docs(llama-cpp): clarify multimodal speculative decoding (#11700)

* docs(llama-cpp): clarify multimodal speculative decoding

Update the speculative decoding guidance now that modern llama.cpp backends can combine mmproj-based vision with speculative decoding, including MTP. Document compatibility checks, draft acceptance statistics, VRAM tradeoffs, and a combined configuration example.

Assisted-by: Codex:GPT-5.6-Sol [gh] [OpenStack] [Docker]
Signed-off-by: Abdullah Mansour <abdullahmansour.marketing@gmail.com>

* docs(llama-cpp): clarify multimodal MTP references

Distinguish the upstream change that removed the general multimodal speculative restriction from the later change that added MTP with explicit vision compatibility.

Assisted-by: Codex:GPT-5.6-Sol [gh] [Docker]
Signed-off-by: Abdullah Mansour <abdullahmansour.marketing@gmail.com>

---------

Signed-off-by: Abdullah Mansour <abdullahmansour.marketing@gmail.com>

docs/content/advanced/model-configuration.md

@@ -397,7 +397,9 @@ The canonical names match upstream llama.cpp (dash-separated). For backward comp
 Multiple types can be chained by passing a comma-separated list to `spec_type` (e.g. `spec_type:ngram-simple,ngram-mod`). The runtime tries them in order and accepts the first proposal that meets the acceptance criteria.
 
 {{% notice note %}}
-Speculative decoding is automatically disabled when multimodal models (with `mmproj`) are active. The `n_draft` parameter can also be overridden per-request.
+The current LocalAI llama.cpp backend supports speculative decoding with multimodal models that load an `mmproj`, including MTP. LocalAI passes both configurations to llama.cpp and does not disable speculation merely because an `mmproj` is present. Upstream llama.cpp removed the former general multimodal/speculative restriction in [ggml-org/llama.cpp#19493](https://github.com/ggml-org/llama.cpp/pull/19493); [ggml-org/llama.cpp#22673](https://github.com/ggml-org/llama.cpp/pull/22673) later added MTP support and explicitly documented its compatibility with vision input.
+
+Compatibility still depends on the installed backend version and the target/draft model architecture. Check the backend logs for successful projector loading and speculative-context initialization, then look for the `draft acceptance` statistics line and its `accepted / generated` counts. A representative run with zero accepted draft tokens receives no speculative speedup and can indicate that the model or settings need tuning.
 {{% /notice %}}
 
 ##### Multi-Token Prediction (MTP)
@@ -427,7 +429,7 @@ Detection runs both at **import time** (the `/import-model` UI / `POST /models/i
 | `spec_type` | `draft-mtp` | Activates MTP. Can be chained with other types (see below). |
 | `spec_n_max` / `draft_max` | `2`-`6` | Number of draft tokens per step. Upstream's PR suggests 2-3 for the tightest acceptance window; LocalAI's auto-default is 6 to favour throughput on models with high acceptance. |
 | `spec_p_min` | `0.75` | Pinned because upstream marks the current default with a "change to 0.0f" TODO; locking it here keeps acceptance thresholds stable across future llama.cpp bumps. |
-| `mmproj_use_gpu` | `false` (or unset `mmproj`) | MTP has a prompt-processing overhead; if the model is non-vision, drop the mmproj entirely to save VRAM. |
+| `mmproj_use_gpu` | `true` for vision | MTP does not require disabling the projector. Keep `mmproj` configured for image input; set this option to `false` to keep the projector on CPU when VRAM is tight. Remove `mmproj` only for text-only use when vision is not needed. |
 
 **Minimal config** (override-only, since auto-detection already covers this for MTP-capable GGUFs):
 
@@ -441,6 +443,23 @@ options:
   - spec_n_max:3
 ```
 
+**With vision enabled:**
+
+```yaml
+name: qwen3-vision-mtp
+backend: llama-cpp
+known_usecases:
+  - chat
+  - vision
+parameters:
+  model: qwen3-with-mtp.gguf
+mmproj: mmproj-qwen3.gguf
+options:
+  - spec_type:draft-mtp
+  - spec_n_max:3
+  - spec_p_min:0.75
+```
+
 **With a separate MTP head file:**
 
 ```yaml