Uploaded April 2026 | Updated September 2026, 1 hour ago

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Can a PowerBASIC 10 fine-tuned Qwen 3.5 9B beat the original Qwen 3.5 9B model in real coding tasks?

In this video, we test the original Qwen 3.5 9B model side-by-side against a PowerBASIC 10 fine-tuned version. The goal is simple: does fine-tuning create better, shorter, more practical answers for PB10 programming?

We run several practical tests:

✅ Test 1 — Fine-tuned model wins on a direct PowerBASIC 10 coding task
✅ Test 2 — Fine-tuned model gives a targeted answer while the original gives a long general explanation
✅ Test 3 — Original model can still get strong results when it uses the SindByte MCP Server and Internet search
✅ Test 4 — We switch the fine-tuned model from Q4 to Q8 and compare the quality jump

The interesting result:
The original model can perform well when it has tools, MCP access, and Internet search.
The fine-tuned model knows PowerBASIC 10 solutions immediately and answers faster, shorter, and more directly.

This is a practical test for developers who care about:
- local AI coding
- PowerBASIC 10
- model fine-tuning
- Q4 vs Q8 quantization
- MCP servers
- specialist coding models
- real-world programming workflows

Tools / links:
SindByte MCP Server + Model-Download
smart-ai-robot.com/en/index.html

Follow me on X:
https://x.com/TheoGottwald

Question for you:
Would you rather use a large general model with tools, or a smaller fine-tuned specialist model that already knows the target language?