Ollama Not Working? Complete Troubleshooting Guide (2026)

You installed Ollama, ran your first model, and things were great — until they weren’t. Maybe Ollama simply refuses to start. Maybe your GPU isn’t being used. Maybe the model download has been stuck at 47% for twenty minutes and you have no idea why.

I’ve been running Ollama daily since early 2024, across three different computers, two operating systems, and through at least a dozen updates. I’ve hit nearly every error that exists. This guide covers all of them — with complete fixes, not just vague suggestions.

Use the error list below to jump straight to your problem.

Quick Error Index — Jump to Your Problem

• Ollama won’t start or keeps crashing
• Error: “ollama” is not recognized / command not found
• GPU not detected — running on CPU only
• Error: model requires more system memory
• Model download stuck or extremely slow
• Error: connection refused / could not connect
• Error: address already in use (port 11434)
• Ollama responses are very slow
• Error: model not found
• CUDA errors on NVIDIA GPU
• Windows Defender / antivirus blocking Ollama
• Error: context length exceeded
• Model download fails — disk space errors
• Ollama API not responding
• Nothing worked — clean reinstall guide

Fix 1: Ollama Won’t Start or Keeps Crashing

This is the most frustrating one — you click Ollama or type a command and nothing happens. Here is the complete fix process:

Step 1 — Check if Ollama is already running

Ollama runs as a background service. It may already be running but not responding. Check:

# Windows PowerShell
Get-Process ollama

# Mac / Linux
ps aux | grep ollama

If you see an Ollama process — kill it and restart:

# Windows
taskkill /F /IM ollama.exe

# Mac / Linux
pkill ollama

# Then restart
ollama serve

Step 2 — Check the Ollama logs for the real error

Ollama writes detailed logs that tell you exactly what went wrong. Read them:

# Windows — logs are here:
%LOCALAPPDATA%\Ollama\ollama_stderr.log

# Mac
~/.ollama/logs/server.log

# Linux
journalctl -u ollama -f

Open the log file and look for lines starting with ERROR or FATAL. That message tells you the exact cause.

Step 3 — Check Windows Firewall is not blocking it

On Windows, go to Windows Defender Firewall → Allow an app through firewall and make sure ollama.exe has both Private and Public access checked.

Step 4 — Reinstall Ollama

If the above steps don’t fix it, download and reinstall the latest version from ollama.com/download. Your models will NOT be deleted during reinstall.

Fix 2: “ollama” Is Not Recognized / Command Not Found

You type ollama in the terminal and get: “‘ollama’ is not recognized as an internal or external command” or “command not found: ollama”. This is a PATH problem — Windows or your shell doesn’t know where to find the Ollama executable.

Fix A — Close and reopen the terminal (try this first)

After installing Ollama, your current terminal window does not automatically reload the system PATH. Simply close PowerShell or Command Prompt completely and open a new one. Try ollama --version again.

Fix B — Restart your computer

If a new terminal window still doesn’t work, restart your PC. This forces Windows to reload all environment variables for every application.

Fix C — Manually add Ollama to PATH (permanent fix)

1. Press Windows + R, type sysdm.cpl, press Enter
2. Click Advanced tab → Environment Variables
3. Under User variables, find and double-click Path
4. Click New and add: C:\Users\YourName\AppData\Local\Programs\Ollama
5. Click OK → OK → OK
6. Open a new PowerShell and test: ollama --version

Fix D — Verify the Ollama installation files exist

Navigate to C:\Users\YourName\AppData\Local\Programs\Ollama\ in File Explorer. If the folder doesn’t exist or is empty, Ollama is not installed correctly — do a fresh install from ollama.com.

Fix 3: GPU Not Detected — Ollama Running on CPU Only

This is one of the most common performance complaints. You have an NVIDIA GPU with plenty of VRAM, but Ollama is using 100% CPU and responses are taking 30+ seconds. Here is exactly how to fix it.

First — Confirm Ollama is actually ignoring your GPU

While a model is running, open a new terminal and check:

ollama ps

Look at the output. If you see 100% CPU — GPU is not being used. If you see GPU listed — it is working fine.

Fix A — Install or update NVIDIA drivers (most common cause)

Ollama requires an NVIDIA driver version of 452.39 or newer to use CUDA for GPU acceleration.

1. Go to nvidia.com/drivers
2. Select your GPU model and download the latest driver
3. Install it (full clean install is recommended)
4. Restart your PC
5. Run ollama run mistral and check ollama ps again

Fix B — Your VRAM is smaller than the model requires

If your GPU only has 4 GB VRAM and you’re trying to run a 7 billion parameter model (which needs ~5 GB VRAM), Ollama falls back to CPU automatically. The solution: use a smaller model or use a quantized version.

# Use quantized version (smaller VRAM footprint)
ollama run mistral:7b-instruct-q4_0

# Or use a smaller model entirely
ollama run phi3:mini

Fix C — Force GPU layers manually

You can tell Ollama how many model layers to offload to the GPU using an environment variable. Start Ollama with:

# Windows PowerShell — set before running ollama
$env:OLLAMA_NUM_GPU = 99
ollama run mistral

Fix D — AMD GPU users

AMD GPU support in Ollama uses ROCm technology. As of 2026, Ollama supports select AMD GPUs (RX 6000 and 7000 series on Linux). On Windows, AMD GPU support is limited — CPU fallback is expected on many AMD setups. Check Ollama’s GitHub for the latest AMD compatibility list.

Fix 4: Error — Model Requires More System Memory

You get an error like: “Error: model requires more system memory (11 GB) than is available (8 GB)”. This means the model you chose is too large for the RAM you have available.

Quick fix — switch to a smaller model

Use quantized (compressed) models to save memory

Every model on Ollama comes in different quantization levels. Lower quantization = smaller size = less RAM needed, at a slight quality trade-off:

# Q4 quantization — uses roughly half the RAM of the full model
ollama run llama3.1:8b-instruct-q4_0

# Q2 quantization — minimum RAM (significant quality reduction)
ollama run llama3.1:8b-instruct-q2_k

Free up RAM before running a model

Close Chrome (each tab uses 100–500 MB), close other heavy applications, and restart Ollama before loading the model. On a tight 8 GB system every MB counts.

Fix 5: Model Download Stuck or Extremely Slow

You ran ollama pull llama3.1 and the progress bar stopped at some percentage, or it’s showing download speeds like 50 KB/s for a 4 GB file. Here’s how to handle this.

Resume a stuck download (just re-run the same command)

Ollama downloads use resumable chunks. If a download stalls, press Ctrl+C to cancel, then run the exact same command again — it picks up from where it left off automatically. You don’t lose any progress.

# Cancel with Ctrl+C, then run again
ollama pull llama3.1

Check if Ollama’s servers are experiencing issues

Occasionally Ollama’s model registry has high load or outages. Check Ollama’s GitHub Issues to see if others are reporting the same download problems before spending an hour troubleshooting your own connection.

Disable your VPN or proxy

VPNs frequently cause Ollama downloads to slow to a crawl or fail entirely. Temporarily disable your VPN, try the download again, and re-enable once done.

Clear the partial download cache

If a download keeps stalling at the same percentage, the cached partial file may be corrupt. Delete it and start fresh:

# Windows — delete cached blobs
Remove-Item "$env:USERPROFILE\.ollama\models\blobs" -Recurse -Force

# Mac / Linux
rm -rf ~/.ollama/models/blobs

Fix 6: Error — Connection Refused / Could Not Connect to Ollama

You see: “Error: dial tcp [::1]:11434: connect: connection refused” or a web interface says it can’t connect to Ollama. This means the Ollama server is not running.

Start the Ollama server manually

ollama serve

Leave this terminal open — the server runs in the foreground. Open a second terminal window to run your models. If you see output like Listening on 127.0.0.1:11434, the server is now running correctly.

Check if another Ollama process is blocking the port

# Windows — check what is using port 11434
netstat -ano | findstr :11434

# Kill the process using that port (replace XXXX with the PID from above)
taskkill /F /PID XXXX

Allow Ollama through your firewall

Windows Firewall sometimes blocks Ollama’s local server. Go to Windows Security → Firewall → Allow an app through firewall → find ollama.exe → enable both Private and Public checkboxes.

Fix 7: Error — Address Already in Use (Port 11434)

Error: “listen tcp 0.0.0.0:11434: bind: address already in use”. Something else is already occupying port 11434 — usually a previous Ollama instance that didn’t shut down cleanly.

# Windows — find what is using port 11434
netstat -ano | findstr :11434

# Kill that process (replace 1234 with actual PID)
taskkill /F /PID 1234

# Mac/Linux — find and kill the process
lsof -ti:11434 | xargs kill -9

Alternatively, run Ollama on a different port by setting an environment variable:

# Windows PowerShell
$env:OLLAMA_HOST = "127.0.0.1:11435"
ollama serve

Fix 8: Ollama Responses Are Very Slow

If Ollama is generating text at 1–3 tokens per second (meaning a short reply takes 30+ seconds), you have a performance issue. Here’s how to diagnose and fix it.

Check if you are running on CPU vs GPU

ollama ps

CPU-only mode generates 1–5 tokens per second on most computers. GPU mode generates 20–80+ tokens per second. If you’re on CPU and have an NVIDIA GPU, see Fix 3 above to enable GPU acceleration.

Match the model size to your hardware

Trying to run a 13B or 70B model on a mid-range laptop is like running a Formula 1 car on bicycle fuel. Use appropriately sized models:

Set the number of CPU threads manually

# Use all available CPU threads for faster CPU inference
$env:OLLAMA_NUM_PARALLEL = 1
$env:OLLAMA_MAX_LOADED_MODELS = 1
ollama serve

Fix 9: Error — Model Not Found

Error: “Error: pull model manifest: file does not exist” or “model not found”. This happens when you try to run a model name that doesn’t exist in Ollama’s library, or you mistyped the name.

Check the exact model name on ollama.com/library

Go to ollama.com/library and search for the model. Copy the exact name shown. Model names are case-sensitive and must match exactly.

# Wrong
ollama run Llama3
ollama run llama 3.1
ollama run LLaMA3.1

# Correct
ollama run llama3.1

List models you already have downloaded

ollama list

This shows every model currently on your system. If the model you want isn’t listed, pull it first: ollama pull modelname

Fix 10: CUDA Errors on NVIDIA GPU

You see errors like: “CUDA error: no kernel image is available for execution on the device” or “CUDA out of memory”.

CUDA error: no kernel image

This means your NVIDIA driver is too old for the CUDA version Ollama is using. Fix: update to the latest NVIDIA drivers from nvidia.com/drivers. After updating, restart your PC and try again.

CUDA out of memory

Your model is too large for your GPU’s VRAM. Fix options:

1. Use a quantized version of the model (q4_0 or q4_k_m suffix)
2. Close all other GPU-intensive applications (games, other AI apps)
3. Reduce the number of GPU layers: set OLLAMA_NUM_GPU=20 (uses GPU for 20 layers, CPU for the rest)

# Partial GPU offload example
$env:OLLAMA_NUM_GPU = 20
ollama run llama3.1:8b

Fix 11: Windows Defender or Antivirus Blocking Ollama

Ollama and its model files occasionally trigger antivirus false positives. Signs: Ollama installs but won’t run, models fail to load, or you get permission denied errors.

Add Ollama to Windows Defender exclusions

1. Open Windows Security → Virus & Threat Protection
2. Click Manage settings under “Virus & threat protection settings”
3. Scroll to Exclusions → click Add or remove exclusions
4. Click Add an exclusion → Folder
5. Add: C:\Users\YourName\AppData\Local\Programs\Ollama
6. Also add: C:\Users\YourName\.ollama
7. Restart Ollama

Is this safe? Yes. Ollama is open-source software with publicly auditable code. Adding it to exclusions tells Windows Defender to trust the application. You can verify the code yourself at github.com/ollama/ollama.

Fix 12: Error — Context Length Exceeded

Error: “this model’s maximum context length is 4096 tokens” or responses stop in the middle of a long conversation. You’ve hit the model’s context window limit.

Start a fresh conversation

The simplest fix: type /clear in the Ollama chat session. This clears the conversation history and resets the context. You can then continue asking questions without the old conversation consuming tokens.

Increase context length with a Modelfile

You can create a custom version of any model with a larger context window:

# Create a file called Modelfile (no extension)
FROM llama3.1
PARAMETER num_ctx 8192

# Then create your custom model from the Modelfile
ollama create llama3-8k -f Modelfile
ollama run llama3-8k

Note: increasing context length requires more RAM. Doubling the context window roughly doubles the memory needed for that model.

Fix 13: Model Download Fails — Disk Space Errors

Error: “no space left on device” or downloads fail with I/O errors. Ollama models are large (2–40 GB each) and your drive is running out of space.

Check how much space your models are using

# See all models and their sizes
ollama list

# Delete a model you no longer use
ollama rm mistral

Move your model storage to a larger drive

Set the OLLAMA_MODELS environment variable to point to a drive with more space:

# Windows — set permanently via System Environment Variables
# Name: OLLAMA_MODELS
# Value: D:\OllamaModels   (change D: to your larger drive)

# Then move existing models manually:
Move-Item "$env:USERPROFILE\.ollama\models" "D:\OllamaModels" -Force

Fix 14: Ollama API Not Responding

You’re building an app or using Open WebUI and the API at http://localhost:11434 returns connection errors or timeouts.

Verify the API server is running

# Test the API directly in PowerShell
Invoke-WebRequest http://localhost:11434

# Should return: Ollama is running

Enable external access to the API (for network use)

By default, Ollama only listens on 127.0.0.1 (your local machine only). To allow other devices on your network to access it:

# Windows PowerShell — allow network access
$env:OLLAMA_HOST = "0.0.0.0:11434"
ollama serve

Security note: Only enable 0.0.0.0 on trusted local networks. Never expose port 11434 to the public internet without authentication in front of it.

Fix 15: Nothing Worked — Complete Clean Reinstall Guide

When every other fix has failed, a clean reinstall almost always resolves deep configuration problems. Here is the complete process for Windows.

Step 1 — Uninstall Ollama

Go to Settings → Apps → Installed Apps, search for “Ollama”, click it, and select Uninstall. Wait for the process to complete.

Step 2 — Delete residual files

# Delete Ollama program files
Remove-Item "$env:LOCALAPPDATA\Programs\Ollama" -Recurse -Force

# Delete Ollama config (keeps your models intact)
Remove-Item "$env:LOCALAPPDATA\Ollama" -Recurse -Force

# Optional: delete models too (if you want completely fresh start)
# Remove-Item "$env:USERPROFILE\.ollama" -Recurse -Force

Step 3 — Reboot

Restart your PC before reinstalling. This clears any locked files or orphaned processes.

Step 4 — Download fresh from official source

Always download Ollama from ollama.com/download only. Avoid third-party sites. Run the installer and follow the setup wizard.

Step 5 — Test before loading models

ollama --version
ollama serve
# Open new terminal:
ollama run phi3:mini

Start with the smallest model (phi3:mini at 2.3 GB) to confirm the installation is working before downloading larger ones.

Useful Environment Variables — Ollama Configuration Reference

These variables let you fine-tune Ollama’s behaviour without editing config files. Set them before running ollama serve:

Frequently Asked Questions

What to Read Next

• ⬅️ How to Install Ollama on Windows → (Start from the beginning)

Still stuck after following this guide? Describe your exact error in the comments below — I personally help every reader who runs into problems.

About this guide: Written based on real troubleshooting experience across Windows 10, Windows 11, macOS, and Ubuntu. All fixes verified with Ollama v0.6.x in March 2026.