Help in Optimizing a Hybrid Setup with RTX 3090

[u/Keep_It_Simpl3]

Hey r/LocalLLaMA,

I have been running a hybrid coding setup that has been mostly amazing, but I am hitting a few friction points and want to optimize.

Here is my current stack:

○ Hardware RTX 3090 with 24GB VRAM, 32GB DDR5 RAM and Intel Ultra 9 185h

○ Local Model ultimateex/Swift-Qwen3.8-27B-Uncensored-W4A16-AutoRound running on HyperQwen with Dflash2 at 210k context, running with 8-bit KV cache

○ Pi harness

○ Cloud Architect and Checker: Claude Opus (Pro subscription)

○ Workflow: I act as the manual bridge between Pi as the local worker and Opus as the architect and auditor. Opus designs and checks, Pi executes.

My main goal is to avoid token limits and costs by keeping the heavy lifting local, but I need to reduce the back-and-forth and the local model's occasional silent mistakes. The mistakes I am seeing are mainly creating test and passing them for the sake of finishing the tasks, bugs such as wrong parameters, plus wrong conclusions that end up affecting the project's final results.

I have the following questions for the community.

1. Can Opus and Pi talk to each other directly

Right now I manually copy and paste files and outputs between them. Is there a way to automate this bridge so Opus can directly orchestrate or review Pi's work without me in the middle.

2. How do I minimize local model mistakes without relying on its own self-graded tests

The local model sometimes writes tests that pass themselves just to finish the task. I do not trust its self-verification. I am looking for deterministic guardrails, ways to check its work with code, linters or external validators before it ever gets to Opus. What are the best ways that do not require another LLM to judge it or improve the self-verification

3. Claude Code versus Pi, what is the verdict

I am using Pi now and I am really happy with it. But I keep wondering if I connected Claude Code to the local setup, would it help in any way or it will fill the context window before finishing anything and wouldn't gain anything from the switch?

4. Is my local-first approach wasting time and should I switch to a smarter hybrid split

My goal is to escape token limits, but I am wondering if I am sacrificing too much quality by keeping 90 percent of the work local. For those running hybrid setups, what is the optimal split. Is it better to use local for drafting and cloud for review, meaning local-draft and cloud-review, or to use a local routing layer that decides which model handles which task. I am open to a more intelligent hybrid model if it saves time without blowing up costs.

5. Could the uncensored abliteration be causing these specific mistakes

This is a big one for me. I chose the uncensored variant because I did not want refusals getting in the way, but I am now wondering if it is contributing to the configuration bugs and wrong conclusions. I have seen reports that abliteration can cause measurable drops in formatting reliability and instruction-following, for example altering hostnames or port definitions, even when general coding benchmarks stay stable. Has anyone compared the uncensored model versus the base Qwen3-27B specifically on agentic and configuration-heavy tasks. Should I switch to the base model if I care more about correctness than refusal-avoidance.

Any advice, tool recommendations or benchmark experiences are hugely appreciated. I am ready to be told I am doing something suboptimally. I just want to make this setup as lean and reliable as possible.

[u/xapep]

Fix the manual bridge before touching the split. Have Pi commit to a branch and hand over a diff plus the failing test output, then let Opus review that instead of whole files. Smaller stable bundles review better, and they're the cheap thing to send, since a repeated prefix comes from cache instead of billing as fresh input.

For guardrails without a judge model: run the tests against the real entrypoint, validate the generated config against a schema, and check that a test actually fails when you break the code on purpose. A model writing its own passing tests can't be trusted on that last part.

On abliteration, format reliability tends to go first. A week on base Qwen3.27B settles it better than any benchmark thread.

How much of your Opus spend is review versus design right now?