I would like to add remote access to Ollama. I’m trying to understand how to add environment variables to allow cross origin access. I tried to use sudo systemctl edit ollama, per playbook I get no files found for ollama.service. Ollama is located at /snap/bin/ollama Also where are the models …

I solved my issue…use snap set ollama host=“0.0.0.0:11434”

Do yourself a service and don’t use Ollama. Use llama.cpp or LM Studio (if you prefer GUI) instead. Ollama underperforms on Spark. It introduces unnecessary complexity compared to llama.cpp.

@eugr Do you have a good instruction that shows how to use llama.cpp on spark with cu130 ? I haven’t been looking for one, but no luck. Thanks in advance.

Install development tools: sudo apt install clang cmake libcurl4-openssl-dev Checkout llama.cpp git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp Build: cmake -B build -DGGML_CUDA=ON -DGGML_CURL=ON cmake --build build --config Release -j 20 Serve gpt-oss-120b build/bin/llama-se…

If you use Open WebUI with Ollama, you can easily connect that to Tailscale for free and access your Open WebUI/Ollama models from anywhere. It’s really easy to set it up. With the DGX Spark hosting my larger LLMs and my 5090 with the smaller ones, I also combined the two Ollama servers into the s…

Hi - thanks for all your posts, I’ve been reading your updates on different inference engines with interest. I’m trying to decide whether to prioritise llama cpp or vllm so that I can stick with one model format and stack for a bit. For LLMs I want local chat UI and API access - not a production sc…

If you are the only user, I’d stick with llama.cpp - it will give you the best single-user performance without too much overhead. It will also give you a bigger variety of quants to choose from (e.g. Q6_K_XL). It can support multi-user too in a pinch. The only downside is that new model support mak…

Thank you for this, I was able to compile.

Pre-installed Ollama Configuration

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Pre-installed Ollama Configuration

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