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REDDIT · REDDIT// 4h agoBENCHMARK RESULT
Qwen3.6 35B shows quantization jitters
A LocalLLaMA user reports that Qwen3.6-35B-A3B gives unstable answers under Q4 and Q6 GGUF quantization in LM Studio/llama.cpp, while Q8 consistently preserves the expected behavior. The discussion frames this as a quantization-sensitivity issue rather than a confirmed model defect.
// ANALYSIS
This is the kind of small, ugly eval that matters for local LLM users: one toy prompt can expose how much behavior shifts when a sparse MoE model gets squeezed.
- –The reported failure mode is not raw benchmark loss, but answer polarity flipping under lower-bit quants
- –Qwen3.6-35B-A3B’s sparse MoE shape may make per-layer or activation-sensitive quantization more important than a simple “Q4 is good enough” rule
- –The comparison with Qwen3.6-27B suggests smaller or denser variants may be more robust for local setups
- –Developers using GGUF builds should test their actual task prompts across quant levels, not assume leaderboard quality survives compression
// TAGS
qwen3.6-35b-a3bllminferenceopen-weightsself-hostedbenchmark
DISCOVERED
4h ago
2026-04-23
PUBLISHED
5h ago
2026-04-23
RELEVANCE
7/ 10
AUTHOR
Sudden_Vegetable6844