A viral Reddit post makes the case against Ollama

Ollama hid llama.cpp's role for over a year and left a license-compliance complaint unanswered for 400 days, per a 1,075-upvote r/LocalLLaMA thread. The stakes for anyone running Ollama: a named CVE for token theft, and a measured 1.8x speed gap against the engine it wraps.

On throughput, the post clocks llama.cpp at 161 tokens per second against Ollama's 89, with Ollama's CPU use running 30-50% higher. It ties that gap, along with broken structured output, vision failures, and new assertion crashes, to Ollama's mid-2025 switch to a custom GGML backend.

CVE-2025-51471 covers token exfiltration through malicious model registries, a supply-chain risk rather than a benchmark complaint.

Top comments on the thread converge on three alternatives: LM Studio, llama.cpp directly, and Unsloth Studio. The recurring practical complaint is that Ollama won't reuse models already on disk, forcing redundant downloads.

None of these complaints are new on their own. Seeing the credit dispute, the speed gap, and the CVE stacked in one thread is what pushed three alternative tools into the top comments.