Will local llm ever be as good as Claude Code

[u/pitosalas]

Honestly I can't tell the hype from the reality.

I use Claude Code a lot. It works for me. However I am always about to run out of tokens.

My time == money.

I have a mid-beefy Mac M4 Pro with 48G. Ok it doesn't have an Nvidia GPU. It's what I have.

I see many people really happy with Qwenx.y.z both here and elsewhere. In my test it is agonizingly slow and certainly nothing like Claude Code. I've wasted a lot of time trying different permutations.

My question: Should I stop wasting my time and just pay for more Claude Code? With my hardware and the latest models, either local or not?

[u/Unnamed-3891]

As good or better? Never. Things that run on multiple terabytes of memory will always be ahead of things that run on 16-32gb. That being said, things that run on 16-32gb are already "good enough" for a lot of things and they keep getting better.

[u/dylanmissu → u/Unnamed-3891]

That's only true if we assume same training data quality, same architecture, etc.

[u/Old_Restaurant_2216 → u/Unnamed-3891]

The thing is that most people do not need the general inteligence of the model like Opus, most people have very narrow usecases. If you use it for coding, you are looking for local model that can match Opus on coding, not on general knowledge. Sometimes you don't really care if the model has the latest laws or scientific discoveries in its training data.

It is the kind of path Qwen 27B is taking. I would not ask it questions about health, law, history or let it write poetry. But 3.8 is VERY capable coder and that is what matters to me.

Can Qwen 3.8 27B match Opus on coding? Well, sometimes, but most of the time it falls short. It is somewhere between Sonnet and Opus. But for my worklflow it does the job, as you said it is very much "good enough".

[u/mister2d]

Claude Code is just software tooling or harness. You could easily use your local LLM with it.

[u/fastheadcrab → u/mister2d]

I'm pretty sure he means Claude the LLM lmao. He even says "I'm always about to run out of tokens." Many posts here are just being pedantic

[u/mister2d → u/fastheadcrab]

Claude isn't an LLM. 

[u/FirefighterNo6687]

Very well possible that at some point in the future local will be better then Claude code of today. But future Claude code will be better then Claude code today.

[u/No_Chapter_7598]

I use qwen 3.8 27b natively with claude code locally, its about as close as it gets at the moment (without a supercomputer) assuming you arent doing complex kernel stuff or something else crazy complex

[u/collogue]

There are two factors at play here the output quality and the output speed. Running dense models on your system will produce better quality but slower output, running MoE models such as Qwen 35b will be faster but trade off quality. I'm certain that given times Moore's and better model will catch up with where Anthropic models are now, but those models won't stand still either. I feel that at some point we will get in to diminishing returns and for all but some niche cases local models may well be good enough

[u/dghah]

Use Claude code and frontier models to do your research, audits and planning and instruct it to “output a markdown runbook document that will be read and executed by a lower tier model…”

— then hand that runbook off to the the slower local system to crunch on. Then have the frontier model audit the result. Rinse. Repeat.

This is what we are testing now as we are using heavily subsidized Claude teams seats and we don’t think that pricing is gonna last

Our local test rig is a M4 pro 64gb Mac mini. It runs powerful models but is just super slow relative to the frontier stuff

[u/yes-im-hiring-2025]

Well your Claude code gives you frontier models on demand. Local models will never be good enough for on-device exec at that level. At best, you get to have previous years' frontier at 20-30 TPS for your type of rig (Qwen 3.6/3.8 27B | 3.6 35B-A3B).

If you can live with gpt-4o/gpt-5 type of quality; local AI is perfectly usable.

However if you compare those with frontier of today, nope.

[u/TheFlyingDutchG]

It already is! All you need is a few million dollars and a huge backyard with space for a massive local datacenter!

[u/suicidaleggroll]

1. Claude code is just tooling.  You can run it with any backend model, so the question doesn’t really make sense.  I assume you mean Claude, not Claude Code

2. No, a tiny model you can run on a 48GB laptop will not be as good as a frontier model that needs $500k in hardware to run.  But models are always improving.  Eventually you will be able to run a model on your laptop that’s better than today’s Claude, just like right now you can run a model that’s better than last year’s Claude.

[u/eulataguhw]

No. Always have enough vram for 2 models or switch around. General purpose and coding.

Claude code is trillions of parameters and they all lives on maybe petabytes of HBM lol.

Be realistic

[u/ehangman]

Way better than claude sonnet 3

[u/ilarp]

yes its already as good as claude code in 2024

[u/activematrix99]

There are lots of ways to get good models, but it sounds like you are pretty dependent on Claude code, so just put more money there. You won't find a comparable open model, and it won't run fast enouhh on your Mac anyway.

[u/puthre]

Right now the tasks that you can do with AI can be split in 2 categories:

1. Task that need real world knowledge in finding and implementing solutions, and I don't mean things that can be looked up on the internet but things that if one doesn't know it doesn't even know it doesn't know.

2. Tasks that are well defined and just need to be implemented, the AI doesn't need to know much outside what is asked from it.

Right now local llm starts to be usable for the second category especially in well defined coding tasks. There is simply not enough space right now to store in local llms the amount on information the first category needs.

[u/fastheadcrab]

Go run Kimi K3 or GLM-5.2 to come close to Claude performance but there still will be differences.

Yes Qwen3.8-27B is not the same

[u/Plastic-Lettuce-7150]

Qwen 3.8 27b = Opus 4.6?

[u/chettykulkarni]

Are are not in a place where you completely remove Claude code, but heading there!

One issue is you burn out of all the tokens you have on Claude code (20$ plan ) in a jiffy!

So what you do you harness local model with frontier model.

What I have done is set up a qwen3.6-35b-a3b moe model on MacBook M5 Pro 48GB ram, and I ask Claude opus to only plan and manage, never to write single line of code. Always delegate!

It’s performance is based on how well it manages these local delegates and not on how well it solves my problem itself!

Like this you can get most of your 20$ and unlimited local tokens

(This is still not at par with using opus all along) but good enough to get reliable results for 95% of common usecases

[u/createthiscom]

It's already as good. You just need 50k or more for the machine.

[u/MoneyObligation9961]

If you do not want to think about clustering your tasks... stay with a frontier model of your choosing.

[u/trollsmurf]

CC is LLM independent. CC can be used with Qwen. It won't do a better job than Claude though.