[throwaway314155]

Wow, thanks for the info. I'm planning on testing this on my M4 Max w/ 36 GB today.

edit:

So looking here https://ollama.com/library/gpt-oss/tags it seems ollama doesn't even provide the MXFP4 variants, much less hide them.

Is the best way to run these variants via llama.cpp or...?

[spullara]

on the model description page they claim they support it:

Quantization - MXFP4 format

OpenAI utilizes quantization to reduce the memory footprint of the gpt-oss models. The models are post-trained with quantization of the mixture-of-experts (MoE) weights to MXFP4 format, where the weights are quantized to 4.25 bits per parameter. The MoE weights are responsible for 90+% of the total parameter count, and quantizing these to MXFP4 enables the smaller model to run on systems with as little as 16GB memory, and the larger model to fit on a single 80GB GPU.

Ollama is supporting the MXFP4 format natively without additional quantizations or conversions. New kernels are developed for Ollama’s new engine to support the MXFP4 format.

Ollama collaborated with OpenAI to benchmark against their reference implementations to ensure Ollama’s implementations have the same quality.

[throwaway314155]

Can you link to that page? I’m not finding these variants.

[spullara]

as far as I can tell that is the only variant.

https://ollama.com/library/gpt-oss

[Patrick_Devine]

The default ones on Ollama are MXFP4 for the feed forward network and use BF16 for the attention weights. The default weights for llama.cpp quantize those tensors as q8_0 which is why llama.cpp can eek out a little bit more performance at the cost of worse output. If you are using this for coding, you definitely want better output.

You can use the command `ollama show -v gpt-oss:120b` to see the datatype of each tensor.

[ode]

LMStudio

[throwaway314155]

Can you be more specific? I've got LM Studio downloaded but it's not clear where are the official OpenAI releases? Are they all only available via transformers? The only one that shows up in search appears to be the distilled gpt-oss 20B...