Local LLM not working on Windows
Ollama on the CPU, CUDA missing inside WSL2, models crawling on shared GPU memory: the Windows-specific fixes for local LLMs, with PowerShell commands.
ollama psWindows breaks local AI in ways the other two platforms mostly don't, and almost none of them announce themselves as an error. The driver installs, the model loads, generation starts — and it is running on your CPU at four tokens a second while a perfectly good RTX sits at zero percent. That is the shape of most Windows problems here: something silently chose the slow path and nothing told you.
There are four culprits behind nearly all of it. The NVIDIA driver on Windows falls back to system RAM instead of returning an out-of-memory error, so an oversized model degrades instead of failing honestly. Ollama installs per-user without Administrator rights, so a terminal that was already open — or one opened as Administrator — cannot find it. Hybrid laptops hand a command-line process the integrated GPU by default. And WSL2 has its own driver plumbing that a well-meant Linux driver install inside the distro will quietly destroy.
Start with the diagnosis table on whichever page matches your symptom. If you do not have a symptom yet, run ollama ps and look at the Processor column — 100% GPU, 100% CPU, or a split tells you which half of this list you are in.
- CUDA out of memorytorch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.00 GiB (GPU 0; 8.00 GiB total capacity; 7.21 GiB already allocated)
- Ollama: "model requires more system memory than is available"Error: model requires more system memory (9.2 GiB) than is available (7.6 GiB)
- LM Studio: "Failed to load model" (insufficient memory)Failed to load model. Error loading model: unable to allocate backend buffer
- "No CUDA-capable device is detected"RuntimeError: No CUDA-capable device is detected
- Out of memory at long context (the KV cache, not the weights)llama_new_context_with_model: failed to allocate KV cache
- AMD GPU not detected / ROCm unsupported (Ollama & llama.cpp)Error: no compatible GPUs were discovered
- Out of disk space / failed GGUF download for large modelsError: write /root/.ollama/models/blobs/sha256-...: no space left on device
- Ollama "connection refused"curl: (7) Failed to connect to localhost port 11434: Connection refused
- Ollama /v1/systemone errors: 400, 404, 413 explained{"error": "request body must not exceed 64 KiB without images"}
- Ollama /v1/systemone image errors: 400, 413, HEIC and sideways photosHTTP 400 or 413 from POST /v1/systemone as soon as the request has an "images" array, or a 200 whose answers ignore the picture
- CUDA works on Windows but not inside WSL2NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running.
- "ollama is not recognized as an internal or external command"'ollama' is not recognized as an internal or external command, operable program or batch file.
- Move your models off C:Error: write /Users/you/.ollama/models/blobs/sha256-...: There is not enough space on the disk.
- Can't reach Ollama from another devicecurl: (7) Failed to connect to 192.168.1.42 port 11434 after 2004 ms: Could not connect to server
- SmartScreen and antivirus are blocking your local AI installWindows protected your PC
- Model loads but runs painfully slowllm_load_tensors: offloaded 0/33 layers to GPU
- Ollama runs on the CPU on Windows despite an NVIDIA GPUNAME ID SIZE PROCESSOR UNTIL
- Windows shared GPU memory makes your model crawl, not crashTask Manager → Performance → GPU
- Your laptop runs the model on the integrated GPU, not the RTX+-----------------------------------------+
- Which GGUF quant should I download? (Q4 vs Q5 vs Q8)Which GGUF quant should I download?
- Local LLM repeating itself or stuck in a loopThe same sentence again. The same sentence again. The same sentence again. The same sentence ag
- Local LLM outputs gibberish? Wrong chat template<|im_start|>assistant<|im_end|> <|im_start|>user I I I the the of of<|endoftext|>assistantassistant