
-    if (!params.kv_overrides.empty()) {
-        params.kv_overrides.emplace_back();
-        params.kv_overrides.back().key[0] = 0;
-    }
-
-    // tensor_buft_overrides sentinel termination (mirrors upstream common/arg.cpp).
-    // Real entries are pushed during option parsing; here we pad/terminate so the
-    // model loader sees back().pattern == nullptr (GGML_ASSERT at common.cpp:1543)
-    // and so llama_params_fit has the placeholder slots it requires.
-    {
-        const size_t ntbo = llama_max_tensor_buft_overrides();
-        while (params.tensor_buft_overrides.size() < ntbo) {
-            params.tensor_buft_overrides.push_back({nullptr, nullptr});
-        }
-    }
-    // Terminate the draft tensor_buft_overrides list with a sentinel, mirroring
-    // the main-model handling above.
-    if (!params.speculative.draft.tensor_buft_overrides.empty()) {
-        params.speculative.draft.tensor_buft_overrides.push_back({nullptr, nullptr});
-    }
-
     // TODO: Add yarn
 
     if (!request->tensorsplit().empty()) {
@@ -1259,6 +1292,69 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
             params.sampling.grammar_triggers.push_back(std::move(trigger));
         }
     }
+
+    // Apply any raw upstream flags last so an explicit passthrough flag wins
+    // over the LocalAI-resolved field it maps to (e.g. --ctx-size beats
+    // context_size). This is the same parser llama-server itself uses.
+    if (!extra_argv.empty()) {
+        // common_params_parser_init resets a few fields for the SERVER example
+        // (n_parallel -> -1, use_color). Snapshot n_parallel so an unrelated
+        // passthrough flag can't silently clobber LocalAI's resolved value.
+        const int saved_n_parallel = params.n_parallel;
+
+        std::vector<char *> argv;
+        std::string prog = "llama-server";
+        argv.push_back(prog.data());
+        for (auto & a : extra_argv) {
+            argv.push_back(a.data());
+        }
+
+        // ctx_arg.params is a reference, so this overlays the given flags onto
+        // `params` in place. Returns false on a recoverable parse error (and
+        // self-restores params); may exit() on a hard error, exactly as
+        // passing the same bad flag to llama-server would.
+        if (!common_params_parse((int)argv.size(), argv.data(), params,
+                                 LLAMA_EXAMPLE_SERVER)) {
+            fprintf(stderr,
+                "[llama-cpp] failed to parse passthrough options; ignoring them\n");
+        }
+
+        // Restore n_parallel unless a passthrough flag explicitly set it
+        // (parser_init's reset sentinel for SERVER is -1).
+        if (params.n_parallel == -1) {
+            params.n_parallel = saved_n_parallel;
+        }
+    }
+
+    // Terminate/pad the override vectors only after BOTH the named-option loop
+    // and the generic passthrough (common_params_parse above) have pushed their
+    // real entries, so back() is the null sentinel the model loader asserts on.
+    // Running these before the passthrough let a passthrough flag (--cpu-moe,
+    // --override-tensor, --override-kv, ...) append a real entry after the
+    // sentinel: a GGML_ASSERT crash for tensor_buft_overrides, a silent drop for
+    // kv_overrides. Double-termination is harmless (the while is a no-op if the
+    // passthrough parse already padded; an extra trailing null is ignored).
+
+    if (!params.kv_overrides.empty()) {
+        params.kv_overrides.emplace_back();
+        params.kv_overrides.back().key[0] = 0;
+    }
+
+    // tensor_buft_overrides sentinel termination (mirrors upstream common/arg.cpp).
+    // Real entries are pushed during option parsing; here we pad/terminate so the
+    // model loader sees back().pattern == nullptr (GGML_ASSERT at common.cpp:1543)
+    // and so llama_params_fit has the placeholder slots it requires.
+    {
+        const size_t ntbo = llama_max_tensor_buft_overrides();
+        while (params.tensor_buft_overrides.size() < ntbo) {
+            params.tensor_buft_overrides.push_back({nullptr, nullptr});
+        }
+    }
+    // Terminate the draft tensor_buft_overrides list with a sentinel, mirroring
+    // the main-model handling above.
+    if (!params.speculative.draft.tensor_buft_overrides.empty()) {
+        params.speculative.draft.tensor_buft_overrides.push_back({nullptr, nullptr});
+    }
 }
 
 

docs/content/advanced/model-configuration.md

@@ -494,6 +494,39 @@ These llama.cpp options are passed through the `options:` array.
 | `direct_io` / `use_direct_io` | bool | `false` | Open the model with `O_DIRECT` (faster cold loads on NVMe; ignored if not supported). |
 | `verbosity` | int | `3` | llama.cpp internal log verbosity threshold. Higher = more verbose. |
 | `override_tensor` / `tensor_buft_overrides` | string | "" | Per-tensor buffer-type overrides for the main model. Format: `<tensor regex>=<buffer type>,<tensor regex>=<buffer type>,...`. Mirrors the existing `draft_override_tensor` syntax for the draft model. |
+| `cpu_moe` | bool | false | Keep all MoE expert weights of the main model on CPU (upstream `--cpu-moe`). Frees VRAM on large MoE models (DeepSeek, Qwen3 `*-A3B`). |
+| `n_cpu_moe` | int | 0 | Keep MoE expert weights of the first N main-model layers on CPU (upstream `--n-cpu-moe`). |
+
+#### Generic option passthrough
+
+Any `options:` entry whose name starts with `-` is forwarded **verbatim** to
+upstream llama.cpp's own `llama-server` argument parser. This means any flag the
+bundled llama.cpp supports works without LocalAI needing a dedicated option,
+even ones added after your LocalAI version was built. See the upstream
+[server flags reference](https://github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md).
+
+Format mirrors the rest of the array - `--flag` for a boolean, or `--flag:value`
+for a flag that takes a value. Everything after the first `:` is the value, so
+embedded colons (e.g. `host:port`) are preserved:
+
+```yaml
+options:
+  - "--cpu-moe"                 # boolean flag
+  - "--n-cpu-moe:4"             # flag with a value
+  - "--override-tensor:exps=CPU"
+```
+
+Notes:
+
+- **Precedence:** passthrough flags are applied last, so an explicit flag
+  overrides the LocalAI option it maps to (e.g. `--ctx-size:8192` overrides
+  `context_size`).
+- **Power-user territory:** an invalid flag or value is rejected by the upstream
+  parser exactly as it would be by `llama-server`, which can fail model loading.
+  Prefer the named options above when one exists.
+- Flags that would terminate the process (such as `--help`, `--usage`,
+  `--version`, `--license`, `--list-devices`, `--cache-list`, and
+  `--completion*`) are ignored.
 
 ### Prompt Caching