Release 2.0.4-beta.9: Audio transcription via mlx-audio

Major Features:
- Audio transcription via mlx-audio backend (Whisper, >10min duration)
- OpenAI /v1/audio/transcriptions endpoint
- Memory Gate System (Vision: 8GB, Audio: 4GB)
- Config-based backend routing (ADR-020)
- Benchmark toolchain (memmon/memplot, Schema v0.2.2)

Key Fixes:
- EuroLLM tokenizer decoding
- Vision-model text-only routing regression
- Multimodal model context length detection
- Memory cleanup bug (mx.metal.clear_cache)
- Orphan process bug

Test Results:
- Unit tests: 647 passed, 11 skipped (Python 3.10-3.12)
- wet-umbrella: 171 passed total

See CHANGELOG.md for complete details and known issues.

TESTING.md

@@ -40,7 +40,7 @@ When dependencies like `transformers` or `mlx-lm` update their APIs, unit tests
 ## Quick Start
 
 ```bash
-# Install package + development tools
+# Install package + development tools (text-only tests)
 pip install -e ".[dev,test]"
 
 # Run default test suite (isolated, no live downloads)
@@ -52,6 +52,9 @@ ruff check mlxk2/ --fix && mypy mlxk2/ && pytest -v
 
 **That's it!** Default tests use isolated caches and MLX stubs - no model downloads required.
 
+> **Vision + Audio Tests:** For complete development setup including Vision and Audio,
+> see **[README.md → Development Installation](README.md#development-installation)**.
+
 ## Running All Real Tests
 
 **Single command (recommended):**