Alibaba/Mixture of Experts

AlibabaQwen 3.5 122B A10B

Qwen 3.5 122B A10B — MoE multimodal flagship. 256 experts, 10B active. Near-frontier on coding, reasoning, and vision.

chatcodingreasoningmultilingualvisionmath
122B
Parameters (10B active)
256K
Context length
8
Benchmarks
17
Quantizations
500K
HF downloads
Architecture
MoE
Released
2026-02-24
Layers
48
KV Heads
2
Head Dim
256
Family
qwen

Quantization Options

QuantBitsVRAMQuality
IQ2_XXS2.3836.8 GBlow
IQ2_M2.9345.2 GBlow
Q2_K3.1648.7 GBlow
IQ3_XXS3.2550.1 GBlow
IQ3_XS3.553.9 GBlow
Q3_K_S3.6456.0 GBlow
IQ3_M3.7657.8 GBlow
Q3_K_M461.5 GBlow
Q3_K_L4.366.1 GBmoderate
IQ4_XS4.4668.5 GBmoderate
Q4_K_S4.6771.7 GBmoderate
Q4_K_M4.8975.1 GBgood
Q5_K_S5.5785.4 GBgood
Q5_K_M5.787.4 GBgood
Q6_K6.56100.5 GBexcellent
Q8_08.5130.1 GBlossless
FP1616244.5 GBlossless

Select your GPU above to see speed estimates and compatibility for each quantization.

Benchmarks (8)

IFEval93.4
MMBench92.8
MMLU-PRO86.7
GPQA Diamond86.6
MMMU83.9
LiveCodeBench78.9
SWE-bench72.0
HLE25.3

Run this model

Easiest way to get starteddocs →
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen3.5:122b-a10b:q4_k_m

Downloads and runs automatically. Add --verbose for speed stats.

Setup guide

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA H100 SXM5 80GB
80 GB VRAM • 3350 GB/s
NVIDIA
$25000
NVIDIA H100 PCIe 80GB
80 GB VRAM • 2000 GB/s
NVIDIA
$25000
NVIDIA A100 SXM 80GB
80 GB VRAM • 2039 GB/s
NVIDIA
$10000
NVIDIA A100 PCIe 80GB
80 GB VRAM • 1935 GB/s
NVIDIA
$10000
NVIDIA A100 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
$15000
NVIDIA A100 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
$10000
NVIDIA A100X
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H100 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
$25000
NVIDIA H100 SXM5 80 GB
80 GB VRAM • 3360 GB/s
NVIDIA
$25000
NVIDIA H100 CNX
80 GB VRAM • 2040 GB/s
NVIDIA
$25000
NVIDIA A800 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
NVIDIA A800 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 SXM5
80 GB VRAM • 3360 GB/s
NVIDIA
NVIDIA RTX 6000D
84 GB VRAM • 1570 GB/s
NVIDIA
$7500
NVIDIA B200
90 GB VRAM • 4100 GB/s
NVIDIA
$30000
NVIDIA H100 NVL 94 GB
94 GB VRAM • 3940 GB/s
NVIDIA
$30000
NVIDIA H100 SXM5 94 GB
94 GB VRAM • 3360 GB/s
NVIDIA
$25000
RTX Pro 6000
96 GB VRAM • 1792 GB/s
NVIDIA
$8565
NVIDIA H100 PCIe 96 GB
96 GB VRAM • 3360 GB/s
NVIDIA
$25000
NVIDIA H100 SXM5 96 GB
96 GB VRAM • 3360 GB/s
NVIDIA
$25000
Intel Data Center GPU Max 1350
96 GB VRAM • 2460 GB/s
INTEL
NVIDIA RTX PRO 6000 Blackwell Server
96 GB VRAM • 1790 GB/s
NVIDIA
$9999
NVIDIA RTX PRO 6000 Blackwell
96 GB VRAM • 1790 GB/s
NVIDIA
$9999
AMD Instinct MI300A
120 GB VRAM • 5300 GB/s
AMD
$12000
Apple M4 Max (128GB)
128 GB VRAM • 546 GB/s
APPLE
$3999
AMD Instinct MI250X
128 GB VRAM • 3277 GB/s
AMD
$10000
Apple M1 Ultra (128GB)
128 GB VRAM • 800 GB/s
APPLE
$4999
Apple M2 Ultra (128GB)
128 GB VRAM • 800 GB/s
APPLE
$3999
AMD Radeon Instinct MI250
128 GB VRAM • 3280 GB/s
AMD
$12000

Find the best GPU for Qwen 3.5 122B A10B

Build Hardware for Qwen 3.5 122B A10B

Qwen 3.5 122B A10B122B Parameter Mixture of Experts LLM

Model Specifications

Parameters
122B (10B active)
Architecture
Mixture of Experts
Context Length
256K tokens
Capabilities
chat, coding, reasoning, multilingual, vision, math
Release Date
2026-02-24
Provider
Alibaba
Family
qwen

VRAM Requirements

QuantizationBPWVRAMQuality
IQ2_XXS2.3836.8 GB65%
IQ2_M2.9345.2 GB75%
Q2_K3.1648.7 GB78%
IQ3_XXS3.2550.1 GB82%
IQ3_XS3.553.9 GB84%
Q3_K_S3.6456.0 GB85%
IQ3_M3.7657.8 GB86%
Q3_K_M461.5 GB88%
Q3_K_L4.366.1 GB90%
IQ4_XS4.4668.5 GB92%
Q4_K_S4.6771.7 GB93%
Q4_K_M4.8975.1 GB94%
Q5_K_S5.5785.4 GB96%
Q5_K_M5.787.4 GB96%
Q6_K6.56100.5 GB97%
Q8_08.5130.1 GB100%
FP1616244.5 GB100%

Benchmark Scores

MMLU-PRO86.7
IFEval93.4
MMMU83.9
MMBench92.8
GPQA Diamond86.6
HLE25.3
LiveCodeBench78.9
SWE-bench72.0

How to Run Qwen 3.5 122B A10B

Run Qwen 3.5 122B A10B locally with Ollama (needs 75.1 GB VRAM at Q4_K_M):

ollama run qwen3.5:122b-a10b

Compatible GPUs (30)

GPUs that can run Qwen 3.5 122B A10B at Q4_K_M quantization: