QwenQwen3.5-122B-A10B on NVIDIA GeForce RTX 4060 Ti 16GB
RTX 4060 Ti 16GB cannot run Qwen3.5-122B-A10B. 16 GB VRAM is insufficient at any quantization level.
Model Size
122B
Device VRAM
16 GB
Bandwidth
288 GB/s
Quantization
Q3_K_M
Performance by Quantization
OwnRig currently has one published compatibility entry for Qwen3.5-122B-A10B on NVIDIA GeForce RTX 4060 Ti 16GB at Q3_K_M. This pairing has limitations — check the rating and notes below.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q3_K_M | – | – | ✗ Offload | Not viable | estimated |
Notes
Q3_K_M
Q3_K_M needs 28GB; 16GB far too small. All 122B expert weights must reside in memory.
About Qwen3.5-122B-A10B
Qwen3.5-122B-A10B (122B) is a chat, coding, ai coding, reasoning, multi-purpose model. Mixture-of-Experts with 122B total parameters but only 10B active per token. Runs on far less VRAM than the total size suggests. Qwen's best open-weight MoE in the medium tier; excels at knowledge-heavy and vision tasks. Native multimodal. Apache 2.0 licensed.
View all Qwen3.5-122B-A10B hardware options →About NVIDIA GeForce RTX 4060 Ti 16GB
NVIDIA GeForce RTX 4060 Ti 16GB has 16 GB at 288 GB/s. Street price: $449.
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Estimate method: Estimated from Qwen 3 32B and MoE benchmarks with size/architecture scaling. Reference hardware source: github.com (2026-03-24)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.