Qwen 2.5 27B Quantization Benchmark: Q4 Viable, Q6 Safest
Fun-Meaning-6474 · reddit · 2026-08-24
The team compared Atomic Dynamic GGUF quants for Qwen 2.5 27B on an RTX 6000 using a voxel island creation task. The model handled 3D scenes surprisingly well. Key findings:
| Quant | Size | Top-1 vs BF16 | Mean KLD | Speed |
| :--- | :--- | :--- | :--- | :--- |
| AD-Q4KM | 17.1 GB | 95.6% | 0.0113 | 67 tok/s |
| AD-Q5KM | 20.2 GB | 97.3% | 0.0042 | 57 tok/s |
| AD-Q6K | 25.0 GB | 98.7% | 0.0011 | 49 tok/s |
| Q80 | 28.9 GB | 98.9% | 0.0006 | 50 tok/s |
Results indicate differences aren't drastic, with Q4 sometimes preferred, but AD-Q6K is recommended for the safest bet.
More from Infra
- Hippius launches decentralized storage at 1/100th of Big Cloud costs — markjeffrey · 2026-08-24
- Low-power router with Wake-on-LAN to manage idle AI servers efficiently — Ok-Breakfast1878 · 2026-08-24
- Bandwidth-First Architecture: dMatrix Addresses Inference Speed Bottlenecks — BenBajarin · 2026-08-24
- Nvidia Network Inertia Creates Opportunity for Agent-Optimized NeoClouds — AccBalanced · 2026-08-24
- Hugging Face explores potential sale valuing it at over $13B — xeophon · 2026-08-24
- Peking Univ. Releases TensorCast: 228x Faster Cold Starts, 93.2% Lower TTFT — jiqizhixin · 2026-08-24