Qwen
Qwen3-ASR-1.7B
2.3B parameters · Base · Qwen3 family
Recommended download
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.
We don't have architecture data for this model, so we can't estimate whether it fits your hardware.
| 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 |
GGUF · Q8_0
2.02 GB
- 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.
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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
Context / KV 8,192 tokens · FP16 set above the quant table
Generic commands. We don't have architecture data for this model, so we can't estimate whether it fits your hardware.
llama-server -m Qwen3-ASR-1.7B-Q8_0.gguf -c 8192 -ngl 999Use llama-cli in place of llama-server for a one-shot prompt.
FROM ./Qwen3-ASR-1.7B-Q8_0.gguf
PARAMETER num_ctx 8192
PARAMETER num_gpu 999
PARAMETER stop "<|im_end|>"
PARAMETER stop "<|endoftext|>"
PARAMETER temperature 0.000001
# Chat template: Ollama uses the template embedded in the GGUF (no TEMPLATE directive needed).ollama create qwen-qwen3-asr-1-7b -f Modelfileollama run qwen-qwen3-asr-1-7bGGUF 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.
transformers does not load GGUF weights.
GGUF weights run under llama.cpp, Ollama or LM Studio.
Load Qwen3-ASR-1.7B-Q8_0.gguf, set the context length to 8192 tokens. Set GPU offload to Max (all layers).
MLX runs MLX-format weights only (Apple Silicon). This quant is a GGUF build.
GGUF weights run under llama.cpp, Ollama or LM Studio.
Technical details
Sampling defaults
- temperature
- 1.0E-6
Stop strings
<|im_end|>
<|endoftext|>
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
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