Ollama vs LM Studio on 16GB: What Stayed Stream-Safe With OBS Live
Same 13B quant, same prompts, avatar rig on. Tok per sec, stalls, and which tool I would trust on stream.
Primary source: Bench log - 13B Q4_K_M, OBS live, September 2026
Two free tools, one 16GB PC, one live audience. The difference is usability under load, not logos.
Claim: identical on 16GB. My test says no.
Rig: Ryzen 7700, 16GB DDR5, RTX 4060 8GB, OBS 31 with VTuber rig plus chat overlay live. Model: 13B Q4_K_M, context 4k. Three prompts: short chat, long summary (1,800 words in), RAG note lookup. Timed with a stopwatch app on my phone. No sponsor. Both tools free at test time.
Round 1, short chat: Ollama held 28 to 34 tok/s. Idle RAM near 9.1GB. LM Studio held 26 to 31 tok/s. Idle near 10.4GB. Chat felt equal. Viewers would not spot it.
Round 2, long summary: Ollama dropped to 14 tok/s at 3k context and stuttered twice when OBS wrote a replay buffer. LM Studio held 17 tok/s and kept audio smooth. I reran it. Same gap. My guess: LM Studio paged KV cache a touch better on this card. Log lines back that read, but I am not certain.
Round 3, RAG lookup: Both answered right. Ollama cited page numbers cleaner. LM Studio UI made file attach faster (drag, click, done in 20 sec vs 50 sec in terminal flags). Speed tie. Usability win to LM Studio.
What broke: 32B Q4 with stream live? Neither. Ollama crawled at 4 tok/s. LM Studio froze OBS preview for two seconds on load. I killed both runs. If you must run 32B on 16GB while live, split boxes or use an API fallback for the show.
For more real-world testing with multiple streamers, see 3 VTubers test local LLMs live to understand where models break first under streaming load.
My pick: streaming on one PC, grab LM Studio for the night. Low RAM headroom or headless box, grab Ollama. Full prompt texts and VOD stamps sit with the two quoted testers linked below. I asked each for a yes before quoting. They got draft links first.
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