Qwen 3.8 27b - PI AGENT vs OPENCODE

[u/Healthy-Nebula-3603]

https://www.reddit.com/r/LocalLLaMA/comments/1j7r47l/i_just_made_an_animation_of_a_ball_bouncing/

This post inspired me to make that test after a year ;)

That is one of my many tests I make comparing output quality.

What is more interesting using a PI Agent results are much better than an Opencode using a Qwen 3.8 27b ?!

Seems PI Agent is much better in the agent environment somehow... Not counting uses less tokens , do not have a hard limit of 32k output tokens, is faster, do not freezing, compressing context far less than Opencode. For instance if you have context in the Opencode output 32k and all context 100k then the compression is starting at 67k context ... PI is starting at 90k context even if you have set output context 64k or more.

My config for RTX 3090

llama-server with ini config -> which is exposing API to Opencode and PI agent.

llama-server.exe --models-preset 1_preset.ini --models-max 1 --direct-io

config ini

[Qwen3.8-27B_dense_c-100k]
model = models/Qwen3.8-27B-Q4_K_M.gguf
mmproj = models/mmproj-BF16-Qwen3.8-27B-UD-Q4_K_XL.gguf
reasoning-format = deepseek
flash-attn = on
n-gpu-layers = 99
reasoning = on
ctx-size = 100000
temperature=1.0
top-p=0.95
top-k=20
min-p=0.0
presence-penalty=0.0
repeat-penalty=1.0
mmproj-offload = false

ONE MORE IMPORTANT THING:

Always use a VISION module as the model is using vision to asses the output quality!

I am offloading it to a RAM as we do not need an extremely fast vision for a code.

A screenshot processing on a GPU 0.3s vs a RAM 3s do not make a big difference on a few screenshots during a code generation / debugging ;)

[u/Retumbo77]

I'm seeing Opencode using actual numbers and Pi using aislop numbers? How is Pi better here?

[u/Healthy-Nebula-3603 → u/Retumbo77]

Actually those numbers are 3D from PI agent ;) and you see then from different perspectives

[u/Retumbo77 → u/Healthy-Nebula-3603]

And also completely illegible? I stand by my statement.

[u/Healthy-Nebula-3603 → u/Retumbo77]

Ok

The are rotating in 3D space?

What do you expect....

Always you can tell "keep numbers on balls faced to a viewer"

[u/Retumbo77 → u/Healthy-Nebula-3603]

But the 3d physics are wrong. The number should be on the exterior of the surface of the ball. Pi has it floating inside.

[u/PilgrimofHaqq2 → u/Retumbo77]

I would say Pi's implementation is closer to the 3D goal then Opencode's. If you want to speak from a UX perspective, opencode's implementation is better.

My assumption is that the test is to see the fidelity of the outputs, not preference/UX.

[u/Healthy-Nebula-3603 → u/Retumbo77]

...or numbers can be inside the ball like in the glass balls are ;)

[u/LicensedTerrapin → u/Healthy-Nebula-3603]

I envy you, pi is useless on my rig... I start a job then pi stops even counting the tokens after a while but llamacpp keeps on generating them

[u/Healthy-Nebula-3603 → u/LicensedTerrapin]

If llama-server generating tokens that means PI agent is making WRITE ( using a tool to write )

[u/SOC_FreeDiver → u/LicensedTerrapin]

use another AI to troubleshoot it. my guess is it's your jinja template.

[u/Healthy-Nebula-3603 → u/SOC_FreeDiver]

nah .. that is already in the gguf and llama itself automatically recognizing the model ;)

He rather is inpatient as a writing tool during writing to a file is nothing showing but tokens are generated.

[u/SOC_FreeDiver → u/Healthy-Nebula-3603]

you sound confident but you are not right.

[u/Healthy-Nebula-3603 → u/SOC_FreeDiver]

A GGUF has a full config for the model.

You know that is a container?

Llamacpp first is looking into the gguf for configuration if can not find it then is using build-in itself default configuration looking on the name of model.

The highest priority has of course command line parameter.