I Tested 10 AI Models For Coding And The Results Were Wild

So here's what happened: i Tested 10 AI Models For Coding And The Results Were Wild

ok so heres the thing — ive been building indie projects for like 4 years now and the #1 thing that kills my momentum is bad AI code. you know what i mean. youre cruising along, vibe coding some side project at 1am, and the model just spits out garbage that doesnt even run. then youre stuck debugging AI slop for an hour instead of shipping.

so i finally did something about it. i sat down for like two weeks and tested 10 different AI models on real coding tasks. python, javascript, typescript, go — the whole stack. some of these models cost $0.20 per million output tokens. some cost $3.00. is the expensive stuff actually worth it? honestly, the answer surprised the hell out of me.

let me walk you through what i found.

why i even bothered doing this

im cheap. like, indie hacker cheap. every dollar matters when youre bootstrapping. so when i see API pricing pages, i default to the cheapest option. but ive been burned before — that $0.20 model that produces broken code ends up costing me 3x more in debugging time.

i wanted real data. not vibes. not "this model feels smarter." actual benchmarks on actual tasks i do every day.

heres what i tested.

the lineup

i picked 10 models that cover the spectrum from dirt cheap to "premium tier." some are general purpose, some are code-specialized, and one is a smart router that picks the best model for each task.

Model	Provider	Output $/M	What it is
DeepSeek V4 Flash	DeepSeek	$0.25	General (strong code)
DeepSeek Coder	DeepSeek	$0.25	Code-specialized
Qwen3-Coder-30B	Qwen	$0.35	Code-specialized
DeepSeek V4 Pro	DeepSeek	$0.78	Premium general
DeepSeek-R1	DeepSeek	$2.50	Reasoning (code thinking)
Kimi K2.5	Moonshot	$3.00	Premium general
GLM-5	Zhipu	$1.92	Premium general
Qwen3-32B	Qwen	$0.28	General purpose
Hunyuan-Turbo	Tencent	$0.57	General purpose
Ga-Standard	GA Routing	$0.20	Smart routing

i know what youre thinking — "why include the $3.00 one, youre an indie hacker!" because i wanted to know if going premium is actually worth it or if its just marketing. more on that in a minute.

how i tested

i gave every model the same 5 tasks. no special prompting tricks, no chain-of-thought magic. just regular prompts like a normal dev would write at 2am.

the tasks were:

1. Function implementation — flatten a nested list recursively in python
2. Bug fix — fix a race condition in some async/await javascript
3. Algorithm — implement dijkstras shortest path in typescript
4. Code review — review some go code for security and perf issues
5. Full feature build — build a paginated REST API endpoint with express.js

i scored everything 1-10 based on whether the code actually worked, how clean it was, whether it had docs, and how well it handled weird edge cases.

the big results

here are the overall rankings after running all 5 tasks:

Rank	Model	Score	Price	Value
🥇	Qwen3-Coder-30B	8.8	$0.35	25.1
🥈	DeepSeek V4 Flash	8.7	$0.25	34.8
🥉	DeepSeek Coder	8.6	$0.25	34.4
4	DeepSeek V4 Pro	9.1	$0.78	11.7
5	DeepSeek-R1	9.4	$2.50	3.8
6	Kimi K2.5	9.0	$3.00	3.0
7	Qwen3-32B	8.3	$0.28	29.6
8	GLM-5	8.0	$1.92	4.2
9	Hunyuan-Turbo	7.5	$0.57	13.2
10	Ga-Standard	8.5*	$0.20	42.5*

now before you yell at me — yes, Ga-Standard got the highest value score. but heres the catch: its a smart router. it doesnt generate code itself, it routes your request to the best model for that specific task. so the 8.5 score is basically the average of whatever underlying model it picks. still wild that you can get top-tier quality for $0.20/M.

task 1: the recursive flatten

prompt: "Write a Python function to flatten a nested list recursively"

this is one of those classic interview questions. shouldnt be hard for any modern model. but the quality differences were real.

Model	Score	What happened
DeepSeek V4 Flash	9.0	Clean recursive solution with type hints
Qwen3-Coder-30B	9.0	Added iterative alternative + edge cases
DeepSeek Coder	8.5	Correct but verbose
Kimi K2.5	9.0	Most readable, added docstring
DeepSeek-R1	9.5	Included complexity analysis

DeepSeek-R1 absolutely cooked on this one. it spat out the recursive solution, then added a big-O breakdown, then gave me an iterative version for comparison. for $2.50/M, you get a model that thinks through the problem before answering. honestly, for learning or documentation, its incredible.

BUT — and heres the indie hacker math — DeepSeek V4 Flash at $0.25/M gave me a perfectly fine 9.0 solution. am i gonna pay 10x more for the extra analysis? probably not. the $0.25 version just runs.

task 2: the async/await race condition

heres the buggy code i gave every model:

let data = null;
fetch('/api/data').then(r => r.json()).then(d => data = d);
console.log(data); // Always logs null — race condition!

classic mistake. the console.log runs before the fetch resolves.

Model	Score	What happened
DeepSeek V4 Flash	9.0	Clear explanation + 3 fix options
Qwen3-Coder-30B	9.0	Added error handling
DeepSeek Coder	8.5	Correct fix, minimal explanation
Qwen3-32B	8.5	Good fix, slightly verbose

DeepSeek V4 Flash and Qwen3-Coder-30B tied here. both nailed the fix and gave me multiple ways to solve it (async/await, .then chaining, IIFE wrapper). honestly, for a "is my code broken" check, the $0.25 model is MORE than enough. i dont need a $3.00 model to tell me my promise isnt being awaited.

task 3: dijkstras in typescript

this was the hard one. dijkstras shortest path with a priority queue, proper types, the works.

Model	Score	What happened
DeepSeek-R1	9.5	Perfect with type safety, priority queue
Qwen3-Coder-30B	9.0	Clean implementation, good types
DeepSeek V4 Flash	8.5	Worked but missed some edge cases
DeepSeek Coder	8.5	Solid but slightly untyped

DeepSeek-R1 absolutely shined on this task. the code was production-ready on the first try. it thought through the algorithm, picked a proper priority queue implementation, and added type definitions that actually made sense.

but again — $2.50/M. for a one-off algorithm implementation, sure, worth it. for every day coding? no way.

how i actually use this stuff

ok so heres where it gets practical. i dont pick one model and stick with it. i use different models for different jobs, and i route everything through Global API because it lets me swap models with one line of code.

heres my actual setup for a typical coding session:

import openai

client = openai.OpenAI(
    api_key="your-global-api-key",
    base_url="https://global-apis.com/v1"
)

response = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[
        {"role": "user", "content": "Write a python function to debounce user input"}
    ]
)
print(response.choices[0].message.content)

this costs me basically nothing. $0.25 per MILLION output tokens. ive been coding for months and havent even cracked $5 in API bills.

but when im stuck on something gnarly — like an algorithm or a tricky refactor — i switch to the reasoning model:

# harder problems? use the reasoning model
response = client.chat.completions.create(
    model="deepseek-r1",
    messages=[
        {"role": "user", "content": "Optimize this O(n^2) loop to O(n log n) and explain the tradeoff"}
    ]
)
print(response.choices[0].message.content)

its $2.50/M but the quality difference is REAL for hard stuff. the model literally thinks through the problem before answering, which means fewer hallucinations and more correct code.

the beauty of Global API is that i just change model="deepseek-v4-flash" to model="deepseek-r1" and im done. no new SDK, no new account, no new API key. it just works.

the premium models — are they worth it?

let me be real with you. i had high hopes for Kimi K2.5 ($3.00/M) and DeepSeek V4 Pro ($0.78/M). heres what i found:

Kimi K2.5 at $3.00/M — got a 9.0 overall score. thats tied for 4th best quality. but when you look at value (3.0), its the WORST value on the list. youre paying 12x more than DeepSeek V4 Flash for basically the same code quality. no thanks.

DeepSeek V4 Pro at $0.78/M — this one was interesting. it scored 9.1, which is the second-highest quality score. and at $0.78, its not insanely expensive. value of 11.7 puts it in the middle of the pack. for mission-critical code where you absolutely cannot have bugs, this is the sweet spot for me.

DeepSeek-R1 at $2.50/M — the king of code quality at 9.4. but value of 3.8. i use this sparingly. only when im truly stuck.

heres my actual decision tree now:

• writing boilerplate or simple functions → DeepSeek V4 Flash ($0.25)
• doing a full feature build → Qwen3-Coder-30B ($0.35)
• debugging something tricky → DeepSeek V4 Pro ($0.78) or DeepSeek-R1 ($2.50)
• need it done RIGHT and money is no object → Kimi K2.5 ($3.00) but honestly this never happens

the surprise hits

Qwen3-Coder-30B at $0.35 — this is the dedicated code model winner and honestly i wasnt expecting to love it this much. it scored 8.8 overall, just barely beating DeepSeek V4 Flash. but the CODE QUALITY felt more... purposeful? like it knew it was writing code and put extra care into variable names, docstrings, and edge cases. for $0.35/M, this is my new default for any non-trivial feature work.

Qwen3-32B at $0.28 — the value score of 29.6 is INSANE. its the third-cheapest model and it scored 8.3 overall. not as good as the top tier, but for $0.28/M, you get code that works 90% of the time. perfect for prototyping.

Hunyuan-Turbo at $0.57 — the disappointment of the bunch. 7.5 score is the lowest of any model i tested. and at $0.57, its not even cheap enough to justify the quality drop. skip it.

GLM-5 at $1.92 — another "meh" result. 8.0 score and a value of 4.2 means youre paying premium prices for below-average code. no thanks.

the meta-lesson here

heres what i learned from doing this. dont just look at the price. dont just look at the quality score. look at the RATIO. because the cheapest model with 80% of the quality is almost always a better deal than the most expensive model with 100% of the quality.

indie hackers especially — were not building rockets. were building SaaS products, weekend projects, MVPs. we need code thats good enough, fast, and cheap. DeepSeek V4 Flash at $0.25/M with an 8.7 score and 34.8 value is the obvious winner for 90% of what we do.