Overview

GPT OSS 120B stands as a flagship open-source solution designed for high-performance inference and complex reasoning tasks. With 120 billion parameters and a massive 128,000 token context window, this model excels at processing extensive documentation and generating precise code snippets without losing context. Developers can integrate it immediately via our standard API endpoints, enabling rapid prototyping and deployment within minutes. The FP16 quantization ensures optimal balance between speed and accuracy, making it suitable for demanding research pipelines requiring robust benchmark performance across both Arabic and English linguistic tasks.

Built for production environments, this model carries an MIT license, granting unrestricted usage rights for commercial applications. While operating at a 3.5x credit multiplier relative to base rates, the architectural efficiency justifies the cost for enterprise-grade workloads. It offers native proficiency in Arabic alongside English, ensuring seamless localization for diverse markets without additional fine-tuning. Decision makers can rely on its stability for customer-facing agents or analytical tools, with transparent pricing structures available directly within the dashboard. This combination of open weights, extensive context handling, and bilingual capability makes it a definitive choice for scaling intelligent applications.

Specifications

Display Name GPT OSS 120B

Family GPT

Category Chat

Parameters 120B

Context Window 128,000 tokens

Quantization FP16

License MIT

Min Tier Starter

Status Available

Pricing

3.5×

credits per token

1K 3,500 Credits

10K 35,000 Credits

100K 350,000 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:120b",
    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:120b",
    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:120b",
            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:120b",
    "messages": [
      {"role": "user", "content": "Hello!"}
    ]
  }'

Use Cases

Summarizing lengthy technical documents and reports efficiently for users

Generating and refactoring complex software codebases rapidly for developers

Analyzing legal contracts for compliance and potential risks

Providing detailed customer support through complex multi-turn chat conversations

Extracting key insights from massive log files automatically

In-Depth Guide

Full Guide

Complete Guide to GPT OSS 120B — LLM Resayil

GPT OSS 120B