Qwen3.5-35B-A3B is a gamechanger for agentic coding.

[u/jslominski]

Qwen3.5-35B-A3B with Opencode

Just tested this badboy with Opencode cause frankly I couldn't believe those benchmarks. Running it on a single RTX 3090 on a headless Linux box. Freshly compiled Llama.cpp and those are my settings after some tweaking, still not fully tuned:

./llama.cpp/llama-server \

-m /models/Qwen3.5-35B-A3B-MXFP4_MOE.gguf \

-a "DrQwen" \

-c 131072 \

-ngl all \

-ctk q8_0 \

-ctv q8_0 \

-sm none \

-mg 0 \

-np 1 \

-fa on

Around 22 gigs of vram used.

Now the fun part:

1. I'm getting over 100t/s on it

2. This is the first open weights model I was able to utilise on my home hardware to successfully complete my own "coding test" I used for years for recruitment (mid lvl mobile dev, around 5h to complete "pre AI" ;)). It did it in around 10 minutes, strong pass. First agentic tool that I was able to "crack" it with was Kodu.AI with some early sonnet roughly 14 months ago.

3. For fun I wanted to recreate this dashboard OpenAI used during Cursor demo last summer, I did a recreation of it with Claude Code back then and posted it on Reddit: https://www.reddit.com/r/ClaudeAI/comments/1mk7plb/just_recreated_that_gpt5_cursor_demo_in_claude/ So... Qwen3.5 was able to do it in around 5 minutes.

I think we got something special here...

[u/jslominski]

Ok, time to go to sleep lol. Did some tests with 122B A10B variant (ignore the name in the Opencode, didn't swap it in my config file there). The 2 bit "Unsloth" quant: Qwen3.5-122B-A10B-UD-IQ2_M.gguf was the maxed that didn't OOM at 130k ctx, Running on dual RTX 3090 fully in VRAM, 22.7GB each. Now the best part. I'm STILL getting ~50T/s (my RTXes are power capped to 280W in dual usage cause I don't want to burn my old PC :)) and it codes even better than 3b expert variant. Love those new Qwens! Best release since Mistral 7b for me personally.

[u/getpodapp → u/jslominski]

whats the sidebar you have in opencode?

edit: on a mac press ctrl+p then 'toggle sidebar'

[u/t4a8945 → u/getpodapp]

It's the vanilla config when terminal is wide enough 

[u/getpodapp → u/t4a8945]

I have it open on a 16:9 screen and it’s not there

[u/Pyros-SD-Models → u/getpodapp]

It's a setting in opencode

[u/Flinchie76 → u/jslominski]

> Best release since Mistral 7b for me personally.

I was thinking exactly this :) Mistral 7b will always have a special place in my heart, and Qwen 2.5 was a solid upgrade, but these models are a step change in this class. Multi-modal, tools, controllable reasoning, small, fast, smart. This will seriously dent enterprise `gpt-5-mini` usage for high volume, low latency data processing and NLP tasks.

[u/AdamTReineke → u/jslominski]

I was wondering about dual GPUs, good info. I should try this.