NVIDIA: GPT OSS 20B
GPT OSS 20B is a reasoning model from NVIDIA released on Aug 5, 2025. It reads text and writes text, with a 131K token context window and up to 33K tokens per reply.
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It costs $0 per million input tokens and $0 per million output tokens.
It supports tool calling and structured JSON output, and its weights are open, so you can host it yourself.
- Modalities
- In / out price
- $0 / $0 per 1M
- Context
- 131K
- Max output
- 33K
- Released
- Aug 5, 2025
- Knowledge cutoff
- n/a
- Tool calling
- Structured output
- Reasoning
- Prompt caching
- Open weights
- Free to use
GPT OSS 20B pricing
USD, as listed on Oct 15, 2026. Most bills are input heavy, so the cached input rate matters as much as the headline price.
| Input | $0 / 1M tokens | |
|---|---|---|
| Output | $0 / 1M tokens |
What GPT OSS 20B costs per month
Pick a workload close to yours or type your own volumes.
Supported request parameters
What you can set when you call GPT OSS 20B through an OpenAI compatible API.
- Tools
tools - Structured outputs
structured_outputs - Reasoning
reasoning - Temperature
temperature
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GPT OSS 20B questions
How much does the GPT OSS 20B API cost?
$0 per million input tokens and $0 per million output tokens. The estimator on this page turns that into a monthly bill for your own workload.
What is the context window of GPT OSS 20B?
131,072 tokens of input, and it can write up to 32,768 tokens in one reply. As a rough guide, a million tokens is around 750,000 English words.
Does GPT OSS 20B support tool calling?
Yes. It accepts tool definitions and can return JSON that matches a schema, which is what an agent needs to call your APIs.
Is GPT OSS 20B open source?
Its weights are published, so you can run it on your own hardware or a cloud of your choice. Read the license before commercial use.
When was GPT OSS 20B released?
Aug 5, 2025.
Catalog data from models.dev (MIT licensed), refreshed daily, last on Oct 15, 2026. The summary is written from these facts.
Building on GPT OSS 20B?
I test your real tasks on it and the two closest alternatives, then ship the agent on whichever wins on cost and accuracy.
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