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BigMoeOnEdge

v0.13.1 Bugfix

This release fixes issues for SREs watching stability and regressions.

Published 7d LLM Frameworks
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

android c++ edge-ai gemma gguf gpt-oss
+7 more
inference llama-cpp llm mixture-of-experts moe on-device-ai qwen

Summary

AI summary

Fixes incorrect none reporting for non‑reasoning LFM models.

Changes in this release

Bugfix Medium

Corrects `think_ctl` verdict handling for non-reasoning models.

Corrects `think_ctl` verdict handling for non-reasoning models.

Source: llm_adapter@2026-07-20

Confidence: medium

Full changelog

A correctness fix to the think_ctl verdict introduced in v0.13.0.

The bug. llama.cpp's LFM2 handler publishes <think>/</think> for the whole family, whether
or not a given model reasons. Combined with "this template ignores enable_thinking", that made
every LFM model report none — including the ones that never reason. The app then disabled their
Thinking switch and explained it with "this model always reasons — it offers no way to turn thinking
off"
, which was false, and took away a control that had merely been moot.

| template | uses <think> | reasons | v0.13.0 | v0.13.1 |
|---|---|---|---|---|
| LFM2.5-8B-A1B | yes | yes | none | none |
| LFM2-8B-A1B | no | no | none | template |
| LFM2.5-Instruct | no | no | none | template |

The fix. none now requires positive evidence of both halves: the model declares a reasoning
span and its template actually uses it — the same test llama.cpp applies before wiring up
reasoning extraction. A second path had the same flaw (a template where the continuation hook does
nothing also landed in none, catching any plain non-reasoning template), so the probe is reordered
and none is reachable only through the span question. Anything with nothing to suppress reports
template: what those models did before any of this existed.

LFM2.5-8B-A1B still reports none on-device — the case v0.13.0 exists for does not regress. No
behaviour change for any model in the app catalog; this is visible only on LFM2 variants loaded by
hand. Streaming, benchmarks and published numbers are unchanged.

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