Family Qwen · 122B parameters

Qwen 3.5 122B-A10B

Mid-flagship Qwen 3.5 between 27B and 397B. 122B/10B active MoE. Fits on an H100.

🇨🇳 Alibaba·License Apache 2.0·Context 255.859375k tokens·Output April 2025·Tested on the GIGABYTE AI TOP ATOM · our measurements← Catalog

01What it can do

Strengths
  • Frontier-level quality with 10B active parameters
  • 262k context
  • Apache 2.0
  • Highly effective for inference
Limitations to know
  • —73 GB VRAM Q4—multi-GPU required
Architecture
MoE · 122B total / 10B active · Qwen 3.5 flagship · 262k context
Training
Qwen 3.5 flagship within reach — 10B active out of 122B, native 262k context.
Ideal for
MoE workstationReasoning

04Install

Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.

$ollama run qwen3.5:122b-a10b
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

02Required memory

Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.

Q4_K_M
The lightest, ~5% loss
73 GB
Q5_K_M
Good quality/size compromise
88 GB
Q8_0
Nearly indistinguishable from FP16
131 GB
FP16
Full precision — server use
244 GB
Fallback CPU · If you don't have a GPU, allow 110 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for Qwen 3.5 122B-A10B?

To run Qwen 3.5 122B-A10B locally with Q4 quantization, you need about 73 GB of VRAM. An option to compare: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) — leave some headroom for the system and context; check engine compatibility with the GPU.

Current offer: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395)
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Why this choice? Our complete guide on BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) →

Affiliate links — commission possible at no extra cost to you; independent recommendation. As an Amazon Associate, BestLLMfor earns from qualifying purchases.

This model in your private ChatGPT, without the cloud

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03Expected speed

Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.

Entry-level
~3t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~12t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~28t/s
RTX 4090, M4 Max, Radeon 7900