Open ASR Leaderboard: Trends and Insights with New Multilingual & Long-Form Tracks

Back to Articles Open ASR Leaderboard: Trends and Insights with New Multilingual & Long-Form Tracks Published November 21, 2025 Update on GitHub Upvote 25 +19 Eric Bezzam bezzam Follow Steven Zheng Steveeeeeeen Follow Eustache Le Bihan eustlb Follow Vaibhav Srivastav reach-vb Follow While everyone (and their grandma 👵) is spinning up new ASR models, picking the right one for your use case can feel more overwhelming than choosing your next Netflix show. As of 21 Nov 2025, there are 150 Audio-Text-to-Text and 27K ASR models on the Hub 🤯 Most benchmarks focus on short-form English transcription (<30s), and overlook other important tasks, such as (1) multilingual performance and (2) model throughput, which can a be deciding factor for long-form audio like meetings and podcasts. Over the past two years, the Open ASR Leaderboard has become a standard for comparing open and closed-source models on both accuracy and efficiency. Recently, multilingual and long-form transcription tracks have been added to the leaderboard 🎉 TL;DR - Open ASR Leaderboard 📝 New preprint on ASR trends from the leaderboard: https://hf.co/papers/2510.06961 🧠 Best accuracy: Conformer encoder + LLM decoders (open-source ftw 🥳) ⚡ Fastest: CTC / TDT decoders 🌍 Multilingual: Comes at the cost of single-language performance ⌛ Long-form: Closed-source systems still lead (for now 😉) 🧑‍💻 Fine-tuning guides (Parakeet, Voxtral, Whisper): to continue pushing performance Takeaways from 60+ models As of 21 Nov 2025, the...