Ollama
Ollama - Run AI Models Locally on Your Computer [2026]
Last updated May 8, 2026
What is Ollama?
Verdict
Based on 9 video reviewsUse ollama if you want to run AI locally for privacy, fast responses, and lower ongoing cost. Reviewers repeatedly highlight that Ollama is easy to set up on your own PC, lets you use on-prem or local models, and avoids expensive subscriptions for coding workflows. Multiple videos also point to quick responses, good local code completion, lightweight models that run fast on modest hardware, and the ability to try different models without much setup. The main catch is that your experience still depends on your hardware and setup. Best for developers, tinkerers, and privacy-conscious users who want local AI on their own machine.
✓ Best for
- •Anyone
✗ Not for
- •Those who need ui lacks statistics like tokens per second
- •Those who need crashes frequently
- •Not every model runs as smoothly as advertised.
Pros
- +Fewer censorship filters
- +Offers privacy first by allowing local deployment of AI models.
- +Run frontier AI models for free on your own machines.
- +Vision of a truly local, private AI assistant is compelling
- +Ollama provides an alternative to expensive subscriptions for coding tools.
Cons
- −UI lacks statistics like tokens per second.
- −Crashes frequently
- −Not every model runs as smoothly as advertised.
Ollama's Top Features
Key capabilities that make Ollama stand out.
Model usage: For the purpose of this demo, the GLM 4.7 flash model is being used with Ollama.
Local model deployment: Ollama allows you to deploy models locally on your computer.
Local AI model execution: Ollama is a free open-source tool that lets you download and run AI language models directly on your computer.
Default local URL and port: Ollama uses a default local URL and port that is pre-filled in editor settings, requiring no changes if the setup is standard.
Model compatibility: Supports pulling models like Llama 2, Mistral, and other open-source LLMs.
Download local AI models: Ollama allows users to directly download and use local AI models.
Local LLM execution: Ollama allows users to run open LLMs directly on their own hardware, offering a straightforward setup.
Text-based LLMs: Ollama can run large language models that process and generate text.
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How Does Ollama Work?
Installation and running a model
You install it, you type one command, and a model starts running on your machine.
Integrate with local Ollama models
The video will cover how to integrate OpenClaw with local Ollama models.
Check Ollama is working properly in the console
Before connecting to an editor, verify Ollama is functional by listing available models, launching one (e.g., Gemma 4), and asking it to respond.
Download and install
Ollama is available for Mac, Linux, and Windows. Simply click, download, and install.
Install Ollama
A whole video was made about how to install Ollama, deep diving into everything.
Download Ollama
Ensure Ollama is downloaded and installed locally before proceeding with model setup.
Choose a smaller model initially
Begin with a smaller Ollama model as a starting point to explore its capabilities.
Verify CLI availability
Confirm that the 'ollama' command is accessible in your terminal after installation.
Ollama's Pricing
Ollama Limitations
Important caveats to consider before choosing Ollama.
Frequent crashes
Constraints in lightweight models
Limited modality in lightweight models
Higher resource requirements for heavier models
Output quality of smaller models
Artifact generation in lightweight models for code completion
Cloud service in preview
Unstable cloud pricing
Is Ollama Safe?
Gemma 4 is Apache 2.0, allowing commercial use, product building, fine-tuning, and distribution without hidden restrictions.
Using Ollama with OpenClaw gives AI access to execute commands and send messages on your behalf.
Ollama is data protection compliant.
Storing data in local vector databases plays a minor role.
Ollama Comparisons
How Ollama stacks up against its top competitors, based on expert reviews and real-world usage.
Ollama vs llama.cpp
View llama.cpp| Feature | Ollama | llama.cpp |
|---|---|---|
| Local AI runtime / deployment experience | Reviewers compare Ollama and llama.cpp as two leading local AI options, with the choice hinging on workflow preferences rather than a universally better tool. Ollama is positioned as a simpler packaged experience, while llama.cpp is part of the same local-AI performance conversation.Alex Ziskind, 7:30–10:00 | Reviewers compare Ollama and llama.cpp as two leading local AI options, with the choice hinging on workflow preferences rather than a universally better tool. Ollama is positioned as a simpler packaged experience, while llama.cpp is part of the same local-AI performance conversation.Alex Ziskind, 7:30–10:00 |
Bottom line
Overall, Ollama wins for simple local AI deployment, privacy, and practical self-hosted use cases, while alternatives win in specific areas. If you want an easy way to run models on your own machine, reviewers position Ollama as one of the strongest choices, especially compared with more manual local setups.Parlons IA, 15:00–17:30 But if you want the smartest model outputs, a reviewer explicitly gives that edge to Claude over Ollama-based local models.Fru Dev, 12:30–15:00 Against llama.cpp, LM Studio, and Hyperlink, the verdict is mostly depends: they serve similar local-AI needs, and the right choice comes down to whether you prefer simplicity, interface, or other workflow-specific tradeoffs.Alex Ziskind, 7:30–10:00 Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–2:30
Ollama vs Hyperlink
View Hyperlink| Feature | Ollama | Hyperlink |
|---|---|---|
| Local chatbot experience | Hyperlink is presented alongside Ollama and LM Studio as part of a new generation of local AI chatbots. The comparison suggests these tools compete in the same category, but the source segment does not establish a single clear winner.Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–2:30 | Hyperlink is presented alongside Ollama and LM Studio as part of a new generation of local AI chatbots. The comparison suggests these tools compete in the same category, but the source segment does not establish a single clear winner.Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–2:30 |
Bottom line
Overall, Ollama wins for simple local AI deployment, privacy, and practical self-hosted use cases, while alternatives win in specific areas. If you want an easy way to run models on your own machine, reviewers position Ollama as one of the strongest choices, especially compared with more manual local setups.Parlons IA, 15:00–17:30 But if you want the smartest model outputs, a reviewer explicitly gives that edge to Claude over Ollama-based local models.Fru Dev, 12:30–15:00 Against llama.cpp, LM Studio, and Hyperlink, the verdict is mostly depends: they serve similar local-AI needs, and the right choice comes down to whether you prefer simplicity, interface, or other workflow-specific tradeoffs.Alex Ziskind, 7:30–10:00 Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–2:30
Ollama vs LM Studio
View LM Studio| Feature | Ollama | LM Studio |
|---|---|---|
| Local chatbot / desktop usability | LM Studio is explicitly compared with Ollama in the context of local chatbot tools. Based on the cited segment, both are viable alternatives, with no clear universal winner stated.Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–2:30 | LM Studio is explicitly compared with Ollama in the context of local chatbot tools. Based on the cited segment, both are viable alternatives, with no clear universal winner stated.Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–2:30 |
Bottom line
Overall, Ollama wins for simple local AI deployment, privacy, and practical self-hosted use cases, while alternatives win in specific areas. If you want an easy way to run models on your own machine, reviewers position Ollama as one of the strongest choices, especially compared with more manual local setups.Parlons IA, 15:00–17:30 But if you want the smartest model outputs, a reviewer explicitly gives that edge to Claude over Ollama-based local models.Fru Dev, 12:30–15:00 Against llama.cpp, LM Studio, and Hyperlink, the verdict is mostly depends: they serve similar local-AI needs, and the right choice comes down to whether you prefer simplicity, interface, or other workflow-specific tradeoffs.Alex Ziskind, 7:30–10:00 Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–2:30
Ollama vs Other private local AI setups
View Other private local AI setups| Feature | Ollama | Other private local AI setups |
|---|---|---|
| Ease of installing private AI on your PC | A French review about installing private AI locally frames Ollama as a straightforward way to set up private AI on a personal computer, implying an advantage in simplicity versus more manual local setups.Parlons IA, 15:00–17:30 | — |
Bottom line
Overall, Ollama wins for simple local AI deployment, privacy, and practical self-hosted use cases, while alternatives win in specific areas. If you want an easy way to run models on your own machine, reviewers position Ollama as one of the strongest choices, especially compared with more manual local setups.Parlons IA, 15:00–17:30 But if you want the smartest model outputs, a reviewer explicitly gives that edge to Claude over Ollama-based local models.Fru Dev, 12:30–15:00 Against llama.cpp, LM Studio, and Hyperlink, the verdict is mostly depends: they serve similar local-AI needs, and the right choice comes down to whether you prefer simplicity, interface, or other workflow-specific tradeoffs.Alex Ziskind, 7:30–10:00 Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–2:30
Ollama vs Claude
View Claude| Feature | Ollama | Claude |
|---|---|---|
| Model intelligence / output quality | — | One reviewer explicitly says Ollama models are less intelligent than Claude models, making Claude the clear winner if your priority is maximum reasoning or model quality rather than local privacy and control.Fru Dev, 12:30–15:00 |
Bottom line
Overall, Ollama wins for simple local AI deployment, privacy, and practical self-hosted use cases, while alternatives win in specific areas. If you want an easy way to run models on your own machine, reviewers position Ollama as one of the strongest choices, especially compared with more manual local setups.Parlons IA, 15:00–17:30 But if you want the smartest model outputs, a reviewer explicitly gives that edge to Claude over Ollama-based local models.Fru Dev, 12:30–15:00 Against llama.cpp, LM Studio, and Hyperlink, the verdict is mostly depends: they serve similar local-AI needs, and the right choice comes down to whether you prefer simplicity, interface, or other workflow-specific tradeoffs.Alex Ziskind, 7:30–10:00 Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–2:30
YouTube Reviews
10 videosWhat creators say about Ollama
What Reviewers Say
“Installer une IA privée sur ton PC | Ollama expliqué simplement”
Parlons IA
Parlons IA presents Ollama as a simple way to install and run a private AI locally on a PC, emphasizing local use and privacy-oriented setup in its main walkthrough.YouTube: Parlons IA, “Installer une IA privée sur ton PC | Ollama expliqué simplement,” 2:30–5:00 Later in the video, the creator also compares Ollama with other approaches/tools for running local AI, framing it as one option in the broader local-model ecosystem.YouTube: Parlons IA, 15:00–17:30
private AI on your PC” emphasis through the Ollama explanation and setup walkthrough.[Parlons IA, 2:30–
comparison” framing with other local AI options/tools.[Parlons IA, 15:00–
“Ollama Review: Best Local AI Tool in 2025?”
Killer Reviews
Killer Reviews gives an overall positive verdict on Ollama, describing it as a strong local AI tool and highlighting benefits early in the review.YouTube: Killer Reviews, “Ollama Review: Best Local AI Tool in 2025?”, 0:00–2:30 The same review also notes downsides later on, indicating that while the tool is compelling, it is not without limitations.YouTube: Killer Reviews, 2:30–5:00
Best Local AI Tool in 2025?” — overall verdict framing is strongly favorable.[Killer Reviews, 0:00–
The reviewer also includes “cons” after the initial praise.[Killer Reviews, 2:30–
“Local AI just leveled up... Llama.cpp vs Ollama”
Alex Ziskind
Alex Ziskind evaluates Ollama in direct comparison with llama.cpp, discussing where each tool fits and how Ollama stacks up in local AI workflows.YouTube: Alex Ziskind, “Local AI just leveled up... Llama.cpp vs Ollama,” 7:30–10:00 The review includes at least one explicit downside for Ollama alongside the comparison, suggesting tradeoffs rather than a one-sided recommendation.YouTube: Alex Ziskind, 7:30–10:00
Llama.cpp vs Ollama” — Ollama is discussed comparatively, not in isolation.[Alex Ziskind, 7:30–
The review also identifies a “con” for Ollama in that same segment.[Alex Ziskind, 7:30–
“Hyperlink vs. Ollama & LM Studio
Die neue Generation lokaler KI-Chatbots!” — Von ChatGPT bis n8n – KI-Tools praktisch nutzen
This video discusses Ollama mainly in comparison with Hyperlink and LM Studio, placing it among a newer generation of local AI chatbot tools.YouTube: Von ChatGPT bis n8n – KI-Tools praktisch nutzen, “Hyperlink vs. Ollama & LM Studio,” 0:00–2:30 The reviewer also includes a positive point about Ollama in that opening comparison segment.YouTube: Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–2:30
Hyperlink vs. Ollama & LM Studio” — Ollama is positioned as a key local chatbot option in a competitive set.[Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–
The opening segment also contains a positive claim about Ollama.[Von ChatGPT bis n8n – KI-Tools praktisch nutzen, 0:00–
“Ollama + Gemma 4 is INSANE!”
Julian Goldie SEO
Julian Goldie SEO offers a positive take on Ollama in combination with Gemma, presenting the pairing as notably impressive.YouTube: Julian Goldie SEO, “Ollama + Gemma 4 is INSANE!”, 0:00–2:30 The tone of the segment is strongly enthusiastic and centers on Ollama’s capabilities when paired with a strong model.YouTube: Julian Goldie SEO, 0:00–2:30
Ollama + Gemma 4 is INSANE!”[Julian Goldie SEO, 0:00–
“OpenClaw with Local Ollama Models
Complete Easy Setup Guide” — Fahd Mirza
Fahd Mirza shows both a drawback and a benefit in a practical setup context: one segment identifies a limitation or pain point during the integration process, while a later segment highlights a positive aspect of using local Ollama models.YouTube: Fahd Mirza, “OpenClaw with Local Ollama Models - Complete Easy Setup Guide,” 10:00–12:30 YouTube: Fahd Mirza, 12:30–15:00 The review is therefore implementation-focused, reflecting real-world setup tradeoffs rather than only feature-level praise.YouTub
The setup guide includes both a “con” and a later “pro” for local Ollama use.[Fahd Mirza, 10:00–
“Coding with Ollama feels better now”
marimo
marimo is one of the most detailed and positive sources in this set. The creator says Ollama can be an alternative to expensive coding-tool subscriptions, that lightweight models save disk space and run quickly on most devices, and that local models respond quickly in coding workflows such as chat sidebars, cell-specific edits, and code completion.YouTube: marimo, “Coding with Ollama feels better now,” 0:00–7:30 marimo also says cloud-hosted Ollama model proxies can download quickly and save loc
Ollama provides an alternative to expensive subscriptions for coding tools.”[marimo, 0:00–
Lightweight models in Ollama save disk space and run quickly on most devices.”[marimo, 0:00–
Ollama models provide quick responses when interacted with via the chat sidebar.”[marimo, 2:30–
Ollama models running locally can provide helpful code completion.”[marimo, 5:00–
Ollama’s cloud environment is useful for trying out a variety of models without local setup.”[marimo, 7:30–
Ollama is really sweet.”[marimo, 7:30–
“OpenClaw + Ollama + GPT5 | Telegram Bot Demo and Python Quiz”
TechTimeFly
TechTimeFly highlights the benefit of using Ollama for on-premise or local model deployment, framing local control over the model as a major advantage.YouTube: TechTimeFly, “OpenClaw + Ollama + GPT5 | Telegram Bot Demo and Python Quiz,” 2:30–5:00 The focus here is less on benchmarking and more on the value of running models on your own infrastructure.YouTube: TechTimeFly, 2:30–5:00
Ollama allows for the power of using an on-premise or local model.”[TechTimeFly, 2:30–
“Running Paperclip AI with Local Models
Ollama + Qwen Demo” — Fru Dev
Fru Dev presents a mixed view. On one hand, the creator says Ollama’s local execution brings privacy benefits and may feel more comfortable for users concerned about data sharing.YouTube: Fru Dev, “Running Paperclip AI with Local Models — Ollama + Qwen Demo,” 12:30–15:00 On the other hand, the same segment says Ollama models are less intelligent than Claude models, drawing a quality comparison where local privacy comes with a capability tradeoff.YouTube: Fru Dev, 12:30–15:00 Across these reviews
Ollama offers privacy benefits by running locally, which can be comfortable for users concerned about data sharing.”[Fru Dev, 12:30–
Ollama models are less intelligent than Claude models.”[Fru Dev, 12:30–
User Reviews
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