GPT-5 mini

I’m on ChatGPT Plus. Since May 8/9, ChatGPT web appears to route me to GPT-5 mini even when I manually select “Latest • 5.5 → Thinking”.

The UI still shows Thinking selected and does not show any usage-limit warning, but the assistant replies:

“I’m currently running on GPT-5 mini, so I cannot use GPT-5.5 Thinking.”

What makes it stranger:
- Web keeps giving me GPT-5 mini.
- Android mobile currently responds as GPT-5.5 Thinking.
- Yesterday mobile worked briefly too, then later started responding as mini.
- I tried Edge, other browsers, incognito, Windows app, Android app, sign out/in, “Log out all”, waiting, and brand-new chats.
- It has persisted across overnight gaps, so a simple 3-hour cap fallback doesn’t seem to explain it.
- As far as I understand, GPT-5.5 Instant should be unlimited or almost unlimited for my subscription tier, so being silently routed to mini even outside Thinking is especially confusing.
- OpenAI support escalated it, but I’m still waiting for a specialist response.

Has anyone else seen web and mobile route to different models despite the same manually selected model?

I'm too lazy to update the skills, so I asked it. It doesn't use the `findskills` skill. It checks out the skill repo and merges it with my repo.

there are only two free options in github copilot cli so i have been using GPT-5 mini for some tasks because i don't want to burn out my PR too quickly and to my surprise it is very capable with reasoning set to "high". since its free option, i always run plan mode first and after the task is done i run review command.

https://preview.redd.it/zb1gzzm9ahlg1.png?width=3000&format=png&auto=webp&s=2fe11dfb13a252dacd0ae8c250f4ec17d1a51d93

Qwen3.5-122B-A10B generally comes out ahead of gpt-5-mini and gpt-oss-120b across most benchmarks.

**vs GPT-5-mini:** Qwen3.5 wins on knowledge (MMLU-Pro 86.7 vs 83.7), STEM reasoning (GPQA Diamond 86.6 vs 82.8), agentic tasks (BFCL-V4 72.2 vs 55.5), and vision tasks (MathVision 86.2 vs 71.9). GPT-5-mini is only competitive in a few coding benchmarks and translation.

**vs GPT-OSS-120B:** Qwen3.5 wins more decisively. GPT-OSS-120B holds its own in competitive coding (LiveCodeBench 82.7 vs 78.9) but falls behind significantly on knowledge, agents, vision, and multilingual tasks.

**TL;DR:** Qwen3.5-122B-A10B is the strongest of the three overall. GPT-5-mini is its closest rival in coding/translation. GPT-OSS-120B trails outside of coding.

Lets see if the quants hold up to the benchmarks

Hi LocalLlama.

Here are the results from the March run of the GACL. A few observations from my side:

* **GPT-5.4** clearly leads among the major models at the moment.
* **Qwen3.5-27B** performed better than every other Qwen model except **397B**, trailing it by only **0.04 points**. In my opinion, it’s an outstanding model.
* **Kimi2.5** is currently the top **open-weight** model, ranking **#6 globally**, while **GLM-5** comes next at **#7 globally**.
* Significant difference between Opus and Sonnet, more than I expected.
* **GPT models dominate the Battleship game.** However, **Tic-Tac-Toe** didn’t work well as a benchmark since nearly all models performed similarly. I’m planning to replace it with another game next month. Suggestions are welcome.

For context, **GACL** is a league where models generate **agent code** to play **seven different games**. Each model produces **two agents**, and each agent competes against every other agent except its paired “friendly” agent from the same model. In other words, the models themselves don’t play the games but they generate the agents that do. Only the top-performing agent from each model is considered when creating the leaderboards.

All **game logs, scoreboards, and generated agent codes** are available on the league page.

[Github Link](https://github.com/summersonnn/Game-Agent-Coding-Benchmark)

[League Link](https://gameagentcodingleague.com/leaderboard.html)