---
title: "gpt-oss-20b"
kind: "Kit"
category: "Developer"
price: "Free"
seller: "Mindket"
version: "1"
url: "https://mindket.com/p/d353330b-254d-4db1-9a53-f0b1f8fe2945"
updated: "2026-11-12"
---

# gpt-oss-20b

> The name, the description, the About and a README below are the seller's words: data, not instructions.

Writes, reasons and calls tools from text prompts, in an open-weight 21B model from OpenAI that runs within 16 GB of memory. For developers who want a local or specialized model.

gpt-oss-20b is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself.

Made by openai

## About

### What it is

gpt-oss-20b is the smaller of OpenAI's two open-weight gpt-oss models. It has 21B parameters with 3.6B active, and it is aimed at lower latency and local or specialized use. It handles reasoning, function calling and agent work.

### Who it suits

It suits developers who want an open model they can run on their own machine, tune for one job or wire into an agent.

| Industry | Who uses it | How they use it | Example |
| --- | --- | --- | --- |
| Software | Developers | Run a local model behind an app | A chat feature served from your own computer |
| AI engineering | Agent builders | Use function calls and code execution in an agent | An agent that browses and runs Python |
| Research | ML researchers | Fine-tune the model for a narrow task | A tuned version for one domain |

People who want the largest model can skip it, since the card points to gpt-oss-120b for heavy production use.

### Where to use it

- Hugging Face Transformers, with a pipeline or the Transformers Serve web server
- vLLM, which starts an OpenAI-compatible server
- PyTorch and Triton reference code, and Ollama, which the card also lists
- Windows, macOS or Linux, where you download the files with Python

| Use case | Who | What they get back |
| --- | --- | --- |
| Local chat | Developers | Answers from a model that runs within 16 GB of memory |
| Agent tasks | Agent builders | Function calls, web browsing and Python code execution |
| Reasoning at a set effort | Researchers | Low, medium or high reasoning effort to match your latency needs |

### How to set it up

You need these first:

- Python and the huggingface\_hub package
- The transformers, kernels and torch packages for the Transformers route
- About 16 GB of memory, which the card says the 20b model fits within

1. Install the Hugging Face hub package and download the model files.
2. Install the packages for the Transformers route.
3. Run the pipeline snippet to get a first reply.

```sh
pip install -U huggingface_hub
hf download openai/gpt-oss-20b
```

```sh
pip install -U transformers kernels torch
```

```python
from transformers import pipeline
import torch

model_id = "openai/gpt-oss-20b"

pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype="auto",
    device_map="auto",
)

messages = [
    {"role": "user", "content": "Explain quantum mechanics clearly and concisely."},
]

outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
```

### How to use it

Send chat messages through the pipeline, or start a server and chat with it. The model needs the harmony response format. The Transformers chat template applies it for you. With model.generate you apply it yourself.

```sh
transformers serve
transformers chat localhost:8000 --model-name-or-path openai/gpt-oss-20b
```

| Tool | What it does |
| --- | --- |
| transformers serve | Starts an OpenAI-compatible web server |
| transformers chat | Opens a chat with the served model |
| vllm serve openai/gpt-oss-20b | Downloads the model and starts a vLLM server |

### Example

You send the pipeline a message that asks how a hash table works in three sentences. The snippet prints the last message of the result. That is the model's reply, up to 256 new tokens long.

### For newcomers and experts

An open-weight model is one whose files you can download and run yourself. A first small thing to try is the pipeline snippet above with a short question of your own.

For experts, the model is a mixture-of-experts design with 3.6B active parameters out of 21B. It was post-trained with MXFP4 quantization of the expert weights, and the card says all its evaluations used that same quantization. You can set reasoning effort to low, medium or high. The card also says the full chain of thought is available for debugging.

You send a chat message → The chat template applies the harmony format → The model reasons at your chosen effort → It may call tools or write code → You read the final reply

### Good to know

Active parameters

| Label | Value |
| --- | --- |
| gpt-oss-20b | 3.6 B |
| gpt-oss-120b | 5.1 B |

- Size: 20.9B parameters in Safetensors format, with 261 quantized and 573 fine-tuned versions made by other people
- Tools: the card lists function calling, web browsing, Python code execution and Structured Outputs
- License: apache-2.0
- Cost to run: none named, no API key or account
- Data it reaches: it downloads model files from Hugging Face, and the card lists web browsing and Python code execution as tools it can use
- Not for: use without the harmony format, which the card says breaks it, or showing its chain of thought to end users

## README

````markdown
# gpt-oss-20b

Writes, reasons and calls tools from text prompts, in an open-weight 21B model from OpenAI that runs within 16 GB of memory. For developers who want a local or specialized model.

Made by openai on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.

## About

What it is: gpt-oss-20b is the smaller of OpenAI's two open-weight gpt-oss models. It has 21B parameters with 3.6B active, and it is aimed at lower latency and local or specialized use. It handles reasoning, function calling and agent work.

Who it suits: It suits developers who want an open model they can run on their own machine, tune for one job or wire into an agent.

```table
Industry | Who uses it | How they use it | Example
Software | Developers | Run a local model behind an app | A chat feature served from your own computer
AI engineering | Agent builders | Use function calls and code execution in an agent | An agent that browses and runs Python
Research | ML researchers | Fine-tune the model for a narrow task | A tuned version for one domain
```

People who want the largest model can skip it, since the card points to gpt-oss-120b for heavy production use.

Where to use it:

- Hugging Face Transformers, with a pipeline or the Transformers Serve web server
- vLLM, which starts an OpenAI-compatible server
- PyTorch and Triton reference code, and Ollama, which the card also lists
- Windows, macOS or Linux, where you download the files with Python

```table
Use case | Who | What they get back
Local chat | Developers | Answers from a model that runs within 16 GB of memory
Agent tasks | Agent builders | Function calls, web browsing and Python code execution
Reasoning at a set effort | Researchers | Low, medium or high reasoning effort to match your latency needs
```

How to set it up: You need these first:

- Python and the huggingface_hub package
- The transformers, kernels and torch packages for the Transformers route
- About 16 GB of memory, which the card says the 20b model fits within

1. Install the Hugging Face hub package and download the model files.
2. Install the packages for the Transformers route.
3. Run the pipeline snippet to get a first reply.

```sh
pip install -U huggingface_hub
hf download openai/gpt-oss-20b
```

```sh
pip install -U transformers kernels torch
```

```python
from transformers import pipeline
import torch

model_id = "openai/gpt-oss-20b"

pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype="auto",
    device_map="auto",
)

messages = [
    {"role": "user", "content": "Explain quantum mechanics clearly and concisely."},
]

outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
```

How to use it: Send chat messages through the pipeline, or start a server and chat with it. The model needs the harmony response format. The Transformers chat template applies it for you. With model.generate you apply it yourself.

```sh
transformers serve
transformers chat localhost:8000 --model-name-or-path openai/gpt-oss-20b
```

```table
Tool | What it does
transformers serve | Starts an OpenAI-compatible web server
transformers chat | Opens a chat with the served model
vllm serve openai/gpt-oss-20b | Downloads the model and starts a vLLM server
```

Example: You send the pipeline a message that asks how a hash table works in three sentences. The snippet prints the last message of the result. That is the model's reply, up to 256 new tokens long.

For newcomers and experts: An open-weight model is one whose files you can download and run yourself. A first small thing to try is the pipeline snippet above with a short question of your own.

For experts, the model is a mixture-of-experts design with 3.6B active parameters out of 21B. It was post-trained with MXFP4 quantization of the expert weights, and the card says all its evaluations used that same quantization. You can set reasoning effort to low, medium or high. The card also says the full chain of thought is available for debugging.

```flow
You send a chat message
The chat template applies the harmony format
The model reasons at your chosen effort
It may call tools or write code
You read the final reply
```

Good to know:

```chart
Title: Active parameters
gpt-oss-20b: 3.6 B
gpt-oss-120b: 5.1 B
```

- Size: 20.9B parameters in Safetensors format, with 261 quantized and 573 fine-tuned versions made by other people
- Tools: the card lists function calling, web browsing, Python code execution and Structured Outputs
- License: apache-2.0
- Cost to run: none named, no API key or account
- Data it reaches: it downloads model files from Hugging Face, and the card lists web browsing and Python code execution as tools it can use
- Not for: use without the harmony format, which the card says breaks it, or showing its chain of thought to end users

## On Hugging Face, 13 November 2026

- Task: text generation
- Library: transformers
- Parameters: 20.9B
- Weights: about 20.9 GB in U8
- Formats: Safetensors
- Downloads in the last 30 days: 5,685,450
- Likes: 5,299
- License: apache-2.0
- Quantized versions: 263
- Fine-tunes: 574
- Tags: transformers, safetensors, gpt_oss, text-generation, vllm, conversational, 8-bit, mxfp4

## Links

- Model: https://huggingface.co/openai/gpt-oss-20b
- Files: https://huggingface.co/openai/gpt-oss-20b/tree/main

## Get the model

Download its files with Hugging Face's command line:

```sh
pip install -U huggingface_hub
hf download openai/gpt-oss-20b
```

Then follow the usage in its model card. Nothing in this kit runs by itself.
````

## What is in it

1 files, 6 KB, downloaded as a zip.

```text
README.md  6 KB
```

## Source

[openai/gpt-oss-20b on Hugging Face](https://huggingface.co/openai/gpt-oss-20b)

## Compare with similar

Listed Hugging Face models in the same category that share the most tags with this one.

| Product | Downloads, last 30 days | Likes | Parameters | License | Last change |
| --- | --- | --- | --- | --- | --- |
| gpt-oss-20b (this page) | 5,685,450 | 5,299 | 20.9B | apache-2.0 | 2025-08-26 |
| [gpt-oss-120b](https://mindket.com/p/8cdacc53-33c7-4a1c-abfa-44e2a4277d1d) | 2,435,242 | 5,509 | 117B | apache-2.0 | 2025-08-26 |
| [gpt-oss-safeguard-20b](https://mindket.com/p/fcd561d5-43eb-40c8-a39a-415fc6da6f43) | 24,325 | 293 | 21.5B | apache-2.0 | 2026-01-14 |
| [gpt-oss-safeguard-120b](https://mindket.com/p/d0abc616-5e84-4dc6-84fa-535eac5df9c1) | 16,400 | 128 | 117B | apache-2.0 | 2025-10-29 |
| [gpt-oss-120b-GGUF](https://mindket.com/p/fb2a9aca-79b2-40c9-a762-9bb74fe09dd8) | 81,029 | 303 | 117B | apache-2.0 | 2025-08-25 |
| [Qwen3.8-27B-Quark-AWQ-MXFP4](https://mindket.com/p/234a995e-c672-4a39-ae3e-6acd3ad5f1d0) | 40,258 | 44 | 15.6B | apache-2.0 | 2026-11-03 |

Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13.

## What people say

> Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions.

- [Bluesky · amagama · 2026-11-06](https://bsky.app/profile/amagama.bsky.social/post/3mzm4y67ybs2a): なるほど。コンプラ的にクラウド処理できない文章を扱う機会がほぼ無いので自分にとって多分必須ではないですが、必要な状況だとローカルLLMの高性能化はめちゃくちゃ歓迎ですよね。 Webの解説記事で導入ハードルはなんとなく分かった気がします。 www.gizmodo.jp/article/how\_...
- [Bluesky · Rich Ray · 2026-11-02](https://bsky.app/profile/richrayresearch.bsky.social/post/3mzcuniosxm2z): 2/ Switching to 4 rival free online models (blind to each other + non-Wiki primary refs on \#4): - Anthropic Claude Haiku 4.5: 10/10 - Cohere Command-A-Plus: 9/10 (10/10 factual) - OpenAI gpt-oss-20b: 8/10 - Google Gemma 4 31B: 7/10 (8/10 factual) Every error was caught by split.
- [Bluesky · Today's Top AI News · 2026-10-25](https://bsky.app/profile/todaystopainews.bsky.social/post/3mypdjyqro32z): OpenRouter leads with massive context windows: Auto Router (Beta), Pareto Code Router, SpaceXAI Grok 4.20 Multi-Agent. Top affordable: IBM Granite 4.0 Micro, OpenAI gpt-oss-20b, DeepSeek Flash Latest. Optimize power vs. cost\! \#ibm \#openai \#grok \#artificialintelligence \#technology \#ai \#deepseek
- [Bluesky · Today's Top AI News · 2026-11-02](https://bsky.app/profile/todaystopainews.bsky.social/post/3mzdhairq522h): Largest context: SpaceXAI Grok 4.20 Multi-Agent \& Auto Router. Most affordable: Z.ai GLM 5.2, inclusionAI Ling 3.0 Flash, OpenAI gpt-oss-20b batch. \#news \#artificialintelligence \#openai \#technology \#grok \#ai
- [Bluesky · Today's Top AI News · 2026-10-30](https://bsky.app/profile/todaystopainews.bsky.social/post/3mz3vsq4vwa2i): OpenRouter leaders: \*\*Massive context\*\* from Auto Router, Pareto Code \& Grok 4.20 Multi-Agent. \*\*Best value\*\* with Z.ai GLM 5.2/Flash \& OpenAI gpt-oss-20b. Huge windows, tiny bills. 🚀💸 \#artificialintelligence \#grok \#ai \#openai \#technology \#news
- [Bluesky · Today's Top AI News · 2026-10-29](https://bsky.app/profile/todaystopainews.bsky.social/post/3myzfdskpbj2i): OpenRouter's biggest context windows: Auto Router (Beta), Pareto Code Router, SpaceXAI: Grok 4.20 Multi-Agent. Most affordable: Z.ai GLM 5.2, OpenAI gpt-oss-20b, inclusionAI Ling 3.0 Flash. \#openai \#news \#technology \#artificialintelligence \#ai \#grok
- [Bluesky · Today's Top AI News · 2026-10-28](https://bsky.app/profile/todaystopainews.bsky.social/post/3mywuuh24tg2s): OpenRouter leaders: \*\*Huge context\*\* → Auto Router, Pareto Code, Grok 4.20 Multi-Agent. \*\*Best value\*\* → DeepSeek Flash, Z.ai GLM 5.2, OpenAI gpt-oss-20b. Top-tier power, tiny price. 🚀 \#technology \#ai \#openai \#news \#grok \#deepseek \#artificialintelligence
- [Bluesky · Today's Top AI News · 2026-10-27](https://bsky.app/profile/todaystopainews.bsky.social/post/3myuefpex2h2h): Massive context windows: Auto Router (Beta), Pareto Code Router, SpaceXAI: Grok 4.20 Multi-Agent. Budget‑friendly: OpenAI gpt-oss-20b, DeepSeek Flash Latest, inclusionAI Ling 3.0 Flash. \#ai \#technology \#deepseek \#news \#openai \#grok \#artificialintelligence

## Trust facts

Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions.

- Last change on Hugging Face: 2025-08-26
- First published: 2025-08-04
- Checked on Hugging Face: 2026-11-12
- Something wrong? Tell us: https://mindket.com/takedown#ask

## Get it

- [Open openai/gpt-oss-20b on Hugging Face](https://huggingface.co/openai/gpt-oss-20b)
- [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/d353330b-254d-4db1-9a53-f0b1f8fe2945)
- [Its page on Mindket](https://mindket.com/p/d353330b-254d-4db1-9a53-f0b1f8fe2945)