jcbtc·Qwen

Qwen3.6 35B A3b Crown Halo Mtp Dynamic — Hardware Requirements & GPU Compatibility

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Qwen3.6 35B A3b Crown Halo Mtp Dynamic is a 35B-parameter open language model from jcbtc in the Qwen family. At Q4_K_M it needs about 23.10 GB of VRAM — see which GPUs and Macs can run it below.

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Specifications

Publisher
jcbtc
Family
Qwen
Parameters
35B
Release Date
2026-06-03
License
Apache 2.0

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How Much VRAM Does Qwen3.6 35B A3b Crown Halo Mtp Dynamic Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
Q4_K_M4.8023.1 GB
Q6_K6.6031.8 GB
Q8_08.0038.5 GB

Which GPUs Can Run Qwen3.6 35B A3b Crown Halo Mtp Dynamic?

Q4_K_M · 23.1 GB

Qwen3.6 35B A3b Crown Halo Mtp Dynamic (Q4_K_M) requires 23.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 31+ GB is recommended. 5 GPUs can run it, including NVIDIA GeForce RTX 5090.

All compatible consumer-level GPUs are running near their VRAM limit. You may also want to consider professional GPUs (e.g., NVIDIA A100, H100) which offer significantly more VRAM. For more headroom and better throughput, consider a multi-GPU configuration with tensor parallelism (supported by tools like vLLM, llama.cpp, or text-generation-inference).

Which Devices Can Run Qwen3.6 35B A3b Crown Halo Mtp Dynamic?

Q4_K_M · 23.1 GB

21 devices with unified memory can run Qwen3.6 35B A3b Crown Halo Mtp Dynamic, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).

Related Models

Frequently Asked Questions

How much VRAM does Qwen3.6 35B A3b Crown Halo Mtp Dynamic need?

Qwen3.6 35B A3b Crown Halo Mtp Dynamic requires 23.1 GB of VRAM at Q4_K_M, or 38.5 GB at Q8_0.

VRAM = Weights + KV Cache + Overhead

Weights = 35B × 4.8 bits ÷ 8 = 21 GB

KV Cache + Overhead 2.1 GB (at 2K context + ~0.3 GB framework)

VRAM usage by quantization

23.1 GB

Learn more about VRAM estimation →

Can NVIDIA GeForce RTX 4090 run Qwen3.6 35B A3b Crown Halo Mtp Dynamic?

Yes, at Q4_K_M (23.1 GB) or lower. Higher quantizations like Q6_K (31.8 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.

What's the best quantization for Qwen3.6 35B A3b Crown Halo Mtp Dynamic?

For Qwen3.6 35B A3b Crown Halo Mtp Dynamic, Q4_K_M (23.1 GB) offers the best balance of quality and VRAM usage. Q6_K (31.8 GB) provides better quality if you have the VRAM.

VRAM requirement by quantization

Q4_K_M
23.1 GB
Q6_K
31.8 GB
Q8_0
38.5 GB

★ Recommended — best balance of quality and VRAM usage.

Learn more about quantization →

Can I run Qwen3.6 35B A3b Crown Halo Mtp Dynamic on a Mac?

Qwen3.6 35B A3b Crown Halo Mtp Dynamic requires at least 23.1 GB at Q4_K_M, 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 Qwen3.6 35B A3b Crown Halo Mtp Dynamic locally?

Yes — Qwen3.6 35B A3b Crown Halo Mtp Dynamic can run locally on consumer hardware. At Q4_K_M quantization it needs 23.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Qwen3.6 35B A3b Crown Halo Mtp Dynamic?

At Q4_K_M, Qwen3.6 35B A3b Crown Halo Mtp Dynamic can reach ~126 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~28 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.

tok/s = (bandwidth GB/s ÷ model GB) × efficiency

Example: AMD Instinct MI300X5300 ÷ 23.1 × 0.55 = ~126 tok/s

Estimated speed at Q4_K_M (23.1 GB)

~126 tok/s
~28 tok/s
~94 tok/s
~78 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of Qwen3.6 35B A3b Crown Halo Mtp Dynamic?

At Q4_K_M, the download is about 21.00 GB. The full-precision Q8_0 version is 35.00 GB.

Which GPUs can run Qwen3.6 35B A3b Crown Halo Mtp Dynamic?

5 consumer GPUs can run Qwen3.6 35B A3b Crown Halo Mtp Dynamic at Q4_K_M (23.1 GB). Top options include AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090.

Which devices can run Qwen3.6 35B A3b Crown Halo Mtp Dynamic?

21 devices with unified memory can run Qwen3.6 35B A3b Crown Halo Mtp Dynamic at Q4_K_M (23.1 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.