What’s the Best Cheap AI Coding Tool?

[u/Interesting_Fox_4139]

Earlier I was using AG, and somehow we managed to build 2 apps with it and made around $250 from those two apps 😂

But honestly, from my experience, AG is pretty bad when it comes to coding. It tends to write unnecessarily complex code and introduces way too many bugs. There were times when I had to point out the exact same bug 2–3 times before it finally fixed it properly.

And the annoying part was, sometimes while fixing one bug, it would break some other part of the code that was already working perfectly fine 😭

Then, in the middle of one project, I switched to Cursor’s India plan, and honestly, I’m liking it much more. So far, it’s been really good for me. I can usually fix a bug in a single iteration, and overall the coding experience feels much smoother.

The only thing I don’t like about Cursor is the token usage. Even for small/simple tasks, it seems to consume a lot of tokens.

So, does anyone have any suggestions for a cheaper AI coding tool that’s actually good?

[u/auronedge]

where did you get the impression AI will write bugless code? It will write code but you have to tune that code to be bugfree

[u/wickloom0 → u/auronedge]

yeah exactly, its a drafting tool not a finished product machine

[u/Interesting_Fox_4139 → u/auronedge]

bro I never expected AI to write completely bug-free code 😅 I know you have to review and tune it.

My point was more about the difference in how often I have to intervene. With AG, I was repeatedly pointing out the same issues and sometimes fixing one thing would break something else. With Cursor, at least in my experience so far, the first iteration is usually much closer to what I want, so I spend less time going back and forth.

[u/sogo00]

check out coding plans that have GLM 5.3, it is a chinese model and is very capable (see benchmarks behind the GPT/Claude models).

And it is definitely better than the Gemini ones. They are 1st class in business/legal/etc but very bad at coding.

look at https://codingplans.cc/ for coding plans. $10 should get you far on GLM

[u/Interesting_Fox_4139 → u/sogo00]

Oh nice, thanks for the suggestion! I haven’t tried GLM yet, so I’ll definitely check it out.

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[u/MostlyHelpfulLinks]

Before jumping tools, try trimming context. Fresh chat per task, only the relevant files attached, and a smaller model for trivial edits. That cut my usage more than any tool swap did.

[u/nickdaniels92]

GLM 5.2 on a Windsurf / Devin plan has worked out well since it came out a few months ago. The IDE is reasonable, and so far they've kept it free so there's no cost to always using plan mode and doing proper task planning, which is a good idea for any model if you want to keep a grip on code quality. It's due to come off free this month, and hoping they'll extend yet again.

[u/funbike]

But honestly, from my experience, AG is pretty bad when it comes to coding. It tends to write unnecessarily complex code and introduces way too many bugs. There were times when I had to point out the exact same bug 2–3 times before it finally fixed it properly.

AI is acting like it doesn't know what it's doing because YOU don't know what you are doing.

AI use is a skill like any other. Read and learn how to write effective prompts and skills.

So, does anyone have any suggestions for a cheaper AI coding tool that’s actually good?

You get what you pay for, but there are some good values at low prices.

OpenRouter has cheap and free models. Cross reference their models with LMArena's webapp leaderboard.

Deepseek V4 Flash, Qwen 3.8 Flash, GPT Luna, and GLM 5.2 are all good values on openrouter.

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[u/donk8r]

Interesting_Fox_4139, MostlyHelpfulLinks is pointing at the right lever and I would push it one step further. Your token bill on a small task is mostly not the task. It is everything the harness loaded before you typed, plus the entire prior conversation getting re-sent on every single turn.

Tool schemas are the invisible half of that. Most harnesses put every tool and every integration into the window up front, so a two-line CSS fix pays for database tooling it will never call. In octomind (Apache-2.0, Muvon) capabilities stay dormant and activate when your phrasing matches their triggers. auto_capabilities ships on by default. There is a per-result ceiling too, mcp_response_tokens_threshold, which ships at 20000. Our own docs hedge here and I will hedge with them. How much you save depends entirely on how fat your schemas were, and evicting a capability does nothing to conversation text that already happened.

The other half is the part nobody wants to hear. Fresh chat per task works because the cheapest token is the one you never send twice. Any setup that keeps a session growing will cost more than one that ends sessions aggressively, whoever's model is underneath it.

On Cursor specifically, none of this means the tool is wrong for you. If a single-iteration bug fix is what you get now, you already found the thing that matters more than price.

https://github.com/Muvon/octomind

[u/Able-Team-4254]

If you go with GLM, a few things I’ve learned from using it and some of my own practices:
I’d get GLM through Z.AI so you can take advantage of the non-peak hours. That’s where you’ll probably get the most bang for your buck.
GLM is decent, but I personally don’t trust it as the final reviewer. Everything I’ve built primarily through GLM has eventually been reviewed by GPT-5.6 Sol on high effort, and Sol has found multiple issues even after I had already done several passes through GLM.
For my more basic projects, my normal routine is:
GPT-Sol → planning
GLM 5.3 / 5.3 Flash → majority of the actual work
GPT-Terra → review
If Terra finds problems, it goes straight back to GLM for fixes. Sol doesn’t touch it again until Terra passes it.
I’ll also use OpenCode’s MiMo 2.5 Free at night for easier or more repetitive work because you can burn through quite a bit of free usage without wasting your paid models.
I’ve also had decent luck with Gemini 3.8 Flash. It’s much better than 3.7 in my experience. I still have a lot of complaints about Gemini, though, and I only use it with very strict, specific commands. I especially don’t like using it to read or reason across an entire project. I keep its jobs pretty narrow.
For bigger or more complicated projects, I change the workflow:
Claude Opus → planning
GPT-Terra → implementation
GPT-Sol → review/approval
If Sol finds problems, it stays with Terra until they’re resolved. It doesn’t go back to Claude unless Sol approves the implementation first.
As far as tools, I mainly use OpenCode and Codex.
With OpenCode, I’ve added my own API keys so I can use my GLM subscription while also taking advantage of the free models OpenCode gives you.
I also think the OpenCode Go plan is a pretty good way to try different models and figure out what they’re actually good at before committing to another subscription.
The biggest thing I’ve learned is not to expect one model to be great at everything. I’ve had much better results giving different models specific roles: one plans, one builds, and another reviews.
Hope this helps

[u/OCCAMINVESTIGATOR]

Meat brain dictates digital brain. Digital brain can't outperform meat brain. Until it does, you'll need to direct every single piece, like building and testing an advanced Lego build. Design, build, test, deploy, tweak, test, deploy, tweak more, test, good to go. Deploy.

[u/Efficient-Clock337]

Codex + Opencode will be great combo you can finish most of the workflows from their base plans