Maybe some were fixed, but: 1) Shipping with 2k default context window for the longest time, w/o any warning and being not easy to change (like any other setti

Maybe some were fixed, but: 1) Shipping with 2k default context window for the longest time, w/o any warning and being not easy to change (like any other setting). Totally made a lot of people think local LLMs are dumb as rocks. Just checked, still not fixed -- defaults to 4K if less than 24GB VRAM: https://docs.ollama.com/context-length https://docs.ollama.com/context-length 2) Registry mistrust due to Deepseek R1 naming. What model do you download/start with `ollama run deepseek-r1`? Not Deepseek R1, but this "for research purposes" thinking finetune of Llama 3 released alongside R1 paper: https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama... . For actual R1 you have to pull `deepseek-r1:671b` 3) Can't reuse existing ggufs you have. If you point it to gguf, it would create a copy of it in ollama folder. 4) Doesn't accept engine parameters from CLI args. Only env variables or modelfile. But some things are only in env variables (e.g. KV cache quantization). And even then not even close to what's available in llama.cpp. 5) Often meaningfully slower than llama.cpp 6) VC-funded wrapper for llama.cpp. For long time had questionable attribution to it. Now looks good. > (and also because VLLM is not super Windows friendly) llama.cpp is Windows friendly and fairly easy. Not GUI app with installer, but easy. Zip with binaries are on github, run llama-server.exe -hf unsloth/gemma-4-12B-it-qat-GGUF:UD-Q4_K_XL will pull the model you expect from hugging face (or -m for manually downloaded .gguf) and start web server with API and HTML chat app.