Mistral vs Copilot: Which AI coding assistant is best in 2025?

Not too long ago, AI coding assistants felt like a cool party trick. Now, they’re pretty much standard issue in a developer’s toolkit. If you’re in the market for one, you’ve probably heard two names buzzing around: GitHub Copilot, the big player from Microsoft, and Mistral AI, the impressive newcomer known for its powerful, open-source models.

Trying to decide between them can feel a bit overwhelming. That’s why we’re here. This guide is a no-fluff comparison of Mistral vs Copilot. We’ll get into their features, performance, how they slot into your daily workflow, and the all-important price tag. By the end, you should have a much clearer picture of which AI sidekick is the right choice for your team.

Understanding AI coding assistants

Let’s get one thing straight: AI coding assistants, or "AI pair programmers," are so much more than a supercharged autocomplete. Think of them as a partner that plugs right into your code editor. They’ll suggest anything from a single line of code to entire functions, often just by reading your plain-English comments and understanding the context of what you’re building.

The main goal here is to get you coding faster. They handle the tedious, boilerplate stuff that can really break your concentration, letting you stay in the zone and focus on the tricky logic. Plus, they’re surprisingly good at helping you debug, write unit tests, or even learn the ropes of a new language or framework you’ve been meaning to pick up.

So what’s the magic behind it? It’s all powered by large language models (LLMs) that have been trained on a massive amount of public code from repositories like GitHub. All that training means they’ve learned the patterns, syntax, and quirks of dozens of programming languages. That’s what makes them such a flexible partner, no matter what you’re working on.

A detailed look at GitHub Copilot

As the tool that really brought AI coding assistants into the mainstream, GitHub Copilot has set a high bar. It’s backed by OpenAI’s powerful models and woven directly into the Microsoft and GitHub ecosystem, which has made it the default choice for millions of developers.

Copilot’s key features and strengths

• Plays nice with your existing tools: Copilot’s biggest selling point is how seamlessly it fits into a developer’s life. It feels right at home in Visual Studio Code and other popular editors like the JetBrains suite. This isn’t just about code suggestions; it means you can chat with it, have it review pull requests, and get suggestions without ever leaving your editor. It’s incredibly smooth.

• Goes beyond simple code completion: Copilot has evolved a lot. It now has an "agent mode" that can try to tackle an entire GitHub issue on its own. Features like "Copilot Spaces" let it learn the specifics of your team’s projects, and it can even predict how a change in one file might require edits in another. It’s actively trying to think a few steps ahead for you.

• You’re not stuck with one model: One of the cooler recent updates is that you can switch between different AI models. If you need raw power for a complex problem, you might pick a GPT model. If you need a quick suggestion, you could switch to something faster. This flexibility lets you pick the right tool for the job.

Copilot limitations to consider

• It’s a black box: Copilot is a closed-source, proprietary product. This means you have zero control over the underlying AI models. You can’t tweak them, and you definitely can’t host them on your own servers. For companies with very strict rules about data security or where data is stored, this can be a non-starter.

• Your code leaves your machine: GitHub has privacy policies for its business clients, but the fact remains that your code snippets and prompts are sent to external servers for processing. Even if the risk is small, it’s a risk some organizations simply aren’t comfortable with.

GitHub Copilot pricing

Copilot’s pricing is easy to understand, which is a big plus. It’s all based on a monthly subscription.

• Free: A decent trial run that gives you 50 agent/chat requests and 2,000 code completions a month.

• Pro: For $10 a month (or $100/year), you get unlimited completions and chats, plus access to the more capable AI models and the full agent feature. It’s also free for verified students and people who maintain popular open-source projects.

• Pro+: At $39 per month (or $390/year), you get everything in the Pro plan, but with access to all available models and a higher limit for the premium features.

• Business & Enterprise: If you’re outfitting a larger team, they offer custom plans that include things like centralized license management and extra legal protections.

A detailed look at Mistral AI

Mistral AI showed up and quickly earned a reputation for building incredibly powerful and efficient language models. They have a strong open-source ethos, and Codestral is their first model built specifically for developers.

Mistral AI’s key features and strengths

• It’s seriously fast: Codestral was built for speed. It spits out code suggestions almost instantly, with very low latency. This makes the whole experience feel fluid and responsive, like the AI is keeping up with your train of thought. It also supports a huge list of over 80 programming languages, from the usual suspects like Python and JavaScript to more specialized ones like Julia.

• It just ‘gets’ complex code: A common piece of feedback from developers is that Mistral’s models, including Codestral, often seem to have a better grasp of tricky logic. They appear to be better at tracking context across multiple files, which is a massive help when you’re working on a large, complicated project.

• You’re in the driver’s seat: This is where Mistral really shines. Because they release models with open weights, you have the freedom to fine-tune them on your own private codebases. You can also deploy these models wherever you want, including on your own on-premise servers. This gives you total control over your data and how the model performs.

Mistral AI limitations to consider

• The ecosystem is still growing: Being the newer kid on the block, Mistral doesn’t have the same polished, built-in integrations as Copilot. To get it working in your editor, you’ll likely need to use a third-party extension or work directly with its API. It’s not a huge hurdle, but it does require a bit more setup.

• The pricing can be a moving target: Mistral’s pay-as-you-go model is super flexible, but it’s not as predictable as Copilot’s flat monthly fee. If your team has a heavy month of coding, your bill could be higher than you anticipated, which can make budgeting a little trickier.

Mistral AI pricing

Mistral’s pricing is mostly usage-based, calculated in "tokens" (which are basically pieces of words). They do have a subscription for their web chat, but most teams using Codestral will be paying for API access.

• Le Chat Pro: For $20/month, you can use all of Mistral’s models, Codestral included, through a simple web chat.

• API Pricing (Pay-as-you-go):

  • Codestral: $1 per 1 million input tokens / $1 per 1 million output tokens.

  • Mistral Large 2: $3 per 1 million input tokens / $9 per 1 million output tokens.

• Enterprise Solutions: They also offer custom plans for companies that need to deploy at a large scale or want help with fine-tuning a custom model.

Mistral vs Copilot: A head-to-head comparison

So, after all that, which one should you pick? It honestly comes down to what your team values most. One gives you a slick, all-in-one package, while the other offers raw power and complete control.

Mistral vs Copilot: Feature and philosophy breakdown

Here’s a quick table to break down how they stack up on the things that matter most.

Feature	GitHub Copilot	Mistral AI (Codestral)	The Verdict
Ecosystem & Integration			Copilot is the hands-down winner here. Its plug-and-play experience in the GitHub and VS Code world is just unbeatable right now.
Performance & Speed			Mistral gets the nod for its incredible speed. The low latency makes coding feel much more natural and interactive.
Customization & Control			If you want to fine-tune a model on your own code or need to run it on your own servers, Mistral is your only real choice.
Code Quality & Reasoning			Both are excellent, but you’ll hear many developers say Mistral has a slight edge when it comes to understanding complex logic across a whole project.
Pricing Model	(Predictability)	(Flexibility)	Copilot makes budgeting easy with its flat-rate plans. Mistral is more flexible with its pay-as-you-go model, but you’ll have a harder time forecasting costs.

This video explores how open-source alternatives, including those using Mistral, are challenging GitHub Copilot with new extensions and capabilities.

Beyond Mistral vs Copilot: AI assistants are not just for developers

Now, while your devs are getting a major productivity boost, what about the rest of your company? Handing a developer-focused tool to your customer support team is like giving a master chef a socket wrench, it’s the wrong tool for the job. It just doesn’t have the right context or integrations.

Your support team needs an AI that’s an expert on your business. Instead of learning from public code, it should be learning from your past support tickets, your help center articles, and all your internal documents. This is where a specialized tool comes in. For example, eesel AI connects directly to help desks like Zendesk or Freshdesk and pulls together all your company knowledge in minutes. It offers the kind of deep control Mistral users appreciate but with the simple setup that makes Copilot so popular, all designed for the unique world of customer support.

An AI Copilot integrated directly into Zendesk, providing support agents with instant, context-aware answers from company knowledge sources.

Mistral vs Copilot: Choosing the right AI assistant

The Mistral vs Copilot debate doesn’t really have one correct answer. It all depends on your team’s specific needs and priorities.

• Choose GitHub Copilot if: Your team is already heavily invested in the GitHub ecosystem and you want a tool that "just works" out of the box with a predictable monthly bill.

• Choose Mistral AI if: You’re chasing peak performance, need the control to fine-tune your own models, or have strict data security requirements that demand an on-premise solution.

At the end of the day, the best AI tool is one that’s built for the task at hand. While your developers are leveling up their workflow with a coding assistant, you can give your support team that same kind of advantage with an AI designed just for them.

See how eesel AI can help automate your frontline support, draft replies that sound just like your brand, and connect to all your knowledge sources with just a few clicks.