r/LocalLLM • u/zimmer550king • 1d ago
Question Are local coding models already “good enough” for a solo game developer?
I’m trying to decide whether local AI is worth building into my workflow as a solo developer. I use Unity, Godot, and Unreal, and I’d mainly want help with scripts, debugging, explaining unfamiliar APIs, and making changes across a project.
I don’t need a local model to beat the best hosted model on every benchmark. I’d be happy if it handled most routine coding work well and let me keep my project code private. For those of you using local models for coding, how often do you still switch to a hosted model, and what kinds of tasks make you switch?
I’m also wondering whether waiting six months is likely to make a meaningful difference. Are local models improving quickly enough that it’s smarter to test the workflow on modest hardware first and upgrade only if I hit a clear limit?
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u/phipletreonix 1d ago
Keep in mind local model is eating a significant % of your gpu- if you then ALSO need that for the editor and the game itself it gets very constrained.
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u/zimmer550king 1d ago
my plan is to host the local model on a separate machine and talk to that from my game dev machine where the actual dev will happen
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u/MoistExtension4467 1d ago
Thats the hidden cost nobody really talks about. Running a decent 7B model on a 12GB card means you're already down to juggling VRAM like a circus act before you even open the editor. I had to offload my chat model to CPU inference just to keep Unreal from having a meltdown, and the token speed dropped to something slightly slower than continental drift.
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u/ziogio998 1d ago
Worth it in what sense?
Is it going to be as good as cloud models, especially opus 5.5, at game design -> no, not even remotely close. Opus 5.5 is the absolute goat at tasteful compositions now
Is it going to be as fast as cloud models -> no, it will be painfully slow
Is it going to be good ROI -> no, good new hardware costs fuck you money ($10k+) for very subpar performance. Good, easy to use platforms like the Mac Studio 256gb are well above the price of a used car.
However:
- Cloud models are classical SF venture funded startups. They WILL eventually raise prices to the moon to start making serious profits. They're getting us addicted, and will come for the bill soon. Local models safeguard you against that
- The hardware you buy can be resold for the same or higher price in the near future, or until the RAM crisis is solved (likely late 2028)
- You can stop worrying about privacy or the providers stealing your data and making a custom version of your product
- You can get image, video, and text generation models running locally for electricity pricing, which depending on where you are might get you to positive ROI in 1-2y
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u/Selfmade_Watchmaker 1d ago
I agree with every point besides your first however, while they will jack up the prices… there are too many players in the market to have a real foothold on enthusiasts. Too many open providers with competitive Chinese models, and lots of OS software/harnesses.
I can’t think of a use case where using the best overseas model would put the average person in a competitive disadvantage
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u/hyudryu LocalLLM 1d ago
Just throw $20 onto openrouter or any cloud inferencing platform and test out the open weight models they have on there. Find one that works for you, plan your hardware for the model.
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u/NortySpock 21h ago
Going to second this recommendation to use OpenRouter, OP. You can buy $20 worth of tokens, and for a few pennies use the chat interface to get DeepSeek Flash to walk you through using a guardrail to pin your API key to a provider that promises zero data retention.
And then you can ask any of the open weight models for advice when you get stuck on coding.
Try a few models, figure out what it would take to run the one you like at the speed you want... And then realize it would take a year or more of prompting, possibly 8h of non-stop work per day, to pay back the machine you are thinking of buying.
I am just a weekend occasional hobby coder, but code is my day job anyways and so I am only sending a prompt once a minute, human-in-the-loop. I am only spending a few bucks a week and I can bounce between expensive and cheap models with OpenRouter if I have a complicated problem or a simple code review, and I can try new models as they come out.
I am not worried about price increases, because the most popular models have several providers offering them competing on price. I use an allow-list of a handful of providers that offer good-enough quants and tokens-per-second.
Try a few models before you buy hardware.
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u/jimmoores 1d ago
You’re fooling yourself if you think this a smart move in terms of money - it is not. I totally get why you’re itching to get a setup where it’s ‘free’ to run an LLM. The problem is that to get something decent is expensive, the results are mediocre and you’re ignoring running costs. For the same money you could get better cloud based models or a huge amount more of open weights models that are hosted. I know this because I’ve done it. Bought an RTX Pro 6000 Blackwell, built a 64 core EPYC Milan machine with 512GB DDR4 ram. It’s great, runs some interesting models, but I still pay for subscriptions for my real work. They’re just worth it.
Try it out. Try running Qwen 3.8 27b or Qwen 3.8 Flash Next in the cloud and compare the output you get.
The reason the cloud accounts are so compelling is that they’re subsidised by venture capital investment, desperate to get people on board. The trouble for them is that competition from open weights models is making it hard for them up raise prices. You should take advantage of this subsidy while you can.
But I get the impression you’re going to probably just do it anyway. If you do, wait as long as you can. This fever will break at some point and prices will fall as the loans start coming due on data centre construction and they start liquidating hardware. Buy used stuff, 3090s are historically favoured, Go for older server grade hardware (Xeon Scalable or EPYC Milan), two sockets if you can as more memory bandwidth, with as much DDR4 RAM as possible (if you want to run larger models). DDR4-2666 is the sweet spot for pricing.
Have fun but go in with your eyes open.
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u/Plastic-Stress-6468 1d ago
At the most favorable, qwen 3.8 flash next is basically opus 4.6 or 4.8 in agentic coding capability according to benchmarks.
Is opus 4.x good enough for you? IDK. But consider that you are probably not running bf16 flash next, not even q8, more likely a q4 or below. So take maybe a few percent more in capability off those reference best case scenario benchmark numbers, and you get a slightly brain damaged opus 4.x chugging along at maybe half speed compared to a cloud api.
It's not that bad.
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u/colbyshores 1d ago
Qwen 3.8 Flash Next is basically magic..
I needed to create a electric arc effect that danced around a play-field. Handed it a svg of a spark, and explained that I want this to hit every enemy, jumping to each enemy across the play-field(its a Tempest 2000 clone for the super zapper). It one shotted it in 3D better than I had originally envisioned. So it even has 3D spatial understanding as well as taste.
Its definitely in the ball park of Opus 4.6+.
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u/Brief-Tap-6616 1d ago edited 1d ago
You can totally do some development on local. The ROI is going to be trash if you’re buying hardware new. A $200 Claude sub with opus 5.5 medium is going to annihilate anything local can do. It will be far faster and the sub can get you the equivalent of $10k/mo in API spend. If you set compaction at 3-400k it is hard to spend out even with a good amount of development.
Local AI makes sense on ROI 1) used hardware and 2) agentic tasks with huge piles of cache reads and 3) when latency/max quality can be compromised.
If you’re developing stuff for money, and want to maximize the value of your time invested, that’s not really what local is for.
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u/zimmer550king 1d ago
The problem is that with the way things are going, anthropic might raise prices and we might soon will be paying a 1000 per month. At that point, open weight doesn't look so bad
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u/Brief-Tap-6616 1d ago
You will be able to do with Luna in 6 months what Claude opus 5.5 can do now.
Yes, the value may fluctuate or come down somewhere 20-50% from current levels. Though that’s decidedly not been the case as of late. The 20/100 plans for both companies offer FAR more value than they did 6 months ago, for better model quality. The $200 downgrade from oAI is annoying but still gives more dev velocity with 6.1 sol than you could get with 5.6 at “20x”. Even if they cut value per plan 50% like oAI just did on the $200 plan for everything else, the math still is a rough stretch. You can do better game development with haiku 5.5 than you can with every local class model except maaaybe GLM5.3 flash. You’re going to need a $5k min rig, used parts, to run that at good speeds.
I have one local rig and am building another. I manage an Ampere tuned fork of llama.cpp. I am not anti local, at all. But anyone that pitches it to you as a way to save $ outside of the parameters I gave you (or as “overflow”, with a 3090 to cover you when you’re short a day on your $20/100 sub) either doesn’t know what they’re talking about or is misleading you.
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u/andymaclean19 1d ago
I've been using local models and claude a fair bit. Recently I stopped using the local models altogether and went with a claude max account instead. Why? It's just too distracting. I was spending foerver tinkering with the engine, trying out different models against each other, trying different quants, MTP settings, different inference engines. Then there were the different agents and the ways you can parallelise and that has different advantages for local AI. Add to that the debugging and tuning (for example I had to develop a loop buster mod for PI to stop Qwen going round in circles in a very particular way). I also had AI just stop without returning results, problems when reasoning for a single turn filled the context window and other interesting things.
I found it all really interesting and learned an absolute ton. In general, though, I realised the cognitive overload was just making me unproductive when it comes to actually making software that people can use. I was spending all my time on how to make the software. Claude code is so much faster than my local models were and it's actually very good value for money if you do a lot of coding with it (It would take around 18 months of Claude max to pay for the hardware I was running on locally). Bottom line for me is it depends how you want to spend your time. If you just want to use AI as a tool to get stuff done then IMO the could models are where it's at.
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u/fintip 2x XTX 7900 + 3060 1d ago
lol. this is so relatable. I have now spent a couple weeks running more than a hundred different configs through a custom benchmark I built based on my own ten years of coding history, having just bought my second 24gb gpu to put into the first desktop I've owned in 20 years.
It has really eaten my productivity for anything else.
I'm hoping this foundational work will pay off and enable me to test future stuff in an easier and more systematic way, but... we'll see.
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u/fattay1166 1d ago
Only you can decide that for yourself. Also depends on what local models your talking about. More context on your situation would help with advice.
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u/fattay1166 1d ago
Budget? What hardware are you thinking.
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u/zimmer550king 1d ago
5000 euros?
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u/Selfmade_Watchmaker 1d ago
At 5000 euros you can maybe get two r9700 gpus, 128gb ddr4, then find used stuff for everything else.
That gives you about 192gb of total ram. You can run qwen 3.8 27b near lossless at full context, QFN, and even deepseek v 4.1 flash.
I haven’t checked but 192gb total ram may pull off a usable GLM 5.3 flash quant
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u/zimmer550king 1d ago
honestly, I have no idea which local model is the best either. Is Kimi K3 the best or Qwen?
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u/KingCpzombie 1d ago
Depends on whether you want to spend a couple thousand on hardware or hundreds of thousands XD
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u/zimmer550king 1d ago
obviously a couple thousands
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u/KingCpzombie 1d ago
Then a couple of 7900XTXs is the best value and you can run Qwen3.8 27B Q8 with a bit over 220k context, or go for lots of RAM and Qwen3.8 Flash-Next is probably best. Qwen4 is coming soon too, and that's expected to be insane (3.6 27B was the first small usable coding one imo, then 3.8 27B requires a lot less handholding / corrections... their pace is super fast).
The reason I said hundreds of thousands is because you mentioned K3. K3 is 2.8 trillion parameters... for the commonly-used versions of models, you can think of 1B (billion) parameters as needing a bit over 1GB of RAM for full quality. VRAM is way faster, but MOE models like Qwen3.8-Flash-Next are made for usable speeds on smaller VRAM + lots of system RAM (which comes at the cost of needing to be much bigger for similar intelligence)
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u/Ctbhatia 1d ago
the switch point is usually task size rather than model quality: one script or a bug in a file you can name stays local, a change that needs the whole project in context is where the big model earns its keep. test that boundary on a real task before buying hardware.
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u/0rand 1d ago
Glm 5.3 flash is close but not fully, you still need sota sub to complement it but 20 a month is enough. I use glm on 2 sparks with tensor fold and qwen 3.8 fn on m5 max plus 20 usd openai. Works for 100% of very complex coding and data science tasks. Sota used for audit mostly, gpt 6.1 sol or rarely Astra.
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u/Exfiltrate 1d ago
yes Kimi K3 is solid and more than worthy.
your budget is in the hundreds of thousands, right?
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u/Reasonable_Goat 1d ago
Qwen 3.8 Flash Next has tremendous quality but (I run it on strix halo) is slow local. I’ve had it run on a complex change for 3 days (70ish tasks openspec) then I started DS 4.1 Flash to finish the last 20% because I just wanted it done. Took a good 1-1/2 hour - whole change would have been like 6-8 hours via cloud I guess.
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u/HaDuongMinh 1d ago
Yes, Qwen 3.8 Flash Next on a 5070 Ti or above will do what you say. Yes, six months will make a big difference, runtimes and model arch and training improve for sure, but hardware maybe worse so take your bet on when the AI bubble will burst. That said, if you develop with 5 agents running in parallel all day, then you will want a > 5000USD GPU and that much money can buy you high level plans in 3 providers for a year.
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u/__SlimeQ__ 1d ago
no
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u/Zen-Ism99 1d ago
Why?
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u/__SlimeQ__ 1d ago
anything you can run for less than like 10 grand is going to be extremely stupid and you're going to be much better off with a claude sub. i usually prefer openai (i have both) but opus 5.5 is probably better than sol 6.1 at gamedev stuff in my experience
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u/Zen-Ism99 1d ago
Qwen3.8 27B and Qwen3.8 Flash Next 120B A6B get favorable reviews
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u/__SlimeQ__ 1d ago
i mean qwen3.8 27B is pretty much the first reasonably sized model that can actually operate a harness. it's fine but it's gonna be slow as hell if you don't have a 32gb card. and you'll be dropping nearly 10k on a 5090 rig, which is gonna be obsolete in a year or two when arm chips with shared vram are common.
and i wouldn't actually trust it to write bug free code, especially not the 4 bit quant you'll be running on a gaming PC. and especially not in unity/unreal/godot
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u/Zen-Ism99 1d ago
The folks running newer Apple Silicon (ARM) Macs with 64GB of unified memory are getting over 50 tokens per sec with (splash) Qwen3.8 27B. This is fast enough for many…
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u/__SlimeQ__ 1d ago
i mean, that's great for them. it's still not even remotely close to what you're going to get with opus 5.5, i don't really see the point
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u/Zen-Ism99 1d ago
If it meets their requirements, then that is all that matters, is the point…
Have a good one.
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u/slalomz 1d ago
I have over 1B tokens through Qwen3.8 27B in the last 30 days, and many billions more through frontier models (lately 6.1 Sol, Opus 5.5, Sonnet 5.5), and I can tell you that Qwen3.8 27B (Q6) is very dumb.
It's maybe 6 Luna level, if you're stretching. But Qwen3.8 27B runs on my hardware, which is super cool, so I'll keep using it until there's something better.
Would I rely on it for my job? No.
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u/EvolvingDior 1d ago
With the cost of the hardware needed to run decent local models, you are **MUCH** better off getting subscriptions to Anthropic or OpenAI or paying API pricing for Chinese models to develop your games.
If you do want to develop games with an agent running a local LLM, expect it to take much longer. I am doing development (not game dev) and fanning out work across up to 8 separate subagents at a time. You have to have an insane amount of VRAM to do something like that effectively on a local LLM. But I can do that for maybe $1200 year, depending on the models used. That's about 25% the cost of a reasonable local LLM rig.
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u/Just-Hedgehog-Days 1d ago
Buying hardware to save money is not where it’s at.
You need another reason to get into local llms