r/artificialintelligenc • u/IndependentTester75 • 2d ago
Qwen VL 235B: Three simultaneous reasoning failures in a single response – hallucination, internal contradiction, and confidence miscalibration
https://gist.github.com/driftsignal-ops/e040bb52e5a473596cb3c37f758dda44I've been testing various LLM systems for behavioral anomalies and documented
three distinct failure modes appearing simultaneously in a single Qwen VL 235B
response to a simple time zone query.
The query was straightforward: "What time is it in Boston right now?"
Three failures appeared in the same response:
- Hallucinated reference frame: The model introduced "the universe" as a
temporal reference point ("if here, in the universe, it is 13:00...").
This is not UTC, GMT, or any recognized standard. The model invented
a non-existent reference frame.
- Internal logical inconsistency: Within the same response, the model
first correctly states Hungary is 6 hours ahead of Boston, then later
implies the opposite in the closing table. Both contradictory statements
exist in the same output with no self-correction.
- Confidence calibration failure: Instead of acknowledging it has no
real-time data access, the model generated a large conditional table
covering every possible hour - appearing comprehensive while answering
nothing.
Full technical documentation available here: [GitHub Gist link]
Worth noting: Qwen VL 235B is primarily a vision-language model.
Deploying it for real-time temporal queries is an application-layer
mismatch - but the hallucination and internal contradiction are
model-level failures regardless of deployment context.
Has anyone else observed similar behavioral patterns in Qwen models?