Parakeet TDT 0.6B v3
NVIDIA's multilingual speed flagship — 25 European languages, TDT transducer with native word timestamps
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Why it fits
Parakeet TDT 0.6B v3 is NVIDIA's 600M-parameter multilingual speech-recognition model, extending
the English-only v2 to 25 European languages using the Granary multilingual corpus (~660k hours of
pseudo-labeled speech plus ~10k hours of human transcriptions). Architecturally it pairs a
FastConformer encoder with a Token-and-Duration Transducer (TDT) decoder: each decode step
predicts both the next token and how many 80 ms frames it occupies, then skips ahead by that duration —
which is what makes the family a speed benchmark for local transcription, and what gives it
model-native word timestamps. The model auto-detects the spoken language, preserves punctuation and
capitalization, and is released under the permissive CC-BY-4.0 license. This OpenASR repo repackages
the weights as .oasr packs that run natively in the OpenASR runtime — no Python at inference time,
all decoding local. The q8_0 build is the recommended default; q4_k is the smallest build for
tight-memory devices and fp16 is for maximum fidelity or verification.
What you can do with it
- 🇪🇺 25 European languages — one 0.6B checkpoint covers bg/hr/cs/da/nl/en/et/fi/fr/de/el/hu/it/lv/lt/mt/pl/pt/ro/sk/sl/es/sv/ru/uk, auto-detecting the spoken language with no prompting
- ⚡ Built for throughput — the Token-and-Duration Transducer (TDT) decoder predicts how many frames each token spans and skips ahead, cutting decode steps versus conventional transducers
- 🕑 Native word timestamps — the duration head is the model's own alignment output, so word-level timings come from the model rather than a uniform approximation
- ✍️ Punctuation and capitalization — trained on transcripts that preserve both (Granary + NeMo ASR Set 3.0; ~670k hours), so the raw decode reads like text
Other models
Developer details CLI commands, file hashes, and per-quant downloads — for scripting and verification.
Model facts
Usage
These are CLI / local-server examples. The desktop app runs this model without typing a command — use Install above.
$ openasr pull parakeet-tdt-0.6b-v3:q8 ↓ parakeet-tdt-0.6b-v3.oasr 876.6 MB ✓ verified sha256 $ openasr transcribe meeting.wav --backend native --model-pack ~/.openasr/models/parakeet-tdt-0.6b-v3/q8_0/parakeet-tdt-0.6b-v3-q8_0.oasr ✓ local transcript · 0 bytes sent
$ openasr serve --backend native --model-pack ~/.openasr/models/parakeet-tdt-0.6b-v3/q8_0/parakeet-tdt-0.6b-v3-q8_0.oasr --addr 127.0.0.1:8080 ▶ http://127.0.0.1:8080 · model=parakeet-tdt-0.6b-v3 · 0 bytes will leave this host
from openai import OpenAI client = OpenAI(base_url="http://127.0.0.1:8080/v1", api_key="local") audio = open("meeting.wav", "rb") text = client.audio.transcriptions.create(model="parakeet-tdt-0.6b-v3", file=audio)