Optimizing Qwen3.8 27B on 16GB VRAM: Complete Benchmarks and Guide
MaxDev0 · reddit · 2026-08-18
A comprehensive guide on optimizing Qwen3.8 27B hybrid models for 16GB VRAM, featuring benchmarks, quantization evals, and speculative decoding tests.
Key Recommendations:
- Balanced Profile (Default)
- Model: Qwen3.8-27B-IQ4XS-pure-MTP.gguf (14.56 GB)
- KV Cache: kvarn4
- Speculative Decoding: Native MTP (depth 2)
- Max Context: 32k - 48k tokens
- Quality: 92.55% Top-1 match
- Extended Context Profile (>48K)
- Model: Qwen3.8-27B-AD-IQ3S-IQ3XXS.gguf (12.98 GB)
- Max Context: 72,000 tokens
- Quality: 89.85% Top-1 match
Benchmark Results (vs Q80):
- Qwen3.8 IQ4XS-pure: PPL 4.1474, Mean KLD 0.1169
- Atomic AD-IQ3S-IQ3XXS: PPL 3.9594, Mean KLD 0.2282
Launch Command:
Includes full llama-server startup parameters for MTP speculative decoding and KV cache optimization.
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