[KongchangAI]
Modelgpt-oss:120b / GPT-OSS 120B

gpt-oss:120b

An open-source 120B-parameter large language model from OpenAI that uses a MoE architecture. It can run on consumer-grade hardware through quantization, making it suitable for local inference and orchestration tasks.

Timeline (last 90 days)

Oct 30

The list of cloud models that will require credits to call after November 9 includes: gemma4:31b, gpt-oss:120b, gpt-oss:20b, nemotron-3-super, nemotron-3-ultra, nemotron-3-nano:30b.

Unverified50%
Oct 14

The 77GB coordinator model gpt-oss:120b cannot share the same machine with the worker models it calls, and each task delegation triggers about 100GB of model swapping, with a simple greeting taking nearly five minutes.

Unverified50%
Oct 14

After migrating the worker models to a second host with a 5600G equipped with a GTX 1060, gpt-oss:120b stayed resident throughout a long run of 1 hour and 46 minutes with no swapping at all, and orchestration reliability surpassed Gemma.

Unverified50%
Oct 14

When the 120B coordinator is resident (about 77GB), only about 3GB of memory is free in the system; in a multi-image run the first image completes and the remaining images time out at the 300-second limit and fall back to placeholders.

Unverified50%
Oct 14

The only real advantage of 120B over 20B is more reliable orchestration, but even this did not solve the deeper reliability problem it was supposed to solve.

Unverified50%

All Facts (5)

Source Articles