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Qwen3-Coder-Next

qwen.ai

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Re: Qwen3-Coder-Next

#391

Post by wincy »

politelemon wrote: post #256
embedding-shape wrote: post #121

Earlier quoted context omitted.

Yeah, Apple hardware don't seem ideal for LLMs that are large, give it a go with a dedicated GPU if you're inclined and you'll see a big difference :)

What are some good GPUs to look for if you're getting started?

If you want to actually run models on a computer at home? The RTX 6000 Blackwell Pro Workstation, hands down. 96GB of VRAM, fits into a standard case (I mean, it’s big, as it’s essentially the same form factor as an RTX 5090 just with a lot denser VRAM).

My RTX 5090 can fit OSS-20B but it’s a bit underwhelming, and for $3000 if I didn’t also use it for gaming I’d have been pretty disappointed.

Re: Qwen3-Coder-Next

#392

Post by [deleted] »

Aurornis wrote: post #323
cubefox wrote: post #260

Earlier quoted context omitted.

> I experimented with the Q2 and Q4 quants. Of course you get degraded performance with this.

Obviously. That's why I led with that statement. Those are the quant thresholds where people with mid-high end hardware can run this locally at reasonable speed, though. In my experience Q2 is flakey, but Q4 isn't dramatically worse.

[deleted]

Re: Qwen3-Coder-Next

#393

Post by selcuka »

jychang wrote: post #377
openclawai wrote: post #332

Earlier quoted context omitted.

For context on what cloud API costs look like when running coding agents: With Claude Sonnet at $3/$15 per 1M tokens, a typical agent loop with ~2K input tokens and ~500 output per call, 5 LLM calls per task, and 20% retry overhead (common with tool use): you're looking at roughly $0.05-0.10 per agent task. At 1K tasks/day that's ~$1.5K-3K/month in API spend. The retry overhead is where the real costs hide. Most cost…

On the other hand, Deepseek V3.2 is $0.38 per million tokens output. And on openrouter, most providers serve it at 20 tokens/sec. At 20t/s over 1 month, that's... $19something running literally 24/7. In reality it'd be cheaper than that. I bet you'd burn more than $20 in electricity with a beefy machine that can run Deepseek. The economics of batch>1 inference does not go in favor of consumers.

> At 20t/s over 1 month, that's... $19something running literally 24/7.

You can run agents in parallel, but yeah, that's a fair comparison.

Re: Qwen3-Coder-Next

#394

Post by mrklol »

kristopolous wrote: post #255
simonw wrote: post #3

This GGUF is 48.4GB - https://huggingface.co/Qwen/Qwen3-Coder-Next-GGUF/tree/main/... - which should be usable on higher end laptops. I still haven't experienced a local model that fits on my 64GB MacBook Pro and can run a coding agent like Codex CLI or Claude code well enough to be useful. Maybe this will be the one? This Unsloth guide from a sibling comment suggests it might be: https://unsloth.ai/docs/models/qwen3…

We need a new word, not "local model" but "my own computers model" CapEx based This distinction is important because some "we support local model" tools have things like ollama orchestration or use the llama.cpp libraries to connect to models on the same physical machine. That's not my definition of local. Mine is "local network". so call it the "LAN model" until we come up with something better. "Self-host" exists b…

I mean if it’s running in your lan, isn’t it local? :D

Re: Qwen3-Coder-Next

#395

Post by mrklol »

Aurornis wrote: post #320
echelon wrote: post #285

Earlier quoted context omitted.

I don't even need "open weights" to run on hardware I own. I am fine renting an H100 (or whatever), as long as I theoretically have access to and own everything running. I do not want my career to become dependent upon Anthropic. Honestly, the best thing for "open" might be for us to build open pipes and services and models where we can rent cloud. Large models will outpace small models: LLMs, video models, "world" m…

> I do not want my career to become dependent upon Anthropic As someone who switches between Anthropic and ChatGPT depending on the month and has dabbled with other providers and some local LLMs, I think this fear is unfounded. It's really easy to switch between models. The different models have some differences that you notice over time but the techniques you learn in one place aren't going to lock you into a provid…

Because they make it easy. Imagine they limit their models to their tooling and suddenly it’s introducing work.

Re: Qwen3-Coder-Next

#396

Post by vessenes »

codazoda wrote: post #319
zackify wrote: post #317

Earlier quoted context omitted.

I'm using this model right now in claude code with LM Studio perfectly, on a macbook pro

You mean Qwen3-Coder-Next? I haven't tried that model itself, yet, because I assume it's too big for me. I have a modest 16GB MacBook Air so I'm restricted to really small stuff. I'm thinking about buying a machine with a GPU to run some of these. Anywayz, maybe I should try some other models. The ones that haven't worked for tool calling, for me are: Llama3.1 Llama3.2 Qwen2.5-coder Qwen3-coder All these in 7b, 8b, o…

I’m mostly out of the local model game, but I can say confidently that Llama will be a waste of time for agentic workflows - it was trained before agentic fine tuning was a thing, as far as I know. It’s going to be tough for tool calling, probably regardless of format you send the request in. Also 8b models are tiny. You could significantly upgrade your inference quality and keep your privacy with say a machine at lambda labs, or some cheaper provider, though. Probably for $1/hr - where an hour is a many times more inference than an hour on your MBA.

Re: Qwen3-Coder-Next

#398

Post by marci »

embedding-shape wrote: post #121
gigatexal wrote: post #29

Earlier quoted context omitted.

I’ve a 128GB m3 max MacBook Pro. Running the gpt oss model on it via lmstudio once the context gets large enough the fans spin to 100 and it’s unbearable.

Yeah, Apple hardware don't seem ideal for LLMs that are large, give it a go with a dedicated GPU if you're inclined and you'll see a big difference :)

Their issue with the mac was the sound of fans spinning. I doubt a dedicated gpu will resolved that.

Re: Qwen3-Coder-Next

#399

Post by falloutx »

CryptoBanker wrote: post #355
falloutx wrote: post #336

Earlier quoted context omitted.

> Anthropic will let you use their API with any coding tools you want No, in 2026, even with their API plan the create key is disabled for most orgs, you basically have to ask your admin to give you a key to use something other than Claude Code. You can imagine how that would be a problem.

That’s not an Anthropic problem, that’s a problem with whomever you work for.

Have talked to engineers in atleast 5 more companies and they have the same issue, apparently its part of the deal Anthropic is giving to companies, and they are happily taking it. I have never seen companies so complaint to a external vendor.

Re: Qwen3-Coder-Next

#400

Post by anhner »

SamDc73 wrote: post #374

This is model 12188, which claims to rival SOTA models while not even being in the same league. In terms of intelligence per compute, it’s probably the best model I can realistically run locally on my laptop for coding. It’s solid for scripting and small projects. I tried it on a mid-size codebase (~50k LOC), and the context window filled up almost immediately, making it basically unusable unless you’re extremely exp…

you should look into using subagents, which each have their own context window and don't pollute the main one
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