Photon can now hear.
Photon 2.1 adds automatic speech recognition for Whisper large-v3-turbo, Qwen3-ASR 0.6B and 1.7B, and Parakeet TDT 0.6B v3, with performance beating competitors by up to 3.1×.
It also adds NVIDIA B200 support across every Photon model. Under the hood, this release extends Photon's compiler and megakernel architecture to speech recognition and NVIDIA Blackwell.
Speech recognition
Photon now transcribes both long-form audio files and live PCM streams. Transcripts stream back as the audio arrives, making Photon suitable for live agents, meeting transcription, voice interfaces, and other latency-sensitive applications.
Progressive results include segment timestamps. Depending on the model, Photon also supports word timestamps, language detection, and prompts for domain-specific vocabulary.
Photon is built for latency-sensitive workloads. We tested all four ASR models at concurrency 1 and 8 on both H100 and B200. Photon won all 16 configurations. Speedups ranged from 1.2× for Qwen3-ASR 1.7B against Qwen's qwen-asr stack on H100 at concurrency 1, to 3.1× for Whisper against vLLM on B200 at concurrency 1. Full results are on the benchmarks page.
Built for B200
Photon 2.1 brings the full model catalog to NVIDIA B200. Across every tested model and batch sizes 1, 2, 4, and 8, Photon beat vLLM and SGLang in 51 of 52 matched tests, by up to 2.8×.
The work behind B200 support also lays the foundation for more Blackwell GPUs.
Why it's faster
Photon is built differently from other inference engines. It uses a custom compiler that generates optimized GPU megakernels for each model and chip. Megakernels fuse all GPU operations into a single call, instead of dispatching long chains of separate kernels. This reduces launch overhead and data movement, especially at the low batch counts common in live audio.
How to get it
Photon 2.1 is available today. Install or upgrade with pip install --upgrade moondream. Docs are at docs.moondream.ai. Happy Moondreaming.