# Qwen3.5-122B-A10B

> OnPrem World · https://onpremworld.com/en/models/qwen3.5-122b-a10b · Last updated: 2026-10-14 · CC BY 4.0

A 122B MoE with 10B active: a model for 128 GB unified-memory machines or a 96 GB workstation card.

|  |  |
|---|---|
| Developer | Alibaba Qwen |
| Parameters | 122B (10B active, MoE) |
| Native context | 262,144 tokens |
| Licence | Apache-2.0 |
| Commercial use | Yes |
| KV cache | 12 of 48 layers (the rest are linear attention with a fixed-size state) |
| Released | 2026-02 |

```
ollama run qwen3.5:122b
```

## Memory needed

Weights + KV cache + runtime overhead, in GiB. Lower quantization = less memory, slightly lower quality.

| Quantization | 4K | 8K | 32K |
|---|---|---|---|
| Q4_K_M | 72.9 GiB | 73.0 GiB | 73.6 GiB |
| Q5_K_M | 85.4 GiB | 85.5 GiB | 86.1 GiB |
| Q6_K | 98.9 GiB | 99.0 GiB | 99.5 GiB |
| Q8_0 | 127.4 GiB | 127.4 GiB | 128.0 GiB |
| FP16 | 239.2 GiB | 239.3 GiB | 239.9 GiB |

## Which hardware runs it (8K)

| Hardware | Memory | Best quant | tok/s (est.) |
|---|---|---|---|
| RTX PRO 6000 Blackwell Workstation Edition | 96 GB | Q5_K_M | 176 |
| M5 Max (18-core CPU / 40-core GPU) | 128 GB | Q5_K_M | 56 |
| M4 Max (16-core CPU / 40-core GPU) | 128 GB | Q5_K_M | 50 |
| M5 Ultra | 512 GB | FP16 | 39 |
| M3 Ultra | 512 GB | FP16 | 27 |
| RTX Spark (N1X) laptops & compact desktops | 128 GB | Q5_K_M | 25 |
| DGX Spark | 128 GB | Q5_K_M | 23 |
| Ryzen AI Max+ 395 (Strix Halo) systems | 128 GB | Q5_K_M | 22 |
| Ryzen AI Max+ PRO 495 (Gorgon Halo) systems | 192 GB | Q8_0 | 15 |
| GeForce RTX 3060 (12 GB) | 12 GB | Doesn't fit | – |
| GeForce RTX 3090 | 24 GB | Doesn't fit | – |
| GeForce RTX 4060 Ti 16GB | 16 GB | Doesn't fit | – |
| GeForce RTX 4080 SUPER | 16 GB | Doesn't fit | – |
| GeForce RTX 4090 | 24 GB | Doesn't fit | – |
| GeForce RTX 5060 Ti 16GB | 16 GB | Doesn't fit | – |
| GeForce RTX 5070 | 12 GB | Doesn't fit | – |
| GeForce RTX 5070 Ti | 16 GB | Doesn't fit | – |
| GeForce RTX 5080 | 16 GB | Doesn't fit | – |
| GeForce RTX 5090 | 32 GB | Doesn't fit | – |
| Radeon RX 7900 XT | 20 GB | Doesn't fit | – |
| Radeon RX 7900 XTX | 24 GB | Doesn't fit | – |
| Radeon RX 9060 XT 16GB | 16 GB | Doesn't fit | – |
| Radeon RX 9070 XT | 16 GB | Doesn't fit | – |
| Arc B580 | 12 GB | Doesn't fit | – |
| RTX A6000 | 48 GB | Doesn't fit | – |
| RTX 6000 Ada Generation | 48 GB | Doesn't fit | – |
| RTX PRO 5000 72GB Blackwell | 72 GB | Doesn't fit | – |
| Radeon AI PRO R9700 | 32 GB | Doesn't fit | – |
| Arc Pro B60 | 24 GB | Doesn't fit | – |
| Arc Pro B70 | 32 GB | Doesn't fit | – |
| M4 Pro | 64 GB | Doesn't fit | – |
| M4 Max (14-core CPU / 32-core GPU) | 36 GB | Doesn't fit | – |
| M5 | 32 GB | Doesn't fit | – |
| M5 Pro | 64 GB | Doesn't fit | – |
| M5 Max (18-core CPU / 32-core GPU) | 36 GB | Doesn't fit | – |
| M6 (16GB configuration, 153 GB/s) | 16 GB | Doesn't fit | – |
| M6 (24GB/32GB configurations, 170 GB/s) | 32 GB | Doesn't fit | – |

## Frequently asked questions

### How much VRAM does Qwen3.5-122B-A10B need?

With an 8K context, about 73.0 GiB at Q4_K_M and 127.4 GiB at Q8_0 (weights + KV cache + runtime overhead). Longer contexts need more memory for the KV cache.

### Can Qwen3.5-122B-A10B run on an GeForce RTX 4090?

Qwen3.5-122B-A10B does not fit on the GeForce RTX 4090 (24 GB), even at Q4_K_M with an 8K context.

### Can I run Qwen3.5-122B-A10B on a Mac?

Yes. Qwen3.5-122B-A10B fits on the M3 Ultra (256 GB) at Q8_0 with an 8K context, using about 127.4 GiB, at an estimated 50 tokens/s.

### Can Qwen3.5-122B-A10B be used commercially?

Qwen3.5-122B-A10B is released under Apache-2.0. The licence allows commercial use (read its conditions).

## Sources

- https://github.com/QwenLM/Qwen3.8/blob/main/README.md
- https://huggingface.co/Qwen/Qwen3.5-122B-A10B/blob/main/LICENSE
- https://huggingface.co/Qwen/Qwen3.5-122B-A10B
- https://huggingface.co/Qwen/Qwen3.5-122B-A10B/resolve/main/config.json
- https://huggingface.co/api/models/Qwen/Qwen3.5-122B-A10B?expand[]=safetensors
- https://ollama.com/library/qwen3.5/tags