OpenAI GPT-OSS Hosting

OpenAI GPT-OSS is a groundbreaking open-weight large language model (LLM) series released by OpenAI on August 6, 2025. Designed for local deployment, transparency, and commercial use, GPT-OSS offers powerful AI capabilities while addressing privacy, cost, and customization challenges associated with closed API models like GPT-3.5/4.

Feature highlights

• Agentic capabilities: Use the models’ native capabilities for function calling, web browsing (Ollama is providing a built-in web search that can be optionally enabled to augment the model with the latest information), python tool calls, and structured outputs.
• Full chain-of-thought: Gain complete access to the model’s reasoning process, facilitating easier debugging and increased trust in outputs.
• Configurable reasoning effort: Easily adjust the reasoning effort (low, medium, high) based on your specific use case and latency needs.
• Fine-tunable: Fully customize models to your specific use case through parameter fine-tuning.
• Permissive Apache 2.0 license: Build freely without copyleft restrictions or patent risk—ideal for experimentation, customization, and commercial deployment.

Overview of Capabilities

• 21B and 117B total parameters, with 3.6B and 5.1B active parameters, respectively.
• 4-bit quantization scheme using mxfp4 format. Only applied on the MoE weights. As stated, the 120B fits in a single 80 GB GPU and the 20B fits in a single 16GB GPU.
• Reasoning, text-only models; with chain-of-thought and adjustable reasoning effort levels.
• Inference implementations using transformers, vLLM, llama.cpp, and ollama.
• License: Apache 2.0, with a small complementary use policy.

gpt‑oss‑120b

• A 117‑billion parameter mixture‑of‑experts model (approx. 5.1B active parameters per token).
• Designed for high reasoning and general‑purpose use, offering performance comparable to OpenAI’s proprietary o4‑mini model.
• Architecturally, it has 36 layers, each layer with 128 experts, of which 4 are active per token.

gpt‑oss‑20b

• A smaller 21‑billion parameter model, with roughly 3.6B active parameters per token.
• Optimized for local or edge deployment—runs well on devices with ≈16 GB GPU memory.
• Designed for latency-sensitive agentic workflows, tool use, and rapid prototyping with lower compute overhead.

Summary Table

Benchmark results

from OpenAI GPT OSS models, compared with o3 and o4-mini (Source: OpenAI).

1. What is GPT-OSS?

GPT-OSS refers to a family of open-source large language models (LLMs), such as gpt-oss-20b and gpt-oss-120b, that are designed to be alternatives to proprietary models like GPT-4. These models can be self-hosted for private, secure, and customizable use.

2. What are gpt-oss-20b and gpt-oss-120b?

• gpt-oss-20b: A 20-billion-parameter model suitable for powerful inference on a single high-end GPU or multi-GPU system.
• gpt-oss-120b: A 120-billion-parameter model requiring high memory bandwidth and typically multiple GPUs for optimal performance.

3. What kind of GPU servers are recommended?

To run GPT-OSS models efficiently, we recommend:

• For 20B: 1× A4000 16GB, or 1× RTX 4090 24GB
• For 120B: 1× A100 80GB, or 2× A100 40GB with NVLink or high-speed interconnect

DatabaseMart offers GPU servers with flexible hourly/monthly pricing to match these needs.

4. Do I need to install special software?

Yes. To run GPT-OSS models, you’ll typically need:

• Ollama, vLLM, or Open WebUI as the inference server
• Python ≥ 3.10
• CUDA drivers for GPU acceleration
• Model weights from Hugging Face or other open repositories

We can pre-install these upon request.

5. Can I use Ollama to run GPT-OSS?

Yes. gpt-oss-20b and other models can be loaded via Ollama by configuring your Modelfile and downloading the weights. Ollama also provides a local API for integration with applications.

6. Is the data private and secure?

Absolutely. Since GPT-OSS runs on your dedicated GPU server, no data is sent to third-party APIs. It’s ideal for privacy-conscious users and enterprises.

7. Can I run GPT-OSS in a Docker container?

Yes, our servers fully support Docker with GPU passthrough. You can use Docker images for Ollama, Text Generation Web UI, or vLLM to containerize your LLM workloads.

8. Do you offer pre-installed environments?

Yes. When ordering, you can choose to have:

• Pre-installed Ollama, Python, CUDA
• Your chosen model (e.g., gpt-oss-20b)
• Web UI or API interface ready to go

Just let our team know your preferences during setup.

9. How do I start using GPT-OSS hosting?

1. Choose a compatible GPU server on Cloud Clusters
2. Request GPT-OSS environment setup
3. Access your server via SSH or web interface
4. Start generating with full control and privacy