Update README: add vision (mmproj) section + usage examples

README.md

@@ -16,6 +16,8 @@ tags:
   - long-context
   - 1M-context
   - function-calling
+  - multimodal
+  - vision
   - cybersecurity
   - biomedical
   - agentic
@@ -37,7 +39,9 @@ For full training details, evaluation numbers, and capability writeup, see the *
 
 ---
 
-## Files — pick one quant
+## Files
+
+### Text weights — pick one quant
 
 | File | Quant | Size | Notes |
 |---|---|---|---|
@@ -49,6 +53,14 @@ For full training details, evaluation numbers, and capability writeup, see the *
 
 If you don't know which to pick, **Q4_K_M is the right starting point** — it's the smallest practical quant with good quality preservation.
 
+### Vision projector — for image input
+
+| File | Size | Notes |
+|---|---|---|
+| `mmproj-Qwythos-9B-Claude-Mythos-5-1M-f16.gguf` | ~876 MB | CLIP-style vision encoder + projector; **required for images**, pairs with any quant above |
+
+Qwythos inherits its **vision tower from the Qwen3.5-9B base model** — the vision path was *frozen* during SFT (training was text-only), so the vision behavior is identical to base Qwen3.5-9B's multimodal capability. The mmproj is interchangeable with any community-built Qwen3.5-9B `mmproj-*.gguf`.
+
 ---
 
 ## Quick start
@@ -76,6 +88,45 @@ Drop any of the `.gguf` files into your runtime's model directory. Qwythos uses
 
 ---
 
+## Vision (image input)
+
+Qwythos supports **image input** out of the box. Download both a text quant and the `mmproj-*.gguf` file from this repo, then run with llama.cpp's multimodal CLI or server.
+
+### llama.cpp (`llama-mtmd-cli`)
+
+```bash
+llama-mtmd-cli \
+  -m Qwythos-9B-Claude-Mythos-5-1M-Q4_K_M.gguf \
+  --mmproj mmproj-Qwythos-9B-Claude-Mythos-5-1M-f16.gguf \
+  --image ./photo.jpg \
+  -p "Describe this image in detail." \
+  --temp 0.6 --top-p 0.95 --top-k 20 \
+  -c 16384
+```
+
+### llama.cpp server (OpenAI-compatible API with images)
+
+```bash
+llama-server \
+  -m Qwythos-9B-Claude-Mythos-5-1M-Q4_K_M.gguf \
+  --mmproj mmproj-Qwythos-9B-Claude-Mythos-5-1M-f16.gguf \
+  -c 16384 --port 8080
+```
+
+Then POST to `/v1/chat/completions` with an image URL or base64 payload — the standard OpenAI vision API shape works.
+
+### LM Studio
+
+Load the text quant; LM Studio detects the matching `mmproj-*.gguf` in the same folder and enables the image-attach button automatically.
+
+### What vision unlocks
+
+Since Qwythos inherits its vision tower unchanged from Qwen3.5-9B base, expect Qwen3.5-9B's documented vision capabilities: detailed image description, OCR (printed + handwritten), chart/table reading, UI/document understanding, basic spatial reasoning.
+
+**Honest note:** the SFT used to produce Qwythos was **text-only** — we did not fine-tune the vision tower or train on any image-paired data. Image-grounded reasoning therefore inherits the base model's behavior; it has not been independently evaluated as part of this release. If your application is *primarily* vision-driven, validate on your own use case first.
+
+---
+
 ## Sampling recommendations
 
 Qwythos is a reasoning model — every response opens with a `<think>...</think>` block before the final answer. Use these settings as defaults:
@@ -146,4 +197,5 @@ Weights are released under **Apache-2.0**, inherited from the Qwen3.5-9B base. S
 - Developed and released by [Empero](https://empero.org)
 - Base model: [Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) (Alibaba Qwen team)
 - Quantization: [llama.cpp](https://github.com/ggml-org/llama.cpp) (ggml-org)
+- Vision projector (`mmproj`): inherited from Qwen3.5-9B (vision tower unchanged); F16 GGUF re-hosted with thanks to [Unsloth](https://huggingface.co/unsloth) for the original conversion
 - HF model: [empero-ai/Qwythos-9B-Claude-Mythos-5-1M](https://huggingface.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M)