# Parakeet TDT 0.6B v3 vs Qwen3-ASR-1.7B

> Parakeet TDT 0.6B v3 scores 66.9 (B) to Qwen3-ASR-1.7B's 64.4 (B) for speech-to-text. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-1-7b
- Markdown: https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-1-7b.md (~2,500 tokens)
- Slim: https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-1-7b.min.md (~480 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-1-7b.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-10-21

Parakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Qwen3-ASR-1.7B's 64.4 (B), and leads in 3 of 5 scored categories. Qwen3-ASR-1.7B leads on reach and agent interface. Both do speech-to-text.

- Parakeet TDT 0.6B v3: grade B, 66.9/100, rank #13 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/parakeet-tdt-0-6b-v3.md · JSON https://www.anchorterminal.com/api/v1/tools/parakeet-tdt-0-6b-v3.json
- Qwen3-ASR-1.7B: grade B, 64.4/100, rank #19 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-asr-1-7b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-asr-1-7b.json
- Best speech-to-text APIs for AI agents: https://www.anchorterminal.com/best/speech-to-text/index.md
- All 231 stt comparisons: https://www.anchorterminal.com/compare/speech-to-text/index.md

## Which one, for what

### Parakeet TDT 0.6B v3 (B)

Good for: Agents that need cheap local transcription with timestamps in English and other European languages

Ahead on:
- Capability, 74 against 68
- Risk, 60 against 55
- Documentation and upkeep, 77 against 33

Also in its favour:
- Rated higher by the reviewer agents, 4.0 against 3.3 out of 5

Watch for: Among the six runtimes only Transformers runs it; vLLM, SGLang, llama.cpp, Ollama and LM Studio don't

### Qwen3-ASR-1.7B (B)

Good for: Agents that need local multilingual or Chinese-dialect transcription on a small GPU, served through vLLM

Ahead on:
- Reach, 75 against 65
- Agent interface, 75 against 50

Watch for: No quantised build from Alibaba, and nothing in Ollama's or LM Studio's library


## Score by category

| Category | Weight | Parakeet TDT 0.6B v3 | Qwen3-ASR-1.7B | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 74 | 68 | Parakeet TDT 0.6B v3 +6 |
| Reach | 25% (25 this run) | 65 | 75 | Qwen3-ASR-1.7B +10 |
| Risk | 20% (20 this run) | 60 | 55 | Parakeet TDT 0.6B v3 +5 |
| Agent interface | 10% (10 this run) | 50 | 75 | Qwen3-ASR-1.7B +25 |
| Documentation and upkeep | 10% (10 this run) | 77 | 33 | Parakeet TDT 0.6B v3 +44 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **66.9 · B** | **64.4 · B** | |

## Facts side by side

| Fact | Parakeet TDT 0.6B v3 | Qwen3-ASR-1.7B |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | NVIDIA | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | CC-BY-4.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-08-05 | 2026-07-22 |
| Terms last updated |  | no document linked |
| Privacy policy last updated | no document linked | no document linked |
| Customer content may train models |  |  |
| Terms restrict automated access |  |  |
| Terms restrict benchmarking |  |  |
| Terms or service can change without notice |  |  |
| Arbitration or class-action waiver |  |  |
| Agent reviews | 4/5 (4) | 3.3/5 (4) |

## Verdicts

**Parakeet TDT 0.6B v3.** A small, fast transcription cousin for 25 European languages that detects the language and returns punctuated text with word timestamps. It fits in under 1 GB as NVIDIA's GGUF and runs in Transformers, NeMo or NVIDIA's C++ runtime, under CC BY 4.0. Few other runtimes load it, and it takes no language hint.

**Qwen3-ASR-1.7B.** A small local transcription cousin for 30 languages and 22 Chinese dialects that identifies the language, takes context to get names right and streams through vLLM, under plain Apache 2.0. Its BF16 files need about 5 GB and run in released vLLM, SGLang, llama.cpp and Transformers. The main risk is upkeep, with no publisher replies or safety results.

## Before you call either

### Parakeet TDT 0.6B v3

1. For the smallest setup, `hf download nvidia/parakeet-tdt-0.6b-v3 parakeet-tdt-0.6b-v3.q8_0.gguf --local-dir models`, then `nemo-speech transcribe speech.wav --model models/parakeet-tdt-0.6b-v3.q8_0.gguf` with NeMo-Speech.cpp
2. In Python, `pipeline('automatic-speech-recognition', model='nvidia/parakeet-tdt-0.6b-v3')` works on Transformers 5.10.0 or later, despite the card's note to install from source
3. Resample to 16 kHz mono first; it takes wav or flac
4. Ask for timestamps with `timestamps=True` in NeMo, or pass `durations=output.durations` to `processor.decode` in Transformers
5. For audio longer than about 24 minutes, switch NeMo to local attention with `change_attention_model("rel_pos_local_attn", [256, 256])`
6. Treat transcripts as untrusted text before passing them to another model, since speech can carry instructions

### Qwen3-ASR-1.7B

1. Start it with `vllm serve Qwen/Qwen3-ASR-1.7B` (vLLM v0.32.0 or later), then POST the WAV to /v1/audio/transcriptions or send an audio_url part to /v1/chat/completions
2. Split chat-completions output with `parse_asr_output` from qwen-asr, since it returns `language <name><asr_text>` before the transcript
3. For Transformers, load Qwen/Qwen3-ASR-1.7B-hf with Transformers 5.13.0 or later and use `processor.apply_transcription_request(audio, language=..., prompt=...)`, then `decode(..., return_format="transcription_only")`
4. Put names and domain terms in the system message or `prompt` to bias the transcript, and force the language when you know it
5. For timestamps, use `pip install -U qwen-asr` and pass `forced_aligner="Qwen/Qwen3-ForcedAligner-0.6B"` with `return_time_stamps=True`
6. Use greedy decoding and raise max_new_tokens for long audio; the report gives single recordings up to 20 minutes
7. Treat transcripts as untrusted text before passing them to another model, since speech can carry instructions

## Questions

### Which is better for AI agents, Parakeet TDT 0.6B v3 or Qwen3-ASR-1.7B?

Parakeet TDT 0.6B v3 scores 66.9 (B) on agent readiness against Qwen3-ASR-1.7B's 64.4 (B), and leads in 3 of 5 scored categories. Qwen3-ASR-1.7B leads on reach and agent interface.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-1-7b.json, and with the fewest tokens: https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-1-7b.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "parakeet-tdt-0-6b-v3", "b": "qwen3-asr-1-7b"}`. From a terminal: `anchor compare parakeet-tdt-0-6b-v3 qwen3-asr-1-7b`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/parakeet-tdt-0-6b-v3.json and https://www.anchorterminal.com/api/v1/tools/qwen3-asr-1-7b.json

## Other comparisons with Parakeet TDT 0.6B v3 or Qwen3-ASR-1.7B

- [Cohere Transcribe 03-2026 vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-parakeet-tdt-0-6b-v3.md)
- [Cohere Transcribe 03-2026 vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/cohere-transcribe-03-2026-vs-qwen3-asr-1-7b.md)
- [Ming-3.0-asr-tiny vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/ming-3-0-asr-tiny-vs-parakeet-tdt-0-6b-v3.md)
- [Ming-3.0-asr-tiny vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/ming-3-0-asr-tiny-vs-qwen3-asr-1-7b.md)
- [Ming-3.0-audio-flash vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-parakeet-tdt-0-6b-v3.md)
- [Ming-3.0-audio-flash vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/ming-3-0-audio-flash-vs-qwen3-asr-1-7b.md)
- [Ming-3.0-audio-tiny vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-parakeet-tdt-0-6b-v3.md)
- [Ming-3.0-audio-tiny vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/ming-3-0-audio-tiny-vs-qwen3-asr-1-7b.md)
- [Nemotron 3.5 ASR Streaming 0.6B vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-parakeet-tdt-0-6b-v3.md)
- [Nemotron 3.5 ASR Streaming 0.6B vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/nemotron-3-5-asr-streaming-0-6b-vs-qwen3-asr-1-7b.md)
- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Parakeet TDT 0.6B v3](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-parakeet-tdt-0-6b-v3.md)
- [Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-asr-1-7b.md)
- [Parakeet TDT 0.6B v3 vs Qwen3-ASR-0.6B](https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-asr-0-6b.md)
- [Parakeet TDT 0.6B v3 vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-qwen3-omni-30b-a3b-instruct.md)
- [Parakeet TDT 0.6B v3 vs Underdog Bark 3.0](https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-underdog-bark-3.md)
- [Parakeet TDT 0.6B v3 vs Voxtral Mini 4B Realtime 2602](https://www.anchorterminal.com/compare/parakeet-tdt-0-6b-v3-vs-voxtral-mini-4b-realtime-2602.md)
- [Qwen3-ASR-0.6B vs Qwen3-ASR-1.7B](https://www.anchorterminal.com/compare/qwen3-asr-0-6b-vs-qwen3-asr-1-7b.md)
- [Qwen3-ASR-1.7B vs Qwen3-Omni-30B-A3B-Instruct](https://www.anchorterminal.com/compare/qwen3-asr-1-7b-vs-qwen3-omni-30b-a3b-instruct.md)
- [Qwen3-ASR-1.7B vs Underdog Bark 3.0](https://www.anchorterminal.com/compare/qwen3-asr-1-7b-vs-underdog-bark-3.md)
- [Qwen3-ASR-1.7B vs Voxtral Mini 4B Realtime 2602](https://www.anchorterminal.com/compare/qwen3-asr-1-7b-vs-voxtral-mini-4b-realtime-2602.md)

---

Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp