AI & Tools desk — breakout report
Qwen 27B on 6GB VRAM...
Prompt Engineering's upload has reached 13.8K views — about 3.4× the ≈4K this channel typically draws at the same age.
Key facts
- •3.4x Prompt Engineering's own 90-day median — this channel normally draws about 4K views at the same age.
- •13.8K views so far, published 14 days ago.
- •Category: Science & Technology · Language: en · Quality: HD
- •"Breakout" is measured against this exact channel's trailing 90-day median at matching video age — not a generic niche average.
Updated 2026-09-28 19:10 UTC
View trajectory
Views this upload has gathered since it published, last measured about 168h in — from our own tracking.
Published Sep 28, 2026 · 14 days ago. How breakouts are measured →
From the creator
PrismML says Bonsai 2 keeps 98% of Qwen3.8 27B's performance in a 6 GB file, so I tested it against the full model in the same agent harness, with thinking off on both. On short tasks it's a tie (48.6 vs 47.1), but on six long agentic builds the full Qwen scored 35 out of 60 while Bonsai didn't produce a single…
Category: Science & Technology · Language: en · Quality: HD
Topics: Technology
Tags: Bonsai 2, PrismML, Qwen3.8 27B, Qwen 27B, Bonsai 2 vs Qwen, ternary quantization, 1.58 bit LLM, 1-bit LLM, model quantization, quantization explained, local LLM, run LLM on Mac
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