Qwen3.5 122B A10B — Hardware Requirements & GPU Compatibility
Vision
Qwen3.5 122B A10B is a 125.1B-parameter open language model from Alibaba in the Qwen 3.5 family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 75.43 GB of VRAM — see which GPUs and Macs can run it below.
791.7K downloads
568 likesSpecifications
- Publisher
- Alibaba
- Family
- Qwen 3.5
- Parameters
- 125.1B
- Architecture
- Qwen3_5MoeForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-02-24
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Qwen3.5 122B A10B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 53.5 GB | 63.1 GB | 53.16 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 61.4 GB | 70.9 GB | 60.98 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 75.4 GB | 85.0 GB | 75.05 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 89.5 GB | 99.1 GB | 89.12 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 103.6 GB | 113.2 GB | 103.20 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 125.5 GB | 135.1 GB | 125.09 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 250.6 GB | 260.1 GB | 250.17 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Qwen3.5 122B A10B?
Q4_K_M · 75.4 GBQwen3.5 122B A10B (Q4_K_M) requires 75.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 99+ GB is recommended. Using the full 262K context window can add up to 9.6 GB, bringing total usage to 85.0 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Qwen3.5 122B A10B?
Q4_K_M · 75.4 GB5 devices with unified memory can run Qwen3.5 122B A10B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Where to Download Qwen3.5 122B A10B
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 Qwen3.5 122B A10B need?
Qwen3.5 122B A10B requires 75.4 GB of VRAM at Q4_K_M, or 250.6 GB at BF16. Full 262K context adds up to 9.6 GB (85.0 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 125.1B × 4.8 bits ÷ 8 = 75.1 GB
KV Cache + Overhead ≈ 0.3 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 9.9 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M75.4 GBQ4_K_M + full context85.0 GB- Can NVIDIA GeForce RTX 5090 run Qwen3.5 122B A10B?
No — Qwen3.5 122B A10B requires at least 53.5 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Qwen3.5 122B A10B?
For Qwen3.5 122B A10B, Q4_K_M (75.4 GB) offers the best balance of quality and VRAM usage. Q5_K_M (89.5 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 53.5 GB.
VRAM requirement by quantization
Q2_K53.5 GBQ4_K_M ★75.4 GBQ5_K_M89.5 GBQ6_K103.6 GBQ8_0125.5 GBBF16250.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen3.5 122B A10B on a Mac?
Qwen3.5 122B A10B requires at least 53.5 GB at Q2_K, 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 Qwen3.5 122B A10B locally?
Yes — Qwen3.5 122B A10B can run locally on consumer hardware. At Q4_K_M quantization it needs 75.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen3.5 122B A10B?
At Q4_K_M, Qwen3.5 122B A10B can reach ~39 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 75.4 × 0.55 = ~39 tok/s
Estimated speed at Q4_K_M (75.4 GB)
~39 tok/s~29 tok/s~24 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen3.5 122B A10B?
At Q4_K_M, the download is about 75.05 GB. The full-precision BF16 version is 250.17 GB. The smallest option (Q2_K) is 53.16 GB.
- Which GPUs can run Qwen3.5 122B A10B?
No single consumer GPU has enough VRAM to run Qwen3.5 122B A10B at Q4_K_M (75.4 GB). Multi-GPU or professional hardware is required.
- Which devices can run Qwen3.5 122B A10B?
5 devices with unified memory can run Qwen3.5 122B A10B at Q4_K_M (75.4 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), Mac Studio M4 Max (128 GB), NVIDIA DGX A100 640GB. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.