I am deeply impressed by GLM-5.2’s capabilities, and I want to try it as the default model for my coding agent.
What I am finding among US providers is that most of them prefer to serve a quantized (4-bit, nvfp4) version. The general consensus seems to be that quantization does not degrade model quality by a huge margin. However, there is also some evidence that long-context tasks - exactly the kind of tasks coding agents do - can degrade much faster as context length grows when the model is quantized.
I am wondering if you can share your thoughts on quality vs. quantization?
Realized I never responded to this, but at this point I think fp4 is largely standard and reliable, but some providers definitely end up with per-model issues
I am deeply impressed by GLM-5.2’s capabilities, and I want to try it as the default model for my coding agent.
What I am finding among US providers is that most of them prefer to serve a quantized (4-bit, nvfp4) version. The general consensus seems to be that quantization does not degrade model quality by a huge margin. However, there is also some evidence that long-context tasks - exactly the kind of tasks coding agents do - can degrade much faster as context length grows when the model is quantized.
I am wondering if you can share your thoughts on quality vs. quantization?
Realized I never responded to this, but at this point I think fp4 is largely standard and reliable, but some providers definitely end up with per-model issues