audio.cpp consolidates 12 audio models—including Qwen3-TTS, PocketTTS, and VeVo2—into a unified C++/ggml runtime, achieving 5x faster TTS inference compared to framework defaults. This matters because local TTS inference has fragmented across multiple runtime dependencies (Python frameworks, model-specific loaders, varying quantization support). A consolidated runtime reduces operational surface area for offline speech applications and lowers the infrastructure cost of deploying multiple audio models in production systems. For operators managing multi-model inference pipelines, runtime unification directly improves system observability and failure isolation. For builders, the practical shift is immediate: TTS inference moves from framework-dependent pipelines to a portable C++ binary with predictable performance characteristics. This eliminates the need to maintain separate Python environments or framework integrations per model. The 5x speedup reduces both latency and compute cost per inference, making local TTS viable for real-time applications previously requiring cloud APIs. Runtime consolidation also signals that quantized audio models are approaching parity with full-precision alternatives—operators can now standardize on single-runtime deployments rather than maintaining parallel inference paths.