 | I have run two tests on each LLM with OpenCode to check their basic readiness and convenience: - Create IndexNow CLI in Golang (Easy Task) and - Create Migration Map for a website following SiteStructure Strategy. (Complex Task) Tested Qwen 3.5, & 3.6, Gemma 4, Nemotron 3, GLM-4.7 Flash and several other LLMs. Context size used: 25k-50k - varies between tasks and models. The result is in the table below, hope you find it useful. The speed of most of these selfhosted LLMs - on RTX 4080 (16GB VRAM) is below (to give you idea how fast/slow each model is). Used llama-server with default memory and layers params. Finetuning these might help you to improve speed a bit. Or maybe a bit more than a bit :) --- My Takeaway: Qwen 3.5 27b is a very decent LLM that suit my hardware well. New Gemma 4 26b showed very good results, worth testing more. Both these are comparable to cloudhosted free LLMs from OpenCode Zen - for these two tasks. --- The details of each LLM behaviour in each test are here: https://www.glukhov.org/ai-devtools/opencode/llms-comparison/ [link] [comments] |
