@jtdavies: Coding on small models... My default model for my 4xDGX Spark cluster is @UnslothAI's Qwen3.6-35B-A3B-NVFP4. I get exce…
Summary
A user tests various small AI models for coding tasks, finding Qwen3.6-27B-NVFP4 to be the best balance of speed and accuracy, and notes poor Java performance in these models.
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Cached at: 07/15/26, 10:00 PM
Coding on small models…
My default model for my 4xDGX Spark cluster is @UnslothAI’s Qwen3.6-35B-A3B-NVFP4. I get excellent results and it’s generally faster than the technically smaller 4 and 9B models. It’s significantly better than the Gemma4 models so it’s good all-round.
However, sometimes I need a tool or agent written so I need something to write code. I tested my default model and it’s not great, it solves most things eventually but the gain you get from the speed it lost with mistakes.
S, I tested some others, all in the Qwen3.6 range. In a nutshell, as expected the 27B dense model is noticeably better but equally noticeably slower. I tried the best on a QSFP clustered Spark pair and got about 40% better performance but still only a third of the 35B NVFP4 MoE.
The 27B MoE coder models were good but not up to the 27B dense or the speed of the NVFP4. Qwopus was very poor so getting deleted.
I tried Java as well as Python, most coding benchmarks are done with TypeScript and Python. Java is a very poor show in these models so I included it to demonstrate the difference. All tests were done with thinking off as it took long enough already.
My final choice for coding will be the Qwen3.6-27B-NVFP4 as it runs in vLLM in my cluster so it’s an easy switch. Users will just have to wait for the results.
I’m going to try the DeepSeek V4 and GLM 5.2 but I’m not looking for a Claude Code replacement, my clients don’t code. CC: @HundtRichard
Small models are generally not good at coding but it’s still a useful skill for a model to be able to write its own tools or agents. I’m just completing a grid of tests with some of the lager Qwen3.6 models and code fine-tunes. My Sparks are hot
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