Overview

GPT OSS 20B delivers exceptional performance for its size, featuring a 128,000 token context window and FP16 quantization for efficient inference. Built on the GPT family architecture, this model excels at complex reasoning tasks and code generation while maintaining low latency. Developers can integrate it immediately via our standard API endpoints without complex configuration, enabling rapid prototyping and deployment. The MIT license ensures flexibility for commercial applications, making it a robust choice for building scalable AI solutions. Researchers will appreciate its balanced performance across English and Arabic benchmarks, offering a cost-effective alternative to larger models without sacrificing accuracy in multilingual tasks.

For enterprise deployments, GPT OSS 20B offers production-ready stability with native support for Arabic and English languages. The model operates at a 2.5x credit multiplier relative to the base rate, providing significant cost savings compared to larger counterparts while maintaining high quality. Available on the starter tier, it allows businesses to validate use cases quickly before scaling. Whether you are building customer support agents or analytical tools, this model ensures reliable output suitable for professional environments. Access detailed benchmark comparisons and pricing structures directly within our dashboard to align technical capabilities with your budgetary requirements.

Specifications

Display Name GPT OSS 20B

Family GPT

Category Chat

Parameters 20B

Context Window 128,000 tokens

Quantization FP16

License MIT

Min Tier Starter

Status Available

Pricing

2.5×

credits per token

1K 2,500 Credits

10K 25,000 Credits

100K 250,000 Credits

View Pricing Plans

Code Examples

from openai import OpenAI

client = OpenAI(
    base_url="https://llmapi.resayil.io/v1/",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="gpt-oss:20b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

import anthropic

client = anthropic.Anthropic(
    base_url="https://llmapi.resayil.io/v1",
    api_key="YOUR_API_KEY"
)

message = client.messages.create(
    model="gpt-oss:20b",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(message.content[0].text)

const response = await fetch(
    "https://llmapi.resayil.io/v1/chat/completions",
    {
        method: "POST",
        headers: {
            "Content-Type": "application/json",
            "Authorization": "Bearer YOUR_API_KEY"
        },
        body: JSON.stringify({
            model: "gpt-oss:20b",
            messages: [
                { role: "user", content: "Hello!" }
            ]
        })
    }
);

const data = await response.json();
console.log(data.choices[0].message.content);

curl https://llmapi.resayil.io/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gpt-oss:20b",
    "messages": [
      {"role": "user", "content": "Hello!"}
    ]
  }'

Use Cases

Analyzing long legal documents and contracts for insights

Building responsive customer support chatbot interactions

Generating and debugging software code snippets efficiently

Summarizing lengthy meeting transcripts into concise notes

Processing large knowledge bases for retrieval augmented generation

In-Depth Guide

Full Guide

Complete Guide to GPT OSS 20B — LLM Resayil

GPT OSS 20B