Deploy Popular Open‑Source LLMs on Free CPU in Minutes – Qwen3.5, DeepSeek‑R1, Gemma 3, Llama 3.2 and More

Background: Open‑source large language models (LLMs) are released at a rapid pace, but developers often face high GPU costs, complex environment configuration, and hardware barriers when trying to test new models.

CPU feasibility: Advances in model quantization and inference frameworks now allow many mainstream open‑source models to run basic inference on CPUs, opening a low‑cost path for experimentation. HyperAI offers a free CPU quota (Basic users: up to 12 hours per task; Pro users: up to 24 hours) to support this.

Available model tutorials: HyperAI’s “Tutorial” section provides ready‑made CPU deployment guides for the following models, each with a direct link to the runnable notebook:

Qwen3.5‑9B‑GGUF – https://go.hyper.ai/sT3nm

Qwen2.5‑14B‑Instruct‑GGUF – https://go.hyper.ai/8zRsH

Qwen2.5‑3B‑Instruct‑GGUF – https://go.hyper.ai/rRwPi

DeepSeek‑R1‑Distill‑Qwen‑1.5B‑GGUF – https://go.hyper.ai/GLIuy

DeepSeek‑Coder‑V2‑Lite‑Instruct‑GGUF – https://go.hyper.ai/GkC5A

Gemma‑3‑1b‑it‑GGUF – https://go.hyper.ai/9RWJm

Llama‑3.2‑3B‑Instruct‑GGUF – https://go.hyper.ai/e8ska

gpt‑oss‑20b‑GGUF – https://go.hyper.ai/80rxF

Phi‑4‑mini‑instruct‑GGUF – https://go.hyper.ai/3j2Cc

GLM‑4‑9B‑chat‑GGUF – https://go.hyper.ai/H0GMI

Step‑by‑step example (CPU deployment of Qwen3.5‑9B‑GGUF):

Visit the HyperAI homepage, navigate to the “Tutorial” page, and select “CPU deployment Qwen3.5‑9B‑GGUF”. Click “Run this tutorial online”.

On the tutorial page, click the top‑right “Clone” button to copy the notebook into your own workspace. (The interface supports both Chinese and English.)

Choose the “Free‑CPU” runtime and the “PyTorch” image, then click “Continue job execution”.

Wait for the resource allocation; when the status changes to “Running”, click “Open Workspace” to enter the Jupyter environment.

In the workspace, open the README file and press the “Run” button to start the inference script.

After execution finishes, click the displayed API URL to view the demo output.

Result: The notebook runs successfully on a CPU‑only container, producing model responses that demonstrate the feasibility of low‑cost inference for Qwen3.5‑9B‑GGUF.

Additional note: HyperAI also offers a registration benefit – for $1 users receive 20 hours of RTX 5090 compute (originally $7), with the quota remaining permanently valid.