Laguna-S-2.1 infinite-thinking loops may come from quantization, not prompting
CautiousStudent6919 · reddit · 2026-07-24
A user debugging Laguna-S-2.1 "thinking forever" loops says the problem may be a quantization artifact rather than prompt tuning.
Their main takeaway is that uniform low-bit quants, such as IQ3S, seem to damage the shared-expert and attention weights too much. Switching to an MoE-aware APEX quant like Myric/Laguna-S-2.1-APEX-GGUF reportedly fixed most of the looping while keeping the file size around 54 GB.
They also found that the model behaves best when they stop over-customizing settings:
- Use the stock template with default formatting.
- Stick with temp 0.7, topp 0.95, topk 20.
- Leave minp unset, since the model card warns against it.
One more observation: complex reasoning prompts without tools can still trigger loops. Framing the task around a tool call, or adding a system prompt like "Think briefly then act," seems to help because the model is more agentic than purely conversational.
Related event: Laguna-S-2.1's Reasoning Anomalies Linked to Quantization and Templates(3 posts)→
More from Infra
- SF Compute founder: buying compute is 'an absolutely awful experience' right now — IgorCarron · 2026-09-11
- SmolVM open-sources persistent computer infrastructure for agents that outlive chat sessions — aniketmaurya · 2026-09-11
- PyTorch Day Korea 2026 launches first offline conf, CFP closes Sept 13 — PyTorch · 2026-09-11
- Local LLM server dilemma: 4x CMP-170HX (price up 53% in 20 days) vs Mac Studio M5 Ultra — rumboll · 2026-09-11
- llama.cpp lands Flash Attention tuning for RDNA4, big prefill gains on AMD — pmttyji · 2026-09-11
- Your p99 latency benchmark may be lying: a deep dive into coordinated omission — Franc0Fernand0 · 2026-09-11