Add F5-TTS as tts-1-f5 engine (additive, alongside tts-1-qwen)

docs/MODELS.md

@@ -125,6 +125,66 @@ make test-qwen   # Test Qwen3-TTS explicitly
 
 ---
 
+### F5-TTS ✅ (also enabled by default)
+
+**Status:** INTEGRATED as tts-1-f5 (additive, alongside tts-1-qwen)
+**Project:** SWivid/F5-TTS (community-maintained, gated HuggingFace checkpoint)
+**License:** MIT (model + code)
+**Model:** F5-TTS_v1
+
+**Why Integrated:**
+- Empirical benchmark (Richard, 2026-05-23): faster inference + better voice clones than Qwen3-TTS on the same reference clips
+- Smaller model (~336M params vs Qwen3-TTS 1.7B) — lower VRAM, fits comfortably on modest GPUs
+- Flow-matching architecture, zero-shot cloning, no fine-tuning needed
+- 24kHz output, matches Qwen3-TTS sample rate (drop-in voice swap for clients)
+
+**Model Specs:**
+- Parameters: ~336M
+- Sample Rate: 24kHz
+- Input: Text + Reference Audio (3+ seconds) + Reference Transcript
+- Languages: English (primary); community fine-tunes available for others
+- Size: ~1.5GB (F5-TTS_v1 + Vocos vocoder)
+
+**Model Source:**
+- HuggingFace: `SWivid/F5-TTS` (**gated** — accept license at https://huggingface.co/SWivid/F5-TTS)
+- Auto-downloaded on first use; requires `HF_TOKEN` env var
+
+**Integration:**
+- Used for `tts-1-f5` model (additive default)
+- Voice cloning with `ref_audio` + `ref_text` (same shape as tts-1-qwen)
+- Reuses the same 40 LibriSpeech voices as tts-1-qwen
+
+**Example Config:**
+```yaml
+tts-1-f5:
+  aria:
+    ref_audio: cloned-voices/aria.wav
+    ref_text: "BUT THE WINDOWS ARE PATCHED WITH WOODEN PANES AND THE DOOR I THINK IS LIKE THE GATE IT IS NEVER OPENED"
+    language: English
+```
+
+**Tuning Knobs (engine-specific, not OpenAI-compatible):**
+- `nfe_step` (default 32) — ODE step count; higher = better quality, slower
+- `cfg_strength` (default 2.0) — classifier-free guidance strength
+- `speed` (default 1.0) — pitch-preserving speed multiplier
+- Does NOT support `temperature` / `top_p` / `top_k` (flow-matching, not autoregressive)
+
+**Makefile Targets:**
+```bash
+make test-f5     # Test F5-TTS voice cloning
+```
+
+**Hardware Requirements:**
+- GPU: NVIDIA with 4GB+ VRAM (lighter than Qwen3-TTS)
+- CPU: Works but many× realtime
+- MPS (Apple Silicon): supported, ~1.5–2× realtime per VoiceClone benchmarks
+
+**Source of Inspiration:** [MonumentalSystems/VoiceClone](https://github.com/MonumentalSystems/VoiceClone) — a single-file F5-TTS web app that proved the engine on our reference workload. Our wrapper mirrors their `F5TTS.infer()` call pattern.
+
+**Raccoon Priority:** ⭐⭐⭐⭐⭐ (Empirically beats current default, MIT, lower VRAM)
+
+---
+
 ### 1. Piper TTS (disabled by default) ✅
 
 > 📖 **See [detailed documentation](models/piper-tts.md)** for comprehensive technical specs and integration guide