Qwen2.5 Omni 7B — Hardware Requirements & GPU Compatibility
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Qwen2.5-Omni-7B is Alibaba's 10.7-billion-parameter flagship in the Qwen2.5-Omni family, an end-to-end model that perceives text, images, audio, and video and generates both text and natural streaming speech in response. It shares the family's Thinker-Talker design and TMRoPE positional scheme for synchronizing audio and video timestamps, tuned for low-latency, real-time conversation rather than turn-based chat alone. At just under 11 billion parameters, it needs a single mainstream-to-high-end consumer GPU once quantized. Its language backbone carries a 32,768 token context window. It is released under Alibaba's Qwen Research License, a non-commercial license limited to research and evaluation rather than the Apache 2.0 used for Qwen's text-only models. Published in March 2025, it was the first Omni release, with the smaller 3B variant following about a month later.
338.0K downloads
1.9K likesSpecifications
- Publisher
- Alibaba
- Family
- Qwen 2.5
- Parameters
- 10.7B
- Architecture
- Qwen2_5OmniModel
- Release Date
- 2025-03-22
- License
- Other
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HuggingFace
How Much VRAM Does Qwen2.5 Omni 7B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 5.0 GB | — | 4.56 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 5.2 GB | — | 4.70 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 5.8 GB | — | 5.23 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 7.1 GB | — | 6.44 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 8.4 GB | — | 7.65 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 9.7 GB | — | 8.85 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 11.8 GB | — | 10.73 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Qwen2.5 Omni 7B?
Q4_K_M · 7.1 GBQwen2.5 Omni 7B (Q4_K_M) requires 7.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 10+ GB is recommended. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Qwen2.5 Omni 7B?
Q4_K_M · 7.1 GB55 devices with unified memory can run Qwen2.5 Omni 7B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, iPad Pro M5 13" (16 GB).
Runs great
— Plenty of headroomWhere to Download Qwen2.5 Omni 7B
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
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Frequently Asked Questions
- How much VRAM does Qwen2.5 Omni 7B need?
Qwen2.5 Omni 7B requires 7.1 GB of VRAM at Q4_K_M, or 23.6 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 10.7B × 4.8 bits ÷ 8 = 6.4 GB
KV Cache + Overhead ≈ 0.7 GB (at 2K context + ~0.3 GB framework)
VRAM usage by quantization
Q4_K_M7.1 GB- What's the best quantization for Qwen2.5 Omni 7B?
For Qwen2.5 Omni 7B, Q4_K_M (7.1 GB) offers the best balance of quality and VRAM usage. Q5_K_S (8.1 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 3.3 GB.
VRAM requirement by quantization
IQ2_XXS3.3 GBQ3_K_S5.2 GBQ4_16.6 GBQ4_K_M ★7.1 GBQ5_K_S8.1 GBBF1623.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen2.5 Omni 7B on a Mac?
Qwen2.5 Omni 7B requires at least 3.3 GB at IQ2_XXS, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Qwen2.5 Omni 7B locally?
Yes — Qwen2.5 Omni 7B can run locally on consumer hardware. At Q4_K_M quantization it needs 7.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen2.5 Omni 7B?
At Q4_K_M, Qwen2.5 Omni 7B can reach ~678 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~93 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 7.1 × 0.65 = ~735 tok/s
Estimated speed at Q4_K_M (7.1 GB)
~735 tok/s~93 tok/s~735 tok/s~678 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen2.5 Omni 7B?
At Q4_K_M, the download is about 6.44 GB. The full-precision BF16 version is 21.46 GB. The smallest option (IQ2_XXS) is 2.95 GB.
- Which GPUs can run Qwen2.5 Omni 7B?
52 consumer GPUs can run Qwen2.5 Omni 7B at Q4_K_M (7.1 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 38 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Qwen2.5 Omni 7B?
59 devices with unified memory can run Qwen2.5 Omni 7B at Q4_K_M (7.1 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.