Qwen

Qwen3-ASR-1.7B

Name: Qwen3-ASR-1.7B
Author: Qwen

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2.3B parameters · Base · Qwen3 family

apache-2.0 hash verified source matched revision pinned

Which version should I download?

Default pick: GGUF · Q8_0 — Q8_0 GGUF (ggml-org, converted from official Qwen/Qwen3-ASR-1.7B) — near-lossless 8-bit lead for the 1.7B automatic-speech-recognition model; audio mmproj (Q8_0) bundled. Repo ships no plain Q4_K_M; Q8_0 is the accessible lead.

Set your rig to confirm it fits and to see if a higher-quality quant runs fully on your hardware.

Set your rig

Quantizations

Why these quants? Which quant should I pick?

Format	Level	Size	Verdict	Est. speed	Quality note	Swarm	Download
GGUF	Q8_0	2.02 GB	Set your rig	—	Q8_0 GGUF (ggml-org, converted from official Qwen/Qwen3-ASR-1.7B) — near-lossless 8-bit lead for the 1.7B automatic-speech-recognition model; audio mmproj (Q8_0) bundled. Repo ships no plain Q4_K_M; Q8_0 is the accessible lead.	2S / 0L webseed OK	Magnet .torrent

GGUF · Q8_0

2.02 GB

Set your rig

Est. speed: —
Swarm: 2S / 0L webseed OK

Q8_0 GGUF (ggml-org, converted from official Qwen/Qwen3-ASR-1.7B) — near-lossless 8-bit lead for the 1.7B automatic-speech-recognition model; audio mmproj (Q8_0) bundled. Repo ships no plain Q4_K_M; Q8_0 is the accessible lead.

Magnet .torrent

Run it

Runtime completeness (Q8_0 torrent): llama.cpp ✅ Ollama – vision sidecar –

– Ollama — runs the GGUF directly; no Modelfile bundled
– vision sidecar — not a vision model

Quant

Context / KV 8,192 tokens · FP16 set above the quant table

Generic commands (no rig set). GPU-offload values assume the model fits on your GPU — set your rig for values tuned to your hardware.

Start the server

llama-server -m Qwen3-ASR-1.7B-Q8_0.gguf -c 8192 -ngl 999

Use llama-cli in place of llama-server for a one-shot prompt.

Save as Modelfile next to the GGUF (Modelfile)

FROM ./Qwen3-ASR-1.7B-Q8_0.gguf
PARAMETER num_ctx 8192
PARAMETER num_gpu 999

Create

ollama create qwen-qwen3-asr-1-7b -f Modelfile

Run

ollama run qwen-qwen3-asr-1-7b

GGUF is not a first-class vLLM format.

vLLM GGUF support is experimental and single-file only; prefer safetensors/GPTQ/AWQ for production. If you must, pass the .gguf path to `vllm serve` with --load-format gguf on a recent vLLM.

Load Qwen3-ASR-1.7B-Q8_0.gguf, set the context length to 8192 tokens. Set GPU offload to Max (all layers).

Not an MLX-format quant.

MLX runs MLX-format weights only (Apple Silicon). This quant is not an MLX build.

Technical details

No template or sampling metadata recorded.

Evidence & provenance

Source

Provenance: https://huggingface.co/Qwen/Qwen3-ASR-1.7B
Revision pin: 7278e1e70fe206f11671096ffdd38061171dd6e5
Manifest: Present

License

Name: apache-2.0
Commercial use: yes
Access: Open

File hashes (SHA-256)

qwen3-asr-1.7b-q8-0/LICENSE cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30
qwen3-asr-1.7b-q8-0/Qwen3-ASR-1.7B-Q8_0.gguf 58e22d0532d4eacaf034cfac17a6fed159f37c41390c710186783be439d1fc57
qwen3-asr-1.7b-q8-0/README.md 0d9910d9a297a4b92d46094d03e26b948614b6afd429499199c5a449274d2995
qwen3-asr-1.7b-q8-0/mmproj-Qwen3-ASR-1.7B-Q8_0.gguf 46c1d533af3f354ceb37ce855dbceff7da7fa7cf1e6a523df3b13440bd164c0d

Performance reports

Real-world throughput reported by the community (and scraped sources).

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Reviews & presets

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Sampler presets

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Community runtime reports

Unofficial, community-submitted "it loads for me" reports. These are not the official verified-working badge — an admin reviews reports before anything is marked officially verified.

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