vadimbelsky·Qwen 3.5·Qwen3_5ForConditionalGeneration

Qwen3.5 Medical Ft — Hardware Requirements & GPU Compatibility

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Qwen3.5 Medical Ft is a 9.7B-parameter open language model from vadimbelsky in the Qwen 3.5 family. It supports a context window of up to 262,144 tokens. At BF16 it needs about 19.87 GB of VRAM — see which GPUs and Macs can run it below.

0 2 likes262K context
Based on Qwen3.5 9B

Specifications

Publisher
vadimbelsky
Family
Qwen 3.5
Parameters
9.7B
Architecture
Qwen3_5ForConditionalGeneration
Context Length
262,144 tokens
Vocabulary Size
248,320
Release Date
2026-03-15
License
Apache 2.0

Get Started

How Much VRAM Does Qwen3.5 Medical Ft Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
BF16est.16.0019.9 GB

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 Medical Ft?

BF16 · 19.9 GB

Qwen3.5 Medical Ft (BF16) requires 19.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 26+ GB is recommended. Using the full 262K context window can add up to 34.1 GB, bringing total usage to 54.0 GB. 6 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.

Which Devices Can Run Qwen3.5 Medical Ft?

BF16 · 19.9 GB

21 devices with unified memory can run Qwen3.5 Medical Ft, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).

Related Models

Frequently Asked Questions

How much VRAM does Qwen3.5 Medical Ft need?

Qwen3.5 Medical Ft requires 19.9 GB of VRAM at BF16. Full 262K context adds up to 34.1 GB (54.0 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 9.7B × 16 bits ÷ 8 = 19.3 GB

KV Cache + Overhead 0.6 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead 34.7 GB (at full 262K context)

VRAM usage by quantization

19.9 GB
54.0 GB

Learn more about VRAM estimation →

Can I run Qwen3.5 Medical Ft on a Mac?

Qwen3.5 Medical Ft requires at least 19.9 GB at BF16, 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 Medical Ft locally?

Yes — Qwen3.5 Medical Ft can run locally on consumer hardware. At BF16 quantization it needs 19.9 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Qwen3.5 Medical Ft?

At BF16, Qwen3.5 Medical Ft can reach ~147 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~33 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 ÷ 19.9 × 0.55 = ~147 tok/s

Estimated speed at BF16 (19.9 GB)

~147 tok/s
~33 tok/s
~110 tok/s
~91 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 Qwen3.5 Medical Ft?

At BF16, the download is about 19.31 GB.

Which GPUs can run Qwen3.5 Medical Ft?

6 consumer GPUs can run Qwen3.5 Medical Ft at BF16 (19.9 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU have plenty of headroom for comfortable inference.

Which devices can run Qwen3.5 Medical Ft?

21 devices with unified memory can run Qwen3.5 Medical Ft at BF16 (19.9 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.