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URL: https://willitrunai.com/models/qwen-3.6-35b-a3b

โ‡ฑ Qwen 3.6 35B A3B VRAM Requirements โ€” GPU Compatibility


๐Ÿ‘ Alibaba
Alibaba

Qwen 3.6 35B A3B

Frontier
๐Ÿ‘ huggingface
HuggingFace
5.6MDownloads2.3KLikesApr 2026Released262K tokensContextApache 2.0License98 ExceptionalQuality

Qwen 3.6 35B A3B (35B parameters) requires approximately 28.5 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 3B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 33 GB of VRAM.

Get started

โ€” copy & paste to run locally

Copy-paste commands to run Qwen 3.6 35B A3B on your machine.

Run

docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \ --hf-repo "Qwen/Qwen3.6-35B-A3B" \ --hf-file "Qwen3.6-35B-A3B-Q4_K_M.gguf" \ -c 4096 -ngl 99

Quick specs

Parameters35B (3B active)
Architecturemoe (MoE)
Context262K tokens
Modalitytext+vision
Min RAM13.7 GB
Rec. RAM21.3 GB (Q4_K_M)
LicenseApache 2.0
FamilyQwen
โœ“ Visionโœ“ Codeโœ“ Chatโœ“ Reasoning

About this model

Qwen 3.6 35B A3B is the first open-weight Qwen 3.6 model, a multimodal MoE release focused on stronger agentic coding, long-context reasoning, and more stable repository-scale workflows.

  • โ€ข35B total params with only 3B active per token
  • โ€ข262K native context with preserve-thinking support
  • โ€ขMultimodal open-weights model tuned for coding and agent workflows

Related models

Your hardware

Detecting...

Quick picks

Best budgetS
Mac mini M4 64GB~$1,099 โ€” 11 tok/s
๐Ÿ‘ NVIDIA
Best overallS
NVIDIA A100 40GB~$10,000 โ€” 126 tok/s

Best hardware

Top picks for Qwen 3.6 35B A3B

NVIDIA A100 40GBS
40 GB
RTX 6000 Ada 48GBS
48 GB
RTX PRO 5000 Blackwell 48GBS
48 GB
NVIDIA L40S 48GBS
48 GB
NVIDIA L40 48GBS
48 GB

Run this model

Qwen 3.6 35B A3B on NVIDIA A100 40GBQwen 3.6 35B A3B on RTX 6000 Ada 48GBQwen 3.6 35B A3B on RTX PRO 5000 Blackwell 48GB

Quantization options

VRAM estimates by quant level

No hardware detected โ€” fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
Q2_K
2
13.7 GB
Lowโ€”
Q3_K_S
3
17.2 GB
Lowโ€”
NVFP4
4
19.6 GB
Mediumโ€”
Q4_K_M
4
21.3 GB
Mediumโ€”
Q5_K_M
5
25.2 GB
Highโ€”
Q6_K
6
28.7 GB
Highโ€”
Q8_0
8
37.5 GB
Very Highโ€”
F16
16
71.8 GB
Maximumโ€”

Quality benchmarks

Qwen 3.6 35B A3B benchmark scores

Benchmark verified

Coding

SWE-bench Verified73.4%
HumanEval+โ€”
Aider Polyglotโ€”
LiveCodeBench80.4%

Reasoning

MMLU-Pro85.2%
GPQA Diamond86.0%
MATH-500โ€”
ARC Challengeโ€”

Source: official ยท 2026-04-15

Hardware compatibility

Fit estimates across all hardware

Open calculator

Computing compatibility...

Memory breakdown

Reference: RTX 2060 6GB

Weights21.3 GB
KV Cache4.1 GB
Runtime2.4 GB
Headroom0.6 GB

Frequently asked questions

FAQ โ€” Qwen 3.6 35B A3B

See also

VRAM Deep Dive GuideQuantization GuideScoring MethodologyVRAM Calculator