Model reference · open weights
Qwen3-Omni is an open-weight language model from marksverdhei, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
Qwen3-Omni-30B-A3B-FP8 Block-wise FP8 quantization of Qwen/Qwen3-Omni-30B-A3B-Instruct. Model Details Components Quantized to FP8: - Thinker (48 layers MoE) - main language model - Talker (20 layers MoE) - audio generation model Kept in BF16: - Vision encoder (thinker.visual) - Audio tower (thinker.audiotower) - Code2Wav decoder (code2wav) - Embedding layers - LayerNorm layers - MoE gate routing layers Usage with vLLM Requirements - vLLM = 0.13.0 with Qwen3-Omni support - 2x 24GB GPUs (e.g., RTX 3090) or equivalent - ~35 GB disk space Quantization Details Block-wise quantization with 128x128 blocks provides better precision than per-tensor quantization while maintaining good compression. Each block has its own scale factor stored as weightscaleinv (inverse scale for efficient multiplication during inference). Original Model This is a quantized version of Qwen/Qwen3-Omni-30B-A3B-Instruct. Qwen3-Omni is a natively end-to-end multilingual omni-modal foundation model that processes text, images, audio, and video, and delivers real-time streaming responses in both text and natural speech. Key Features: - State-of-the-art across modalities - Supports 119 text languages, 19 speech input languages, and 10 speech output languages - MoE-based Thinker-Talker architecture - Real-time audio/video interaction For full details, see the original model card.
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | marksverdhei |
|---|---|
| Type | Language models |
| Parameters (lead) | 35.3B |
| Variants | 1 |
| Runs with | transformers |
| Based on | Qwen/Qwen3-Omni-30B-A3B-Instruct |
| Released | 2026-01-20 |
| Popularity | 51k downloads / month |
| Likes | 4 |
| Licence | Commercial licence needed |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| Qwen3-Omni-30B-A3B-FP8 | 35.3B | FP8 | ~40.5 GB | — | Weights ↗ |
Using it via the API
Once AxForge deploys marksverdhei-qwen3-omni for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (marksverdhei-qwen3-omni below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"marksverdhei-qwen3-omni","messages":[{"role":"user","content":"Hello"}]}'
Details
Languages
Tags
Licence
The weights are open but its licence needs a commercial agreement for business use. AxForge can arrange that licence and host the model for you — you pay AxForge, we settle with the model’s maker. Ask us for a quote. Read the licence ↗