# Gradium — How a benchmark change produced a faster TTS model

- Company: Gradium (gradium.ai)
- Announced: 2026-09-09
- Category: not stated
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://gradium.ai/blog/coval-perceived-ttfa-benchmark
- Record: https://forck.live/items/18302-how-a-benchmark-change-produced-a-faster-tts-model
- Subject: Gradium TTS / Phonon

Median TTFA against average word error rate per model, Coval TTS benchmark, 480 runs per model. The dotted line is the Pareto frontier; the dashed crosshair marks Gradium. Captured September 9, 2026. See the live leaderboard . A joint post by Coval and Gradium. On June 3, 2026, Gradium's time to first audio on the Coval TTS leaderboard moved from 171.9 ms to 429.6 ms. No model had shipped and no serving infrastructure had changed. Gradium's own instrumentation still reported 148 ms of network and synthesis latency, unchanged from the week before. Coval had changed their measurement methodology, and had started counting the silence at the start of the stream. Why Coval measures the full stack instead of isolating the model Most latency benchmarks try to isolate the model from the servers around it. Coval takes the opposite position. A benchmark should reflect how the whole stack feels to a user, because that is what the customer experiences, so Coval includes the network round trip in the latency number. Coval then goes one step further and processes the returned audio to find when speech actually starts. The change came from a pattern Coval kept seeing. …

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