LLM regression in reading comprehension?
- Published
- 09/06, 10:10
- Ingested
- 09/06, 23:00
- Source type
- Dev community
- Tier
- Community
- Source status
- Healthy
A user notes a potential regression in LLM reading comprehension, utilizing free tiers of models like Qwen 3.8 max and Gemini 3.1 PREVIEW Temp 1.0 for comparison. While Qwen has been effective despite being slow, Gemini is becoming outdated. The user is interested in accessing K3, an open-source model, and uses Google AI Studio for free Gemini access, finding its free tier generous. They are seeking alternative "intelligent" models.
I only use free tiers of these large models to offset compute while my own system runs and for "different" points of view, since what pops ups suggestions seems to vary a lot sometimes, even when building based on the latest research.
But now I've really struck out with GLM 5.3. So far it feels like an regression over 5.2. It has a hard time reading and following instructions, and is somewhat overly certain in it's statements. I worked on a project recently with it but it became unbearable. From a clean slate the first message can be okay and have great research and ideas but it just veers off course almost immediately.
I use Qwen 3.8 max and Gemini 3.1 PREVIEW Temp 1.0 as competing alternatives or as an ensemble to judge overall quality. Gemini is getting a little out of date (flash 3.8 seemed promising) but Qwen has been great so far, but a little slow and maybe overbearing.
Anyone else having problems? Or suggestions for these top "intelligent" models? I haven't been able to access K3 even though its open source, was impressed with the older models so would be neat to try for free. Also Google AI studio is what i use for free for the gemini stuff, probably pretty well known, but the free tier is pretty generous