Install Ollama on Windows 10/11 (2026): 5-Minute Guide

Install Ollama on Windows (Step-by-Step, November 2026)

Published on March 17, 2026 • 18 min read • Last Updated: November 2, 2026

How to install Ollama on Windows (3 steps): (1) Download OllamaSetup.exe from ollama.com — it is free and, in Ollama's own words, "does not require Administrator". (2) Run the installer; it puts Ollama in your user folder and adds it to your PATH. (3) Open a new PowerShell window and run ollama run gemma3:4b — it pulls the 3.4GB model and starts chatting. That's it. Verify with ollama --version first if you like (the current release is v0.40.13, 28 October 2026). It needs Windows 10 22H2 or newer, Home or Pro, and 8GB+ RAM. An NVIDIA or AMD GPU is optional — Ollama runs on the CPU without one, just slower.

Express Setup: AI Running in 5 Minutes

The shortest path from nothing to a chat window:

How long it takes is your download speed, not the installer. The installer plus a 3.4GB model is roughly 5GB of download; at 100 Mbps that is about seven minutes of transfer, at 300 Mbps about two and a half. The install itself is a few clicks.

Slower internet? Pull the model first and walk away. Models resume if the connection drops, and ollama pull prints a live progress bar so you can see where it is.

---

Do I Need the Terminal? The Native Ollama Windows App (No PowerShell Required)

Ollama ships a desktop app with a real chat window, so you never have to touch PowerShell if you don't want to. The app arrived in Ollama v0.10.0 (July 2025) for macOS and Windows and has shipped in every release since — the current build as of 2 November 2026 is v0.40.13.

When you run the same OllamaSetup.exe installer, the desktop app is included automatically. After installing:

1. Ollama starts in the background and adds an icon to your Windows system tray (bottom-right, near the clock).
2. Click the tray icon (or the Start-menu shortcut) to open the chat window.
3. Pick a model from the dropdown at the top — if you haven't downloaded one yet, choosing it triggers the download.
4. Type a message and chat, exactly like ChatGPT, but 100% local.

The app also lets you drag and drop a text file or PDF into the chat, send images to vision models such as Gemma, raise the context length in settings for long documents (Ollama's own post notes that a larger context "requires more memory"), and switch models with one click. It talks to the exact same local engine on http://localhost:11434, so anything you do in the GUI shows up in ollama list and vice-versa.

If you want a deeper, all-platform walkthrough of features, commands, and the API, see our complete Ollama guide.

---

Complete Installation Guide (10-15 Minutes with Best Practices)

If you have time, this longer path sets you up properly with GPU drivers, the right first model, and troubleshooting prep:

To install Ollama on Windows properly:

1. (Optional) Update your GPU driver first → NVIDIA drivers (Ollama's Windows docs ask for 551.61 or newer) or the current AMD Adrenalin driver (5 extra minutes)
2. Download OllamaSetup.exe from ollama.com (1.56 GB)
3. Run the installer on your normal account — no "Run as administrator" needed
4. Open a new PowerShell/CMD window and verify: ollama --version
5. Download a model matched to your RAM: ollama pull llama3.1:8b (4.9GB) on 16GB machines, ollama pull gemma3:4b (3.4GB) on 8GB
6. Start chatting: ollama run llama3.1:8b

Total time: 10-15 minutes with the driver update | Requirements: Windows 10 22H2 or newer, 8GB+ RAM | Cost: Free

New to local AI? Read our 8GB RAM model comparison to see which models fit your hardware. Need a GPU upgrade? Check the GPU buying guide for performance comparisons.

---

Quick Summary:

• ✅ Install Ollama on Windows 10/11 in under 10 minutes, without admin rights
• ✅ Let Ollama use your NVIDIA or AMD GPU (it ships its own CUDA libraries)
• ✅ Download and run your first AI model
• ✅ Troubleshoot common Windows-specific issues
• ✅ Set up PowerShell and Command Prompt integration

Installing Ollama on Windows has become straightforward, but people still trip over three things: an old PowerShell window that cannot see the new PATH, a GPU driver older than Ollama wants, and a first model too big for their RAM. This guide walks through every step, from download to running your first model with the GPU actually in use.

Rolling out across every OS? Pair this Windows walkthrough with the Mac setup guide and the Linux install playbook so you have a consistent, privacy-first stack on every workstation. Dual-booting or running WSL? The same Linux guide covers the Ubuntu side of the Ollama stack in detail.

Once you're installed, pick a model from the best Ollama models ranking, review the 8GB-friendly picks for lightweight systems, and keep the Ollama troubleshooting guide nearby for quick fixes.

Table of Contents

1. System Requirements
2. Pre-Installation Checklist
3. Step-by-Step Installation
4. GPU Configuration
5. Installing Your First Model
6. PowerShell and CMD Setup
7. Performance Optimization
8. Troubleshooting Common Issues
9. Advanced Configuration
10. Next Steps

---

Why Choose Local AI on Windows?

Running AI models locally on your Windows machine offers significant advantages over cloud-based solutions:

🔒 Complete Privacy: Your data never leaves your computer. Ollama's own FAQ puts it plainly: "Ollama runs locally. We don't see your prompts or data when you run locally." Perfect for sensitive work, proprietary code, or personal information.

💰 Zero Ongoing Costs: After your initial hardware investment, there are no monthly subscriptions. Learn more in our cost comparison: Local AI vs ChatGPT.

⚡ Instant Response, No Limits: No API rate limits, no queuing, no "we're experiencing high demand" errors. Your model runs at full speed 24/7. Plus, you can run multiple models simultaneously if you have the RAM.

🎯 Full Customization: Create custom system prompts with a Modelfile, adjust parameters for your specific needs, and integrate AI directly into applications without vendor lock-in.

🌐 Offline Capability: Once models are downloaded, Ollama works completely offline. Perfect for air-gapped environments, travel, or unreliable internet.

For Windows users specifically: Ollama has first-class Windows support with native GPU acceleration via CUDA, ROCm and Vulkan, so it performs the same as on Linux. The installation is straightforward, and you keep using your familiar Windows tools and workflows.

Ready to get started? Let's check if your system meets the requirements.

---

System Requirements

Before installing Ollama on Windows, ensure your system meets these requirements (all from Ollama's Windows documentation and hardware support page):

Minimum Requirements:

• OS: Windows 10 22H2 or newer, Home or Pro; Windows 11
• RAM: 8GB (16GB recommended)
• Storage: at least 4GB for the Ollama binaries, plus space for models
• CPU: 64-bit x86 processor (an ARM64 build, ollama-windows-arm64.zip, also ships)
• Internet: Required for initial download and model fetching

Recommended Requirements:

• OS: Windows 11
• RAM: 16GB or more
• Storage: 50GB+ SSD space
• GPU: NVIDIA GPU with 8GB+ VRAM, or a Radeon RX 7000-series
• CPU: 8+ cores for CPU-only inference

GPU Requirements (Optional but Recommended):

• NVIDIA: compute capability 5.0 or newer (GTX 900 series onward) with driver 550 or newer; cards at compute capability 5.0–6.2 (GTX 900/1000 series) need driver 570 or newer. Ollama's Windows page asks for 551.61+.
• AMD (ROCm): Radeon RX 7900 XTX / XT / GRE, RX 7800 XT, RX 7700 XT, RX 7600 XT / 7600, and Radeon PRO W7900 / W7800 / W7700 / W7600 / W7500, with an "AMD ROCm v7 / HIP7-capable driver stack"
• Anything else (older Radeons, Intel Arc): Vulkan, which Ollama enables by default and which "requires no additional setup steps" on Windows with the vendor's normal driver

---

Does Ollama Need Admin Rights, and Where Does It Install?

Short answer: no, the standard OllamaSetup.exe install does NOT require administrator rights. Ollama's Windows docs say it directly: "The Ollama install does not require Administrator, and installs in your home directory by default." It is a per-user install — it puts the program inside your own account folder instead of C:\Program Files, so it runs fine on locked-down work laptops and Windows 10/11 Home where you're not an admin.

Here's exactly where everything lands so you can find (or clean up) it later:

A few practical notes:

• You can paste any of those paths (e.g. %LOCALAPPDATA%\Programs\Ollama) straight into the File Explorer address bar to jump there.
• You can choose a different program folder from the command line: OllamaSetup.exe /DIR="D:\some\location". The part that actually eats disk space — the models — moves with the OLLAMA_MODELS environment variable (covered in Performance Optimization below).
• Some corporate machines block .exe files via SmartScreen or AppLocker even without admin; if that's you, ask IT to whitelist OllamaSetup.exe, or use the zip build described under Method 2.

Worried whether your machine can even run a model before you install? Run the numbers against our Ollama system requirements guide first — it breaks down exactly which model sizes fit 8GB, 16GB, and 32GB of RAM — and the Ollama model RAM & VRAM table has the file size of every family.

---

Pre-Installation Checklist

1. Check Windows Version

# Open PowerShell and run:
winver
# Ensure you have Windows 10 22H2 or newer, or Windows 11

2. Verify System Architecture

# Check if you have 64-bit Windows:
wmic os get osarchitecture
# Should return "64-bit"

3. Check Available Storage

# Check available disk space:
Get-PSDrive C | Select-Object Used,Free
# Ensure at least 4GB for Ollama plus room for the models you want

4. Update Windows

Ensure Windows is fully updated to avoid compatibility issues:

• Settings → Update & Security → Windows Update → Check for updates

5. Update Your GPU Driver

Not antivirus — the driver. Ollama's docs say the most common "GPU not detected" cause is an old driver. Grab the current NVIDIA driver (551.61 or newer for Windows) or AMD Adrenalin before you install; leave Windows Defender exactly as it is.

---

🚫 Common Mistakes to Avoid

---

Step-by-Step Installation

Method 1: Official Installer (Recommended)

Step 1: Download Ollama

1. Visit ollama.com/download/windows
2. Click "Download for Windows"
3. Save the OllamaSetup.exe file (1.56 GB as of v0.40.13)

Step 2: Run the Installer

1. Double-click OllamaSetup.exe — no "Run as administrator" needed
2. If Windows Defender SmartScreen appears:
   • Click "More info"
   • Click "Run anyway"
3. Follow the installation wizard. It installs to %LOCALAPPDATA%\Programs\Ollama and adds that folder to your user PATH; to install elsewhere, start it from a terminal as OllamaSetup.exe /DIR="D:\Ollama"

Step 3: Verify Installation

# Open a new PowerShell window (important: must be new)
ollama --version
# Should display the installed version, e.g. ollama version is 0.40.13

Method 2: Silent Install or the Standalone Zip (Advanced)

The installer accepts standard flags, so you can script it:

# Download installer
Invoke-WebRequest -Uri "https://ollama.com/download/OllamaSetup.exe" -OutFile "$env:TEMP\OllamaSetup.exe"

# Install silently (optionally with a custom program folder)
Start-Process -FilePath "$env:TEMP\OllamaSetup.exe" -ArgumentList '/S /DIR="D:\Ollama"' -Wait

# Refresh PATH in this window instead of opening a new one
$env:Path = [System.Environment]::GetEnvironmentVariable("Path","Machine") + ";" + [System.Environment]::GetEnvironmentVariable("Path","User")
ollama --version

If you want only the CLI — for a service, a container, or a machine where .exe installers are blocked — Ollama publishes ollama-windows-amd64.zip (1.49 GB, "contains the CLI and Nvidia GPU libraries only"). Unzip it anywhere, add an extra package to the same folder if you need it (ollama-windows-amd64-rocm.zip for AMD, 245 MB), and run ollama serve from that folder. Ollama's docs suggest NSSM if you want it to run as a Windows service — see Advanced Configuration.

---

GPU Configuration

NVIDIA GPU Setup

Step 1: Install a Current Driver (not the CUDA Toolkit)

1. Download the current driver from nvidia.com — Ollama's Windows docs ask for 551.61 or newer, and its hardware page says GTX 900/1000-series cards (compute capability 5.0–6.2) need 570 or newer
2. Run the driver installer, choose "Express"
3. Restart if it asks

You do not install the CUDA Toolkit. OllamaSetup.exe bundles the CUDA runtime libraries it needs; the toolkit is for people compiling CUDA code.

Step 2: Verify the Driver Sees the Card

nvidia-smi
# Should display GPU name, driver version and memory

Step 3: Confirm Ollama Is Using the GPU

# Load a model, then ask Ollama where it is running
ollama run llama3.2 "hello"
ollama ps
# PROCESSOR column should read "100% GPU" (or a GPU/CPU split if the model is too big for VRAM)

There is no switch to "enable CUDA" — if the driver is new enough, Ollama uses the card. If ollama ps shows 100% CPU, jump to Issue 3.

AMD GPU Setup

# RX 7000-series / PRO W7000: install the current AMD Adrenalin driver (ROCm v7 / HIP7 capable), then:
ollama run llama3.2 "hello"
ollama ps      # expect "100% GPU"

# Older Radeons (e.g. RX 6000): Ollama falls back to Vulkan automatically — no setup needed

---

Installing Your First Model

Step 1: Start Ollama Service

The tray app already runs the server. Only if you quit it (or use the zip build) do you need:

ollama serve
# Keep this window open

Step 2: Download a Model

Open a new PowerShell window:

# Download Gemma 3 4B (3.4GB, text + images, good for testing)
ollama pull gemma3:4b

# For limited RAM (8GB), use a smaller model:
ollama pull llama3.2          # 2.0GB

# For a 16GB machine or an 8GB GPU:
ollama pull llama3.1:8b       # 4.9GB

# For a 48GB+ workstation:
ollama pull llama3.3:70b      # 43GB

Which Model Should I Download First in 2026?

The model names have moved on since this guide first published. Here are the current go-to picks matched to common Windows RAM tiers — every tag and size below was checked on the Ollama library on 2 November 2026:

The classic llama3.2 and phi3:mini (2.2GB) commands still work and are perfectly fine for a quick first test. For a ranked breakdown of all the top options — including the best pick per library category — see our best Ollama models guide, and if you're on a tight memory budget, the best models for 8GB RAM.

Step 3: Run the Model

# Start interactive chat
ollama run gemma3:4b

# Example prompt:
> Write a hello world program in Python

# Exit with /bye or Ctrl+D

Step 4: List Installed Models

# See all downloaded models
ollama list

# See what is loaded right now, and whether it is on the GPU
ollama ps

# Remove a model
ollama rm model_name

---

PowerShell and CMD Setup

PowerShell Configuration

Create an Ollama profile for PowerShell:

# Create PowerShell profile
New-Item -Path $PROFILE -Type File -Force

# Add Ollama aliases
Add-Content $PROFILE @"
# Ollama Aliases
function ai { ollama run gemma3:4b }
function models { ollama list }
function pull { param($model) ollama pull $model }
"@

# Reload profile
. $PROFILE

Command Prompt (CMD) Setup

Create batch files for easier access:

# Create C:\ollama-scripts\ai.bat
@echo off
ollama run gemma3:4b %*

# Create C:\ollama-scripts\models.bat
@echo off
ollama list

# Add to PATH
setx PATH "%PATH%;C:\ollama-scripts"

Windows Terminal Integration

Add Ollama profile to Windows Terminal:

1. Open Windows Terminal
2. Settings → Add new profile
3. Configure:
   • Name: Ollama AI
   • Command line: powershell.exe -NoExit -Command "ollama run gemma3:4b"
   • Starting directory: %USERPROFILE%
   • Icon: 🤖

---

Performance Optimization

Every variable below is documented in Ollama's FAQ. On Windows, Ollama "inherits your user and system environment variables", so the recipe is always the same: quit Ollama from the tray, set the variable for your user account (Settings → search "environment variables" → Edit environment variables for your account), then start Ollama again from the Start menu. The PowerShell one-liners below do the same thing.

1. Keep Models Loaded Longer

# Models unload after 5 minutes of idle by default. Keep them resident for an hour:
[Environment]::SetEnvironmentVariable("OLLAMA_KEEP_ALIVE", "1h", "User")
# Or forever (until you run out of memory):
[Environment]::SetEnvironmentVariable("OLLAMA_KEEP_ALIVE", "-1", "User")

2. Context Length and Parallelism

# Ollama uses a 4096-token context by default. Raise it for every model (costs VRAM):
[Environment]::SetEnvironmentVariable("OLLAMA_CONTEXT_LENGTH", "16384", "User")

# Handle more than one request at a time per model (default 1):
[Environment]::SetEnvironmentVariable("OLLAMA_NUM_PARALLEL", "2", "User")

# Cap how many models stay loaded at once:
[Environment]::SetEnvironmentVariable("OLLAMA_MAX_LOADED_MODELS", "2", "User")

3. Storage Optimization

# Move model storage to a faster or bigger SSD
$newPath = "D:\OllamaModels"
New-Item -ItemType Directory -Path $newPath -Force
[Environment]::SetEnvironmentVariable("OLLAMA_MODELS", $newPath, "User")
# Quit the tray app and relaunch it so the change is picked up

4. Network Optimization

# Behind a corporate proxy? Ollama pulls over HTTPS only, so set HTTPS_PROXY (not HTTP_PROXY):
[Environment]::SetEnvironmentVariable("HTTPS_PROXY", "http://proxy.example.com:8080", "User")

# Let other machines on your LAN reach the API (default binds 127.0.0.1:11434):
[Environment]::SetEnvironmentVariable("OLLAMA_HOST", "0.0.0.0:11434", "User")

---

Troubleshooting Common Issues

The first place to look for any of these is %LOCALAPPDATA%\Ollama\server.log (press Win + R, run explorer %LOCALAPPDATA%\Ollama). For more detail, quit the tray app and relaunch it with debug logging:

$env:OLLAMA_DEBUG="1"
& "ollama app.exe"

Issue 1: "ollama is not recognized"

Solution:

# Almost always an old window. Open a NEW PowerShell window first. If it still fails:
$ollamaPath = "$env:LOCALAPPDATA\Programs\Ollama"
[Environment]::SetEnvironmentVariable("Path", "$env:Path;$ollamaPath", "User")

# Then open another new window, or refresh this one:
$env:Path = [System.Environment]::GetEnvironmentVariable("Path","Machine") + ";" + [System.Environment]::GetEnvironmentVariable("Path","User")

Issue 2: "Windows Defender blocks Ollama"

Solution:

1. Windows Security → Virus & threat protection
2. Protection history → Find blocked item
3. Actions → Allow on device
4. Add exclusion: Settings → Add or remove exclusions
5. Add folder: %LOCALAPPDATA%\Programs\Ollama

Issue 3: "GPU not detected" (ollama ps shows 100% CPU)

Solution:

# 1. Check the driver version
nvidia-smi
# Needs 550+ (570+ for GTX 900/1000 series). Update from nvidia.com if older.

# 2. Check what Ollama found at startup
Select-String -Path "$env:LOCALAPPDATA\Ollama\server.log" -Pattern "inference compute"

# 3. If you have more than one GPU, pin the one you want (NVIDIA)
[Environment]::SetEnvironmentVariable("CUDA_VISIBLE_DEVICES", "0", "User")

Issue 4: "Model download fails"

Solution:

# Pulls resume — just run it again
ollama pull gemma3:4b

# Behind a proxy, set HTTPS_PROXY (see Performance Optimization) and relaunch Ollama

# If a partial download is corrupt, remove the model and pull it fresh
ollama rm gemma3:4b
ollama pull gemma3:4b

Issue 5: "Out of memory error"

Solution:

# Use a smaller model or a smaller quant
ollama pull llama3.2          # 2.0GB instead of a 4.9GB 8B

# Limit context size inside a chat session (default 4096)
ollama run llama3.1:8b
>>> /set parameter num_ctx 2048

# Close other applications holding memory
Get-Process | Where-Object {$_.WorkingSet -gt 500MB} | Select-Object Name, @{n='Memory(GB)';e={$_.WorkingSet/1GB}}

Issue 6: "Port 11434 already in use"

Solution:

# Usually the tray app is already running — that is fine; just use the CLI
# Otherwise find the process using port 11434
netstat -ano | findstr :11434

# Kill the process (replace PID with actual process ID)
taskkill /PID <process_id> /F

# Or change Ollama's default port
[Environment]::SetEnvironmentVariable("OLLAMA_HOST", "127.0.0.1:11435", "User")

Issue 7: "Permission denied" when accessing model directory

Solution:

# Point models at a folder your account owns
$newPath = "$env:USERPROFILE\OllamaModels"
New-Item -ItemType Directory -Path $newPath -Force
[Environment]::SetEnvironmentVariable("OLLAMA_MODELS", $newPath, "User")

# Move existing models, then quit and relaunch Ollama
Move-Item "$env:USERPROFILE\.ollama\models\*" $newPath -Force

Issue 8: "Extremely slow performance on laptop"

Solution:

# Set Windows power plan to High Performance
powercfg /setactive SCHEME_MIN

# Ensure laptop is plugged in (many laptops throttle on battery)
# Check power mode: Settings → System → Power & battery → Power mode: Best performance

# For laptops with NVIDIA Optimus, force Ollama to use the dedicated GPU:
# NVIDIA Control Panel → Manage 3D settings → Program Settings
# Add ollama.exe → Select "High-performance NVIDIA processor"

# Then confirm:
ollama ps     # PROCESSOR should read 100% GPU

Issue 9: "Windows Firewall blocks API access"

Solution:

# Only needed if you set OLLAMA_HOST to 0.0.0.0 for other machines
New-NetFirewallRule -DisplayName "Ollama API" -Direction Inbound -Protocol TCP -LocalPort 11434 -Action Allow

# Test API access
Invoke-RestMethod -Uri "http://localhost:11434/api/tags" -Method Get

Issue 10: "Model loading is very slow (2+ minutes)"

Symptoms: Model takes 2-5 minutes to load each time you run it.

Solution:

# 1. Check if models are on HDD (not SSD)
Get-PSDrive | Select-Object Name,Root,Provider

# 2. Move models to SSD
$ssdPath = "C:\OllamaModels"  # Change to your SSD drive
New-Item -ItemType Directory -Path $ssdPath -Force
[Environment]::SetEnvironmentVariable("OLLAMA_MODELS", $ssdPath, "User")

# 3. Exclude the model folder from Defender real-time scanning
Add-MpPreference -ExclusionPath $ssdPath

# 4. Keep the model resident between prompts so it only loads once
[Environment]::SetEnvironmentVariable("OLLAMA_KEEP_ALIVE", "1h", "User")

# 5. Use a smaller model for faster loading
ollama pull llama3.2          # 2.0GB instead of a 43GB 70B

Issue 11: Garbled characters like "←[?25h" in the terminal

Ollama's troubleshooting page lists this as a known bug in older Windows 10 builds (21H1 and earlier), where the terminal cannot display the control characters. The fix is to update to Windows 10 22H2 or newer — the same minimum the installer wants.

Still having issues? Check our Ollama troubleshooting guide — it covers the connection-refused, 500 and llama-runner errors in depth — or Ollama's own troubleshooting docs.

---

Advanced Configuration

Custom Model Configuration

Create a Modelfile:

# Modelfile
FROM llama3.1:8b

# Set parameters
PARAMETER temperature 0.7
PARAMETER top_p 0.9
PARAMETER num_ctx 16384

# System prompt
SYSTEM "You are a helpful Windows expert assistant."

# Save as Modelfile (no extension), then:
# ollama create windows-assistant -f Modelfile

API Configuration

The API is on by default at http://localhost:11434; nothing to enable.

# Test API
Invoke-RestMethod -Uri "http://localhost:11434/api/tags" -Method Get

# Generate text via API
$body = @{
    model = "llama3.1:8b"
    prompt = "Hello, how are you?"
    stream = $false
} | ConvertTo-Json

Invoke-RestMethod -Uri "http://localhost:11434/api/generate" -Method Post -Body $body -ContentType "application/json"

# To reach it from other machines, set OLLAMA_HOST to 0.0.0.0:11434 (see Performance Optimization)

Running as Windows Service

The tray app is the normal way to keep Ollama running. If you need a true service (a headless box, a shared machine), Ollama's docs point to the standalone zip plus NSSM:

# 1. Unzip ollama-windows-amd64.zip to, say, C:\Ollama
# 2. Install NSSM, then register "ollama serve" as a service
nssm install Ollama "C:\Ollama\ollama.exe" serve
nssm set Ollama AppEnvironmentExtra OLLAMA_MODELS=D:\OllamaModels
nssm start Ollama

# Check service status
Get-Service -Name "Ollama"

---

Security Considerations

1. Firewall Configuration

# Ollama binds 127.0.0.1 by default, so nothing outside the machine can reach it.
# Only if you expose it (OLLAMA_HOST=0.0.0.0) should you open the port — and then restrict who may connect:
New-NetFirewallRule -DisplayName "Ollama LAN only" -Direction Inbound -Protocol TCP -LocalPort 11434 -RemoteAddress 192.168.1.0/24 -Action Allow

2. User Permissions

The per-user install already keeps the binaries, logs and models inside your own profile, where other standard accounts on the machine cannot read them. Nothing to tighten unless you moved OLLAMA_MODELS to a shared drive.

3. Privacy

There is no telemetry switch because there is nothing to switch off for local models — Ollama's FAQ: "Ollama runs locally. We don't see your prompts or data when you run locally." The one thing that does leave the machine is a cloud-model request (tags ending in :cloud). To rule even that out:

[Environment]::SetEnvironmentVariable("OLLAMA_NO_CLOUD", "1", "User")

Our securing Ollama guide covers reverse proxies and authentication if you do expose the API.

---

Performance Benchmarks

Nobody's tokens-per-second transfers to your machine, so this table does not pretend to be a stopwatch reading. It is the arithmetic ceiling for each card: the vendor's published memory bandwidth divided by the model's download size on the Ollama library. Real output lands below it — the ceiling is the number you cannot beat, and the one that tells you which models are worth trying on which card.

"Won't fit" is the row that matters most: once a model spills out of VRAM, Ollama offloads layers to system RAM and those layers run at the DDR figure in the last row. For the one measured table on this site — the same prompt run seven times per model on a single machine — see the best Ollama models guide, and for the reasoning behind the formula, GPU memory bandwidth for local LLMs.

---

Next Steps

Now that Ollama is installed and running on Windows:

1. Explore More Models

# Browse available models
Start-Process "https://ollama.com/library"

# Try specialized models
ollama pull qwen2.5-coder:7b   # For programming (4.7GB)
ollama pull mistral            # For general chat (4.4GB)
ollama pull deepseek-r1:8b     # Visible chain-of-thought (5.2GB)
ollama pull dolphin-mixtral    # Low-refusal, 26GB — 24GB+ cards only

2. Build Applications

• Install Continue.dev for VS Code integration
• Try Open WebUI for ChatGPT-like interface
• Explore LangChain for building AI apps

3. Join the Community

• Ollama Discord
• r/LocalLLaMA Reddit
• Ollama GitHub

---

Frequently Asked Questions

Q: Can I run Ollama on Windows 7, 8, or an early Windows 10 build?

A: No. Ollama's Windows docs require Windows 10 22H2 or newer (Home or Pro) or Windows 11. Builds before 22H2 also hit the garbled-terminal bug described in Issue 11.

Q: How much disk space do models really need?

A: The library lists the download for every tag. Typical first picks:

• Small (Llama 3.2 3B, Phi-4 Mini, Gemma 3 4B): 2.0–3.4GB
• Medium (Llama 3.1 8B, Qwen 2.5 Coder 7B, DeepSeek-R1 8B): 4.7–5.2GB
• Large (DeepSeek-R1 14B, gpt-oss 20B, Qwen3.8 27B): 9–18GB
• Extra Large (Llama 3.3 70B): 43GB

Q: Can I use Ollama offline after installation?

A: Yes! Once models are downloaded, Ollama works completely offline. You only need internet to download new models or updates.

Q: Is my data private when using Ollama?

A: For local models, yes — all processing happens on your Windows machine, and Ollama's FAQ states it does not see your prompts. Only the optional :cloud tags send a request to Ollama's servers.

Q: Can I run multiple models simultaneously?

A: Yes, if you have enough memory. Ollama keeps several models loaded at once (cap it with OLLAMA_MAX_LOADED_MODELS) and serves them through the same API.

---

Conclusion

You've successfully installed Ollama on Windows and are ready to explore the world of local AI. With your setup complete, you have:

• ✅ Full privacy and control over your AI
• ✅ No subscription fees or API costs
• ✅ Ability to run models offline
• ✅ Complete customization options
• ✅ Integration with Windows tools and workflows

Ollama on Windows updates itself: the tray app downloads new releases in the background and shows "Restart to update" when one is ready. Explore new models as they're released — the library adds several a week — and pick from the ranked list when you do.

---

Next Steps

1. Find the best Ollama models for your hardware — our ranked guide to the top 15 models and the best pick per library category
2. Set up Open WebUI — get a ChatGPT-like interface for your Ollama models
3. Set up AI coding with Continue.dev — free Copilot alternative using Ollama
4. Understand GGUF vs GPTQ vs AWQ quantization — learn which format Ollama uses and why
5. Find models for 8GB RAM — budget-friendly model recommendations
6. Fix any Ollama error — connection refused, 500s, GPU not used, slow pulls