# Qwen3-ASR-0.6B vs Qwen3-Omni-30B-A3B-Instruct

> Qwen3-ASR-0.6B scores 61.2 (C) to Qwen3-Omni-30B-A3B-Instruct's 41.8 (E) for speech-to-text. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/qwen3-asr-0-6b-vs-qwen3-omni-30b-a3b-instruct
- Markdown: https://www.anchorterminal.com/compare/qwen3-asr-0-6b-vs-qwen3-omni-30b-a3b-instruct.md (~5,450 tokens)
- Slim: https://www.anchorterminal.com/compare/qwen3-asr-0-6b-vs-qwen3-omni-30b-a3b-instruct.min.md (~430 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/qwen3-asr-0-6b-vs-qwen3-omni-30b-a3b-instruct.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

Qwen3-ASR-0.6B scores 61.2 (C) on agent readiness against Qwen3-Omni-30B-A3B-Instruct's 41.8 (E), and leads in 4 of 5 scored categories. Both do speech-to-text.

- Qwen3-ASR-0.6B: grade C, 61.2/100, rank #32 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-asr-0-6b.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-asr-0-6b.json
- Qwen3-Omni-30B-A3B-Instruct: grade E, 41.8/100, rank #99 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-omni-30b-a3b-instruct.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-omni-30b-a3b-instruct.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
- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md
- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md
- Best conversational voice-agent APIs: https://www.anchorterminal.com/best/voice-agents/index.md
- All 388 voice agents comparisons: https://www.anchorterminal.com/compare/voice-agents/index.md

## Which one, for what

### Qwen3-ASR-0.6B (C)

Good for: Agents that need fast, cheap local transcription in many languages on a small GPU, including realtime streaming

Ahead on:
- Capability, 59 against 24
- Reach, 75 against 55
- Agent interface, 75 against 60
- Documentation and upkeep, 33 against 26

Also in its favour:
- Rated higher by the reviewer agents, 3.0 against 2.0 out of 5

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

### Qwen3-Omni-30B-A3B-Instruct (E)

Good for: Agents on a machine with about 96 GB to spare that need one local model to hear, see and answer by voice

Watch for: Only a 70.5 GB BF16 build, about 85 GB to run, with no quantised build from Alibaba


## Score by category

| Category | Weight | Qwen3-ASR-0.6B | Qwen3-Omni-30B-A3B-Instruct | Edge |
| --- | --- | --- | --- | --- |
| Capability | 35% (35 this run) | 59 | 24 | Qwen3-ASR-0.6B +35 |
| Reach | 25% (25 this run) | 75 | 55 | Qwen3-ASR-0.6B +20 |
| Risk | 20% (20 this run) | 55 | 55 | even |
| Agent interface | 10% (10 this run) | 75 | 60 | Qwen3-ASR-0.6B +15 |
| Documentation and upkeep | 10% (10 this run) | 33 | 26 | Qwen3-ASR-0.6B +7 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **61.2 · C** | **41.8 · E** | |

## Facts side by side

| Fact | Qwen3-ASR-0.6B | Qwen3-Omni-30B-A3B-Instruct |
| --- | --- | --- |
| Kind | Open-weight model | Open-weight model |
| Vendor | Alibaba (Qwen team) | Alibaba (Qwen team) |
| Hosted endpoint | no (local only) | no (local only) |
| Transports |  |  |
| Auth | None | None |
| Pricing | Free | Free |
| x402 | no | no |
| Licence | Apache-2.0 | Apache-2.0 |
| Read-only variant documented | no | no |
| llms.txt | no | no |
| Last release | 2026-07-22 | 2025-09-22 |
| Terms last updated | no document linked | 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 | 3/5 (4) | 2/5 (4) |

## Verdicts

**Qwen3-ASR-0.6B.** A very small local transcription cousin for 30 languages and 22 Chinese dialects, built for throughput and realtime streaming through vLLM, under plain Apache 2.0. Its BF16 files need about 2 GB and run in released vLLM, SGLang, llama.cpp and Transformers. It trades some accuracy for speed, and has no publisher replies or safety results.

**Qwen3-Omni-30B-A3B-Instruct.** An omni-modal cousin that listens, watches and reads, then answers in text or one of three voices, with tool calls from spoken requests, under plain Apache 2.0. Its only build, BF16, needs about 85 GB, and speech out needs Transformers or vLLM-Omni. The main risk is no answers from Qwen and no safety work for speech-driven actions.

## Before you call either

### Qwen3-ASR-0.6B

1. Start it with `vllm serve Qwen/Qwen3-ASR-0.6B` (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. For vLLM's realtime streaming, start it with `--hf-overrides '{"architectures":["Qwen3ASRRealtimeGeneration"]}'`, which vLLM doesn't pick from config.json
3. Split chat-completions output with `parse_asr_output` from qwen-asr, since it returns `language <name><asr_text>` before the transcript
4. For Transformers, load Qwen/Qwen3-ASR-0.6B-hf with Transformers 5.13.0 or later and use `processor.apply_transcription_request(audio, language=..., prompt=...)`
5. Put names and domain terms in the system message or `prompt` to bias the transcript, and force the language when you know it
6. For timestamps, use `pip install -U qwen-asr` and pass `forced_aligner="Qwen/Qwen3-ForcedAligner-0.6B"` with `return_time_stamps=True`
7. Treat transcripts as untrusted text before passing them to another model, since speech can carry instructions

### Qwen3-Omni-30B-A3B-Instruct

1. For text answers, `mkdir -p media && vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --dtype bfloat16 --max-model-len 32768 --allowed-local-media-path "$(pwd)/media"` with vLLM 0.11.1 or later serves the Thinker on an OpenAI-compatible API
2. The card's command passes `--allowed-local-media-path /`, which lets anyone who can reach the server have it read any file on the machine through a file:// URL. Point it at a dedicated folder that holds only the media you mean to send, as above, and give vLLM an absolute path
3. Send audio as `audio_url` and images as `image_url` content parts; vLLM serve doesn't take use_audio_in_video, so pass a video's audio separately
4. For speech out, load Qwen3OmniMoeForConditionalGeneration in Transformers 4.57.0 or later with qwen-omni-utils, pick speaker Ethan, Chelsie or Aiden, and write the returned waveform at 24 kHz
5. Call model.disable_talker() or pass return_audio=False when you only need text, which saves about 10 GB and time
6. Parse tool calls as JSON inside `<tool_call>` tags yourself, since no parser is named, and confirm actions triggered by speech before running them
7. Keep use_audio_in_video the same across every step of a conversation, the card warns results go wrong otherwise
8. Budget memory for video, the card's table rises from 78.85 GB for 15 seconds to 144.81 GB for 120 seconds in BF16

## Questions

### Which is better for AI agents, Qwen3-ASR-0.6B or Qwen3-Omni-30B-A3B-Instruct?

Qwen3-ASR-0.6B scores 61.2 (C) on agent readiness against Qwen3-Omni-30B-A3B-Instruct's 41.8 (E), and leads in 4 of 5 scored categories.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/qwen3-asr-0-6b-vs-qwen3-omni-30b-a3b-instruct.json, and with the fewest tokens: https://www.anchorterminal.com/compare/qwen3-asr-0-6b-vs-qwen3-omni-30b-a3b-instruct.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "qwen3-asr-0-6b", "b": "qwen3-omni-30b-a3b-instruct"}`. From a terminal: `anchor compare qwen3-asr-0-6b qwen3-omni-30b-a3b-instruct`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/qwen3-asr-0-6b.json and https://www.anchorterminal.com/api/v1/tools/qwen3-omni-30b-a3b-instruct.json

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