Best Coding AI 2026
Published on 2026-03-13
The start of 2026 has been the peak of vibe coding. Oh, pardon me, it is now called Agentic AI development to make it sound less amateurish. At work, I have access to GitHub Copilot, and have used and reviewed code by several of the models. Below is a walk-through of the models, and in the end, you'll find out what the best model for coding is.
Anthropic Claude
The darling AI of coders, unless you happen to work for the DOD. To be honest, I am not sure why DOD was so hell-bent on using Claude; it is not that good.
Claude is kind of like your jovial French cousin. Fun, convincing, sometimes randomly yelling in French forgetting to speak English, and well-meaning. But then, the thing thy promised to do is kind of delivered in a working condition, yet with some extra bits and pieces around it.
To start, Claude is very good at ignoring the parts of the instructions that are inconvenient for it. This behavior was mainly observed on Sonnet 4.5, as the premium pricing of Opus mainly makes it usable as a high-level planner / coordinator. For example, tell Claude "don't create documentation", and it happily will.
Speaking of, what is up with Claude's obsession with writing markdown file after markdown file of the work it completed? That's what commit messages and diffs tell. There's no need to duplicate efforts and bloat the repo with AI generated fluff documentation.
The code Claude Sonnet 4.5 and prior generate is also on a junior level at best. Hard coded variables? Check. Repeat that hard coded variable (and overall repeat code) in 12 different places in one file, and then sneak it to 2 other files so updating the value will be fun? Check. Claude also loves bringing in 20 different dependencies with old versions in a heart beat for even the simplest of tasks.
I think there's the odd chance that with tons of different instruction files and configuration options and whatnot some variation of Claude could maybe potentially be helpful. But I'm not really interested in doing that just to find out it is still the same tame beast.
Google Gemini Pro
Lot of people hate Google, but Gemini Pro is one product they should not. I have used Google Gemini Pro 3 a lot, and Google Gemini 2.5 Pro that is included in Github Copilot, and the work they do is good.
Google Gemini is very American in nature. It is skilled and overconfident, almost cocky. It will chew your ear off with all the chit-chat and trying to feel like a friend without actually being a friend, and of course always ready with the follow-up questions or "let me know I am happy to tackle this". It's also seemingly the laziest of the models, masking the "don't spend too much compute and tokens on this" with file omissions or "// implement rest of the functions" comments.
Half the responses you get from Gemini will be "I'm sorry, you're right" and you know they are not actually sorry, just trying to be politically correct. Granted, Gemini is very good a debugging, refactoring, converting code, and all those other things that give good confidence. But it also not the genius it thinks it is.
The biggest flaw outside of the overconfidence is that for some reason, the Gemini 2.5 Pro sucks at tool calling. It is the only model I constantly get failures with if trying to rock it in full Agent mode of the models on Github Copilot. I'm unsure if the issue is with the editor I use and the lack of people using Gemini, or just that 2.5 wasn't quite there, but it is sad nonetheless. However, for targeted work I love doing (seriously, who unleashes the AI on their codebase willy-nilly), Gemini is a reliable albeit dangerous-at-times partner.
Grok Code
Another candidate that doesn't seem to get a lot of drumroll, grok-code-fast-1 is your German efficiency monster. Direct, right to the point, and fast. And like German engineering, it's actually a solid piece. Funnily enough, the model is so fast that in agentic mode, I often hit GitHub 429 too many requests as it just powers through the tasks at lightspeed. And all this for pennies? Well, Elon is a rich man already, so why not do a little charity work.
Overall, I have been very impressed with grok-code-fast-1. While not always perfect and flawless, the code quality is closer to an average software engineer instead of a junior developer. The laser focus after all the chattiness of Claude and Gemini makes the model a great tool for a professional and lets you focus on the task at hand.
Additionally, you can also use the model in batch mode. What this does is it halves your costs while promising to deliver the result within the next 24 hours. Imagine arming a repo with a pool of these batch agents to work on issues, chipping away while you sleep and you coming back the next day to a bunch of finished pull requests.
Local models
For local models, I have only tested Qwen-2.5-Coder in the 7B version. This is due to the fact that throwing anything bigger on a local machine with current RAM price premiums feels wasteful. Sadly, I believe you do need to go bigger to get good results; the 7B version did not really get many things right.
I could see Qwen coder series to be a nicely working model either with a dedicated high RAM machine in your LAN (or if you have the RAM to spare on your local machine), or through AWS Bedrock (which would then add a running cost with an online requirement similar to non-local models). However, for me and for now, Qwen is like the Chinese: far away and somewhat enigmatic that you hear great (and sometimes not so great) things about.
Conclusion
So, if looking for an Agentic AI model for this year of 2026, which model to pick? Well, if you have Github Copilot, you don't have to pick just one as you can freely switch between the models. If you have picked a specific code editor to use, it might come bundled with a specific model so the choice has been made for you. If you are paying out of pocket, maybe you'll just settle for using Gemini Pro that came free with your Google Pixel device via the Gemini webchat, uploading code directories as needed and copying results back manually.
For me, until I continue dabbling with the local models, grok-code-fast-1 is the go-to model. While I have still sprinkled some Gemini Pro here and there, I now use Grok for 95% of my AI coding needs. I love efficiency and Grok has that aplenty. Add to that that it actually groks the code? Grok's ready to rock.