/Tech7h ago

Ghostty creator Mitchell Hashimoto argues local AI needs Claude Opus-tier quality for widespread adoption

Drew Houston says running equivalents costs up to $150,000.

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Original post

Mitchell Hashimoto@mitchellh#1562inTech

We've gone really quickly from "local models are dogshit" to "local models are good actually" (like, a 12 month window from A to B). I don't think they're actually good ENOUGH yet. We need an Opus 4.5 quality local model. When that happens, I think the world will spill over.

Opus 4.5 is/was amazing, and is more than good enough for almost all tasks still as long as you pair with a frontier-level planner/judge.

It'll still require a hugely expensive machine to run it, I'm sure, like a $5K or more laptop or mac studio. But, that's going to be pennies compared to the API costs plus all the benefits of guaranteed privacy and so on.

12:05 PM · Jun 16, 2026 · 89.5K Views

Sentiment

Positive users are excited that local AI models are nearing Opus 4.5 quality with benefits like privacy and speed, while negative users worry about high on-prem costs and insufficient performance for research or coding.

Pos

75.0%

Neg

25.0%

17 comments with sentiment.

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derekmoeller@derekmoeller

@mitchellh I don't think it matters much if they are local or not, versus being open source. Open source models open up commodity marginal cost inference providers, which cuts token costs by 80%.

Running bigger models locally is expensive and won't be economically useful for a while.

7h3.8K704

BOOKMARKS17

Matteo Collina@matteocollina

@mitchellh @anoopcodes Have you tried ds4 with deepseek v4 flash by @antirez? Based on my experience, we are very close if not already there.

I’m using it for 30% of my coding tasks, being mostly limited by speed and HW.

https://github.com/antirez/ds4

6h1.2K3417

RETWEETS1

saint@thetronchguy

@mitchellh >as long as you pair w/ a frontier-level planner/judge

i’m the frontier-level planner-judge lmfao

4h25

Erdal@ErdalToprak

@mitchellh I combine gpt 5.5 with codex 5.3 spark for subagents but recently I added my local Qwen 3.6 27b not only I get more codex usage but I can give all credentials to this local subagent

This article on how to setup subagents is useful

7h1.4K78

Mitchell Hashimoto@mitchellh

@derekmoeller Yeah that’s fair too

7h3.2K21

MACHO Δ@0xTMK

@mitchellh > Kimi K2.7 Code is superb > GLM 5.2 seems to be Opsu 4.6 level and amazing > Qwen 3.7 Pro and Max are fantastic > Deepseek V4 Pro (Max) finds bugs nothing else can

7h590131

Erdal@ErdalToprak

@antonioleivag @mitchellh This doc https://developers.openai.com/codex/config-advanced and a translation layer for responses format between vllm and codex app server

6h2221

Luc@lucrbvi

@mitchellh Did you tried GLM-5.2? It seems really good

7h29721

tmo@tmophoto

@mitchellh Running ai on a laptop is a bad decision. It can be run on an old gaming computer stuffed in a corner of your house that you access the llm with tailscale.

5h9314

Drew Houston@drewhouston

@mitchellh Looking like GLM 5.2 is truly Opus-tier -- to run it fast (>100 tok/sec) you'll need 8x RTX 6000 pros minimum ($125-150k), but achievable now

Mitchell Hashimoto@mitchellh

Opus 4.5 is/was amazing, and is more than good enough for almost all tasks still as long as you pair with a frontier-level planner/judge.

4h68340

Lee Moore@leegmoore

@mitchellh I feel like gemma 4 gets us between sonnet 3.7 and sonnet 4 in terms of raw coding. Still quite a bit from opus 4.5 but at some point I many of us were excited about it

7h1.7K3

Pedro@PedroRevezSilva

I think the quality offered by GPT 5.5 is actually an interesting place. When Fable 5 was available it's probably better at some things but the level of intelligence that you might need for 98% of the tasks is probably that. More intelligence than that is only necessary in very specific niche problems, I would say. Maybe when we have open models that are at the level of 5.5 or Opus 4.8, I would like 5.5 better. It will be fine. I think that will be the turning point.

7h1.1K6

Mitchell Hashimoto@mitchellh

@tmophoto Sure, I mean, wherever as long as its local.

5h7962

Greg Meyer@GMMeyer

@mitchellh you can run high quality local models with 100k in hardware, I have a 5090 and I can't run kimi locally at any reasonable speed.

however, we'll see it happen pretty soon

6h3452

Jesse Ezell@jezell

@mitchellh Maybe when everyone has a $40,000 GPU in their macbook and DRAM is as cheap as water.

7h3432

Anthony Ronning@anthonyronning

@derekmoeller @mitchellh GLM 5.2 is better than Opus 4.5 by benchmarks so we're already there essentially.

7h1152

nocrimez@nocrimez

@mitchellh Whats the closest to Opus 4.5 on ~5K hardware you've seen so far @KyleHessling1 ? 🙏

7h2421

Kyle Hessling@KyleHessling1

Part of me wants to say a REAP prune of Minimax m2.7 on a single NVIDIA GB10 unit (Spark, Gx10); speed is usable this way, but not crazy. The other part of me would say that a single 5090 build with Qwopus 27B v2 or similar is also an excellent bet, just due to the nature of the memory bandwidth, but the PCIe bottleneck kills performance on big MOE's like Minimax.

None of them are fully Opus 4.5 level yet on every front, in my opinion/use cases, even though they benchmark similarly, but they're much closer than I would've ever anticipated at this point in time! They probably match it's capability on 60-70% of common LLM queries.

I speculate small use-case-specific dense models running on a single 5090 with near SOTA performance for that use case, likely coding first, in the very near future.

I hope that helps lol it really depends on what you want to get into, the GB10 units are absurdly complete and efficient out of the box and can run much larger models, but the memory bandwidth of the 5090 is hard to recommend against when these sub-40B dense models are getting so good.

So basically, I don't have a perfect answer; but you can't go wrong buying a 5090 right now if you can get one, and you really can't go wrong buying a GB10! The real answer will come with which one gets a big leap first, ~200B MOE's or sub 40B Dense models. The other nice thing about GB10's is you can cluster 2 and run seriously huge models.

Anyways, I'm rambling now lol

6h542

James Blackwell@jwblackwell

@mitchellh Why run locally? Other than for privacy

Will always be more efficient to run in a proper datacenter on latest hardware

4h392

Scott Jordan@Authentic1ty

@mitchellh Uh, we already have those local models but they don't run on $5k setups.

4h115