I need to see these proper harnesses

I tried oMLX and OpenCode a few weeks ago and the 65k context window was useless, it tried to analyze a very small codebase before going full on agentic and ran out of context window immediately

I don't have time to tweak 1,000 permutations of settings just re-prove that its not as smart as Opus 4.6

I need out the box multimodal behavior as similar as typing claude in the command line and its so not there yet

but I'm open to seeing what people's workflows are

I'm running opencode with qwen3.6-35b-a3b at a 3-bit quant. I also have qwen3.5-0.8b used for context compaction. I run with 128k context.

It's usable. I set it loose on the postgres codebase, told it to find or build a performance benchmark for the bloom filter index and then identify a performance improvement. It took a long time (overnight), but eventually presented an alternate hashing algorithm with experimental data on false positive rate, insertion speed and lookup speed. There wasn't a clear winner, but it was a reasonable find with rigorous data.

I'm playing with a tape drive for backups, so I asked a local model to rewrite LTFS ( https://github.com/LinearTapeFileSystem/ltfs ) in Go.

I gave it the reference C implementation, the LTFS spec from SNIA, and asked it to use the C implementation to verify the correctness of the Go code.

LTFS is a pretty straightforward spec, so it made a very reasonable port within about 2 days. It's now working on implementing the iSCSI initiator (client) to speak with my tape drive directly, without involving the kernel.

Edit: the model is Qwen3.6-35B

Hey man, you can just say "I'm lazy, so I'm staying with the cloud. if I wanted to use my brain, I wouldn't be using AI, gosh" - it's much shorter.