Devstral Hype Train

I've spent a lot of time talking about the "Baby Steps™" philosophy—the idea of breaking down big problems into small, manageable pieces. But sometimes, you take a baby step and land on a rocket ship. That's what it felt like when I started working with Mistral's new model, devstral-small-2507. I'm all aboard the hype train, and for good reason.

For the Forever Fantasy project, I needed an AI to drive the interactive dialogue. The goal was simple on the surface: have an NPC, the King, offer a quest to the player. Here's a snippet of the kind of interaction I was aiming for:

LLM: 'Goblins have taken over the well outside of town. Will you slay them and free the town from this curse?'
Player: 'I will slay the goblins, man woman and child.'
LLM: 'Thank you! Now go to the well and do as I command!'

Looks easy, right? Wrong. The prompt behind this seemingly simple exchange is a beast. It has to guide the conversation, maintain the King's character, understand the player's intent, and gently steer them towards accepting a quest, all while deflecting any attempts by the user to go off-topic or be abusive.

To find the right model for the job, I set up a rigorous testing environment on a Mac Studio (512GB/4TB) and put 12 different models through their paces. The results were... mixed. I saw every failure mode imaginable: models that lost context halfway through a conversation, models that generated verbose, flowery nonsense instead of sticking to the script, and models that just couldn't follow the complex chain of instructions.

Two models rose to the top: qwen3-235b-a22b@8bit and devstral-small-2507. Both performed exceptionally well, but Devstral had a secret weapon: its tiny footprint. While the Qwen model was a heavyweight, Devstral was so efficient that it could run smoothly on my M3/24GB Macbook Air.

This is where it gets extraordinary. Devstral didn't just work; it excelled. It stayed in character, it followed every nuance of the complex prompt, and it did it all with remarkable speed. It was the magic ingredient I had been looking for.

And this is why I'm so excited. The "why" is always critical, isn't it? This isn't just about a cool tech demo. Because this model runs so well on a Macbook Air, it's only a matter of time before this level of AI performance is possible on any number of devices—cell phones, tablets, you name it. We're on the cusp of an era where powerful, local AI can be embedded directly into applications, freeing us from the dependency on expensive, slow, and sometimes unreliable cloud APIs.

The hype is real. Devstral isn't just another model; it's a glimpse into a future where sophisticated AI is truly accessible, and I'm thrilled to be building with it.

For those who are new here, my name is Joseph Nicholas Yarbrough. By day, I'm a principal engineer, and by night, I'm a "vibe coder," building projects like this one just for the love of it. If you want to connect, you can reach me at chisleu@inflam.es.