10 top open source AI platforms and tools to try today

I’ve always been a fan of open source AI platforms. My stint as a developer showed me how flawed code can be, especially when developers rush through the process. With open source platforms, coding becomes a joint initiative, and the entire developer community can come together to build better code.

As a marketer, most of what I handle is confidential (client budgets, campaign plans, ad strategies, and more), so knowing exactly where my data goes (and who’s seeing it) matters a lot.

That’s what I love about open source. You get transparency, flexibility, and the option to actually see what’s happening behind the scenes. It’s transparent, customizable, and gives you the freedom to tweak things the way you want. Sure, it takes a bit of setup, and not every model is perfect, but once you find the right ones, it’s hard to go back.

In this article, I’ll walk you through the top 10 open source AI platforms, how I tested them, what works for each tool, what can be improved, their pricing structure, and which ones you should consider to test out.

Table of Contents

• What is open source AI?
• How can marketers use AI?
• What are the ethical considerations before using open source AI?
• 10 Top Open Source AI Platforms and Tools

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What is open source AI?

Open source AI is code that is accessible to everyone for usage, modification of the underlying code, and distribution — subject to prior approval and restricted commercial usage. Thus, open source AI is open to changes from anyone, helping developers adapt the models to the needs of their apps and services.

In the simplest way I can put it: It’s like a group project where the code is public. Anyone can peek at it, fix bugs, add new features, or just fork it and build something better.

Closed tools like ChatGPT or Gemini are kind of like black boxes. You put your data in and you get an output, but you never really know what’s going on behind the scenes or where your data ends up.

With open source, you can see how things work. For marketers, that level of transparency feels reassuring. With open source, I know where my data’s going, and who’s (not) looking at it. Users can also reduce dependency on vendors for updates and support.

Of course, it’s not perfect. Some tools need more setup, documentation can be spotty, and updates rely on the community. But that’s also the fun part — you’re not just a user, you’re part of the build.

Most importantly, for marketers and other end-users, open-source AI is often cheaper compared to closed-source AI.

How can marketers use AI?

In HubSpot’s recent survey, 66% of marketers said they use AI tools in some form. Like most marketers, I also leverage AI in various ways, from project management and graphic design to generating logos and creating content for client businesses.

Here are some ways you can leverage it, too.

Content Creation

Marketers use AI tools to generate ideas and create a blog’s first draft, fast-tracking delivery timelines while reducing overhead costs. Our survey shows 55% of marketers use AI for text-based content creation, while 38% use it for multimedia like images and videos.

I use these tools for editing the first draft to minimize errors, cross-check facts, and polish them before publication. AI platforms also help me with image and video generation and editing.

Automated Workflows

When a marketer is handling multiple clients simultaneously, automating repetitive tasks is crucial to reducing latency. AI helps me with scheduling social media posts, fixing follow-up calls, and routinely collecting feedback.

According to HubSpot’s 2025 State of AI report, 78% of marketers have said that AI reduces time spent on manual tasks like scheduling and data entry. Further, 51% of marketers use AI for email marketing and newsletters.

Marketing Campaigns

Marketers running advertisements on Google use platforms like Google Ads (formerly AdWords) and Google Analytics to understand consumer behavior and how ad campaigns are impacting users. I also used these tools until AI came along, and I decided to switch over for efficiency.

AI tools help me analyze which ads are doing better, redirect spending to target groups, and discover new leads with better conversion rates.

Personalized Assistants

You must have received automated texts like “Hey, you left an item in your cart!” or “Prices just dropped for these items in your cart.”

While the above message does work to remind customers to take action, it’s not as effective as it could be. With open source AI tools, AI can analyze previous interaction data and help create personalized automated messages. Plus, you can be sure that customer data is 100% safe and in your control.

I find these open source tools to be excellent interactive AI assistants too, helping customers with round-the-clock support and other enquiries.

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What are the ethical considerations before using open source AI?

Open source AI is not without flaws. While using these AI tools, I realized how some of them are prone to bias or show incomplete information. Most of these models are in their developmental stages, and contributors are constantly rewriting and updating the code to make them better.

Inherent Bias

Since people write algorithms and train datasets, their biases often get included in AI systems. So, the output also contains bias. Sometimes, open source AI can also be censored by national governments (like DeepSeek censors some controversial aspects of Chinese historical events).

But at the same time, since open source AI models are more collaborative than their closed-source alternatives, there are opportunities for community-led solutions. A diverse set of developers globally can contribute to the underlying code of open source AI to reduce bias related to race and demographic differences.

Incomplete Information

When I used open source AI tools, some of them simply scraped information from the internet and generated a result. A few of them ignored specific prompts and went on to generate something I didn’t ask for.

This made me realize open source AI models are far from perfect. Some models need serious work, while others produce decent results. So, blindly relying on the results of these open source tools would be a mistake.

10 Top Open Source AI Platforms and Tools

There are many open-source AI options. But not all of them are suitable for marketers. Some are for software engineers, while others are best for developing apps.

To help you make a better decision, I’ve created a list of the best open source AI tools based on their features and test performance.

These tools will help you enhance your productivity as well as support your clients’ businesses.

1. Qwen AI

Qwen AI is powered by the Alibaba-backed open source Qwen series models. It has four models specializing in different tasks:

• Qwen3-Max for language.
• Qwen3-VL-235B-A22B for strong vision.
• Qwen3-Coder for coding.
• Qwen3-VL-32B for dense vision language.

You’ve probably seen Qwen pop up in the news recently. The model made headlines after outperforming Western rivals in a real-world trading challenge, where it successfully doubled its portfolio in just a week. For context, GPT-5 reportedly lost almost 60% of its capital during the same period.

I’m not a trader, but it definitely caught my attention. So I was curious: How would that same intelligence translate to something softer like marketing?

How I Tested Qwen AI

I often use an AI assistant like Claude to generate a quick outline for my clients’ blogs. So, for this test, I used Qwen Chat, with Qwen3-Max as the model.

The prompt was simple: To create a blog outline for the “top 10 open source AI tools” (yes, the article you’re reading now) and make it relevant for marketers.

The result was moderately impressive. You can definitely use it as a base to start with. To me, it was as good as closed-source alternatives like ChatGPT.

Qwen Chat generated a detailed outline with a title and divided the blog into multiple sections. It even provided a hook for the introduction and the criteria for selecting the tools.

However, although we’re in 2025, the blog title reads “Top 10 Open Source AI Tools Every Marketer Should Know in 2024.” That was the only technical flaw in the outline. Plus, while the list of tools provided was all open source, it lacked lived experience. For instance, it suggested options like LangChain that are more suited for engineering agents than marketing.

What I like:

• Quick output generation.
• Attention to detail.
• Free to use (you don’t even need to log in or sign up).

What could be improved:

• Minor inaccuracies.

Pricing: The Basic version is free. Advanced models like Qwen-Max, Qwen-Plus, Qwen-Flash, Qwen-VL-Max, and Qwen-Omni-Turbo have tiered pricing structures starting from $0.05 to $1.50 for 1M tokens.

2. Mistral AI

Mistral AI is great for businesses that want to explore agentic AI. It can be trained and fine-tuned by feeding relevant customer data, and then training agents on that information.

Unlike closed-source AI models, I retain control of my data, and using Mistral AI doesn’t mean giving my information away to a third party. Moreover, I can integrate it with my Gmail, Google Calendar, and Google Drive, making it quite convenient. Mistral AI can go through them all and create a summary of my meeting and emails I need to respond to. From there, it can create a to-do list.

How I Tested Mistral AI

Just like Qwen, I used the Mistral AI chatbot to generate a blog outline. The prompt was the same. “Create a blog outline for the ‘top 10 open source AI tools.’ The blog and tools should be relevant for marketers.” This helped me get a comparative perspective of how two open source AI chatbots work.

Unlike Qwen, Mistral AI didn’t provide an opening hook or the criteria for selecting the tools. Instead, it listed 10 different ways in which marketers can use open source AI and didn’t provide the names of tools in the first outline.

So, I gave a follow-up prompt asking for a list of tools for each. It searched the internet and provided me with the tools by sourcing them from existing blogs. Mistral AI also asked if I’d like to go deeper into a specific tool. So, marketers preparing an outline or conducting research can definitely use it to speed up the process.

What I like:

• Follow-up prompts are already included. Users can use these prompts to dive deeper.
• I liked the AI model’s thought process and how it distributed the tools across multiple functionalities (from marketing automation to predictive analytics to image/video editing).

What could be improved:

• The tools were included based on high-ranking blogs on the internet without critically assessing them. Sometimes, a tool was included from its own promotional blog.
• No clear inclusion criteria to understand why a particular tool was included.

Pricing: Mistral AI has a free chat version. Paid plans start at $14.99/month and go up to $50, with custom pricing for enterprises.

3. Ollama

One of the best things about open source models is that they’re really very open to sharing different model weights with users for free. With Ollama, you can access OpenAI’s (the makers of ChatGPT) open source models, DeepSeek, Qwen, and Google’s open source model, Gemma, all from one window.

You can download Ollama on your Windows, Mac, or Linux operating system and operate it directly from your desktop or laptop.

How I Tested Ollama

There are two ways to access the models on Ollama: cloud and downloadable. The cloud models require an Ollama account. I signed in quickly with my Gmail. Alternatively, you can download each model to your desktop or laptop.

I used the same prompt, “Create a blog outline for the ‘top 10 open source AI tools.’ The blog and tools should be relevant for marketers.”

Then I selected OpenAI’s open source model, gpt-oss:120b-cloud, and the thinking level as “low.” The gpt-oss:120b is around 80 GB and takes time to download, depending on your internet speed. The cloud models are much faster, and so I went ahead with the cloud version.

The blog title was on point, and the output generation was really quick. What I found really interesting and different from other AI platforms is how it provided a word limit for each section. Each section was really detailed, and the comparison table was unique. They also included a section on “Real World Success Stories” with examples.

However, I felt some of the tools provided were more suitable for developers and coders than for marketers. Although they can be customized for marketers, I’d have preferred a slightly different set of tools.

What I like:

• Fast output generation.
• In-depth tables with features and comparative analysis.
• Unique sections and detailed, step-by-step guides for marketers that are not available on other open source tools.

What could be improved:

• The tools were more suited for coders than for marketers.
• Most of them need technical expertise to deploy.
• No follow-up prompts to take the conversation forward.

Pricing: Ollama is free to use.

4. DeepSeek

DeepSeek is one of the strongest competitors to ChatGPT. Despite its criticisms around censorship and data sharing policies, DeepSeek is known for its fast result generation capacity, even for deep thinking.

How I Tested DeepSeek

Using the DeepSeek Chat is extremely easy. I logged in with my Google Account, provided my birth month and date for age verification, and went directly to the chat window.

Once again, I used the same prompt: “Create a blog outline for the ‘top 10 open source AI tools.’ The blog and tools should be relevant for marketers.” This helps me get a comparative understanding of how these open source models think and rate the accuracy of results.

To begin with, DeepSeek thought for just seven seconds, even after I opted for the “DeepThink” option. This is exceptionally fast compared to other AI platforms. I liked the reasoning it provided. DeepSeek said since it’s for marketers, the blog should focus on practical applications rather than technical details.

But I was slightly disappointed to see it still provided some tools that require technical expertise because most marketers may not have those skills. At the same time, it also provided the names of tools that I have used on this blog. So, overall, it provided a mixed result. I did like how DeepSeek shares its thought process briefly before showing the main content.

What I like:

• Very fast result generation (even with the DeepThink feature on).
• Some of the sections are very detailed with pointers on key marketing applications, why it’s good for marketers, and some cons of using them.

What could be improved:

• Despite the reasoning to avoid highly technical tools for marketers, it still included them.
• The outline was not optimized for SEO and left out key sections like “How marketers use AI” that were usually present in other alternatives.

Pricing: DeepSeek’s basic chat is free to use. Paid plans start from $0.07 to $1.10 for 1M tokens.

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5. Google Gemma

I use Google’s closed-source models like Gemini on my phone and laptop for work as well as other purposes like planning a trip. So I was curious to try out Google’s open source model, Gemma, for this article.

Developers typically use Gemma to create AI apps. But Gemma 3’s multi-modal capability and mobile-first architecture also help with faster result generation with low latency. So, it’s equally good for marketers like me who need these AI tools for quick brainstorming or idea generation.

How I Tested Google Gemma

I used Ollama to test Gemma because it seemed the most straightforward one. I downloaded the Gemma 3:1b model, which is just 778MB.

Surprisingly, even the basic model works moderately well. It gives a bulleted list as an overall structure, along with tables listing unique features and a comparison matrix.

What I like:

• Quick result generation. Even the base model gives a decent result that can be used with minimal edits.
• The sections in the outline are well marked and differentiated with word limits and what to include in each.

What could be improved:

• Some of the listed tools are highly technical and not suited for marketers.
• Using Google Gemma within the Ollama framework follows the same structural pattern in creating outlines. Gemma lacked a unique voice while creating the outline.

Pricing: Google Gemma is free to use.

6. GPT4ALL

GPT4All is a private and local AI chatbot like Ollama. You don’t even require the internet to access it after you’ve downloaded it to your desktop or laptop.

One of the things I like about open source platforms is how much importance they give to data privacy. With GPT4ALL, your data doesn’t leave the device and stays local. So you can use it for sensitive or confidential purposes.

It is also compatible with Mac M Series chips, AMD, and NVIDIA, making them accessible to a wide range of users. You can also deploy open-source LLMs through GPT4ALL.

How I Tested GPT4ALL

GPT4ALL takes 1.77 GB of storage, so it took me some time to download it. I checked out their chatbot and selected a Qwen model for the test. You can choose between any leading open source model.

The result was decent. With minor edits, you can use it directly in your workflow. However, GPT4ALL takes some time to generate results. Other alternatives in the space generate results slightly faster. Also, I faced multiple issues during the downloading process and had to close the window multiple times before I could proceed.

What I like:

• Availability of multiple models from the same window.
• Option to directly upload files from your local storage, Google Drive, or Microsoft SharePoint, and generate datasets for your clients.

What could be improved:

• Slightly slower than other open source platforms.
• Slow to download, with multiple hiccups requiring me to abort the process and start afresh.

Pricing: It is free to use. Although most of its features are currently available only for private preview, you need to request access.

7. Cohere

Cohere is ideal for marketers looking to offer enterprise-grade solutions for their clients. I’ve experimented with Cohere to automate workflows and even connect my apps to streamline pending tasks and boost overall work efficiency.

Their Command family of models serves diverse purposes, depending on what a marketer may need. For instance, I’ve used Command A Translate to quickly translate onboarding Docs written in a different language and the Command A Reasoning tool for ideation purposes.

How I Tested Cohere

It is easy to access Cohere. I provided my name and purpose to go to the Cohere Dashboard. From there, I decided to check out Command A, Cohere’s most performant model for enterprise-grade tasks.

From the Cohere Playground, I tested Command A’s skills. I once again gave the same prompt: “Create a blog outline for the ‘top 10 open source AI tools.’ The blog and tools should be relevant for marketers.” Unlike other AI tools, the blog outline was very basic with the ‘command-a-03-2025’ model.

It provided me with a hook and a list of AI tools that were more suitable for coders than for marketers. Each tool was accompanied by a small definition, use case, and why marketers love it, giving me a quick overview.

What I like:

• Result generation was quick, and it provided a clean outline.
• Each section had a compact summary to expand upon.
• Marketers with a technical background (like me) can view the underlying code from the chat window itself.

What could be improved:

• The outline was very basic and could include more details.
• The user interface looks very technical, and it could be changed a bit to appeal more to general marketers.

Pricing: There’s a free trial version. Command A’s paid version starts at $2.50/1M tokens (input) and $10 for every one million tokens (output). Custom pricing is available as well for enterprises.

8. Llama

Meta’s Llama is one of the most famous open-source AI models, and I was curious to try it out. Llama has come a long way since its first open source model, Llama 1. Now with Llama 4, it offers better text and visual intelligence. The response times have also become much faster.

How I Tested Llama

To test Llama, I had to fill out a form and request to test the model. I got a prompt response in my email to download and use it.

With Llama 4, I could test something beyond generating a blog outline. With Llama 4 Scout supporting 10M tokens, it’s one of the longest context lengths available. So, I wanted to see how good it is at memorizing details.

When I fed it a long client Doc and asked it to search for specific data, it did so accurately.

By using Llama 4, I’ve become Meta’s commercial license holder. Which means I can use it to build and deploy apps and use it for commercial purposes within Meta’s stipulated criteria.

What I like:

• Longer context helps with quick document summarization.
• Easy to search relevant items from a long text.

What could be improved:

• The onboarding process is not smooth. You have to fill out your personal details and then download the model from your email.
• There are questions about data privacy, and Meta’s previous history of mishandling user data raises doubts.

Pricing: Llama 4 Maverick costs start from $0.19 for 1M input and output tokens.

9. Rasa

Rasa helps with building trustworthy conversational AI assistants, which are crucial for customer support. I’ve seen how AI assistants can free up time for employees to focus on higher-value tasks while automating routine ones. Good assistants can help with maintaining brand voice consistently while being compliant with company policies.

How I Tested Rasa

I wanted to see how an open-source platform like Rasa builds an AI assistant. So I went ahead with their default prompt about building a trustworthy banking agent.

The agent was quite impressive. I could easily automate bill payment reminders and even customize a single agent that can be personalized for thousands of customers. Definitely a great one to test out if your business is customer-facing.

What I like:

• Offers realistic conversations with customers by following pre-coded logic.
• Functions are enterprise-grade, scalable, and easy to build.

What could be improved:

• There is a long wait time for building the agents due to high demand.
• More pre-set templates would be better for non-technical marketers to get started with.

Pricing: The free tier offers one bot per company with up to 1,000 external conversations per month. Paid versions start at $35K for more than 500,000 conversations. Custom pricing available for enterprises.

10. Stable Diffusion

I often use AI tools to generate images and videos for my blogs, especially if my team’s designer is not available. Stable Diffusion is a decent open-source tool for creating an image quickly.

Their wide variety of pre-designed templates, like design, cinematic, realistic, and animation, helps me choose easily. They also have different aspect ratios, and I could easily select one depending on my requirements.

How I Tested Stable Diffusion

To test Stable Diffusion, I gave a simple prompt: “I am writing a blog for the Top 10 open source AI Tools and Platforms for Marketers. Create a banner that I can use for the blog.”

I chose the “auto” template, 1:1 aspect ratio, and the highest grade of output quality that the free version offers. It required two credits, and the free version gives me 18 credits to use.

While the first image was not in English, the second was. However, the “top 10” was repeated twice, and it was very basic. The free version doesn’t give me an option to edit it. Even the website watermark is present on the image and can only be removed with the paid version.

So I edited the prompt and specifically asked them to create a banner “in the English language.” I also changed the template to “Design” and selected the 16:9 aspect ratio. But the results were still not great. They didn’t use only English in the template, and there were grammatical errors.

What I like:

• Easy to use.
• Helps with basic image generation.

What could be improved:

• It doesn’t follow the prompt accurately. Even after specifying to make a banner in English, it made mistakes.
• The free version has a watermark and no option to edit the generated image.

Pricing: Stable Diffusion offers 18 free credits. Paid plans start at $20/month for Pro and $40 for Max. Annual plans come at a 50% discount.

What I Learned About Open Source AI Platforms

I’ve been using closed-sourced AI like ChatGPT, Gemini, MidJourney, and others for quite some time. So, having a transparent, auditable, and private option was a breath of fresh air.

If I had to pick one favorite open source AI from this list, I really can’t. It has to be a tie between Qwen, DeepSeek, and Mistral AI. And then comes Ollama for its one-in-all solution.

My advice is to use my tests as a reference, select your own open source AI tools, and try them out.

Editor's note: This post was originally published in April 2023 and has been updated for comprehensiveness.

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