Qwen 3.8 27B — Multi-Kaggle Cluster

Authenticated as admin · Native CUDA C++ Dual-T4 Engine · 64K Ultra Context

Active GPU Nodes

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MTP Speculative Decoding Ready

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Live Kaggle Nodes & GPU Quota Control

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Load Balancer & Routing Policy

Strategy

Real-Time Generation Speed (tok/s)

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Client API Keys (for IDE / Cursor / Apps)

Key Name	Created	Requests	Total Tokens	Last Used	Status	Actions

Kaggle Account Roster & Weekly Quotas

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Paginated Traffic Logs

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Cluster Credentials & Endpoints

OpenAI API Base URL

https://qwen-proxy.gauravsuthar980.workers.dev/v1

Gateway Worker URL

https://qwen-proxy.gauravsuthar980.workers.dev

Shared Admin Secret

qwen-secret-a87f2e19b4c036d7e98a2f5c1d4b6e8a

Model Identifier

qwen3.8-27b 64K Context

Reasoning aliases: qwen3.8-27b-fast, qwen3.8-27b-high

Step 1: Configure Kaggle Notebook Settings & Secrets

In your Kaggle notebook, verify the right sidebar settings:

Accelerator: GPU T4 x2 (Dual T4) Internet: On (Required) Persistence: No persistence

Go to Settings → Add-ons → Secrets in your notebook and add the following keys:

Secret Key	Recommended Value	Description
`WORKER_URL`	https://qwen-proxy.gauravsuthar980.workers.dev	Your Cloudflare Worker Gateway URL
`ADMIN_TOKEN`	qwen-secret-a87f2e19b4c036d7e98a2f5c1d4b6e8a	Admin token for tunnel registration & watchdog
`ACCOUNT_ID`	gaurav (or `rahul`, `friend-2`)	Unique node ID used for load balancing
`ACCOUNT_NAME`	Gaurav Dual-T4	Display name shown on the live cluster table

Step 2: Serving Script (02_serve_qwen_llamacpp.py)

Paste this script into your Kaggle Notebook cell. It automatically compiles native CUDA llama-server with Flash Attention & MTP Speculative Decoding, creates a Cloudflare tunnel, and connects to this control plane.

02_serve_qwen_llamacpp.py — Native C++ Dual-T4 Server

Step 3: Connect Applications (IDE, Cursor, Python, cURL)

Python (OpenAI SDK 1.0+) with Streaming Reasoning

cURL Streaming Request

Cursor / Continue.dev / Cline Custom Model Configuration

LangChain ChatOpenAI Example

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