Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Qwen 3.8

twitter.com

Post reply on HN
Print view View original

201–210 of 793 posts

Re: Qwen 3.8

#201

Post by exceptione »

chewz wrote: post #111
5701652400 wrote: post #99

in my experience of 1 month daily use, Qwen 3.7 Pro is just unusable. wastes too much time, goes off track, useless stuck loops, cannot debug at all. Deepseek V4 Pro is night-and-day compare to Qwen. actually Qwen models seems the worst SWE experience so far. and it is super expensive compare to Deepseek. cannot delegate anything to it, cannot use it real-time low-level tasks either. totally unusable.

From my experience Qwen-3.7-Max is above the Opus level but delivers results much faster. Slightly worse then Fable. Way ahead of Deepseek 4 Pro (in speed and overall comprehension) - which is a workhorse on its own. I am using them all with Claude Code mostly. Qwen-3.7-Plus is quite OK, good for subagent use. Way better then Sonnet. Qwen-3.8-Max-Preview seems working just fine for me at the moment - I am playing wit…

  > At 10% of regular price it is a steal so far.
What price do you see?

Here standard plan has been discounted to $18.00, from $25.00/month.

Re: Qwen 3.8

#202

Post by gigatexal »

chewz wrote: post #111
5701652400 wrote: post #99

in my experience of 1 month daily use, Qwen 3.7 Pro is just unusable. wastes too much time, goes off track, useless stuck loops, cannot debug at all. Deepseek V4 Pro is night-and-day compare to Qwen. actually Qwen models seems the worst SWE experience so far. and it is super expensive compare to Deepseek. cannot delegate anything to it, cannot use it real-time low-level tasks either. totally unusable.

From my experience Qwen-3.7-Max is above the Opus level but delivers results much faster. Slightly worse then Fable. Way ahead of Deepseek 4 Pro (in speed and overall comprehension) - which is a workhorse on its own. I am using them all with Claude Code mostly. Qwen-3.7-Plus is quite OK, good for subagent use. Way better then Sonnet. Qwen-3.8-Max-Preview seems working just fine for me at the moment - I am playing wit…

What the difference between your experience and https://news.ycombinator.com/user?id=5701652400? ‘s?

Such diametrically different ones.

Re: Qwen 3.8

#203

Post by dofm »

ernsheong wrote: post #106

So are locally-runnable models frozen at Qwen 3.6 now :/

Maybe, maybe not. Qwen 3.6 27B is literally just three months old. Hard to predict. Maybe it just wasn't worth making a 3.7, and after all, the 27B release was after the Plus release.

Re: Qwen 3.8

#205

Post by gigatexal »

mattmanser wrote: post #175
chewz wrote: post #122

Earlier quoted context omitted.

> If by Opus you mean Opus 4 and not Opus 4.8, then sure I meant Opus 4.8 which is rather dumb and ineffective in coding harness, especially with higher thinking levels.

Comments like this boggle my mind. The model which everyone else raves about and is wildly successful with legions of programmers virtually demanding access while abandoning ChatGPT and Copilot in droves, is rather dumb? Have you considered that it's more likely that you're doing something wrong?

Exactly what I’m thinking, too.

Re: Qwen 3.8

#206

Post by dofm »

regularfry wrote: post #193
ch_sm wrote: post #123

Earlier quoted context omitted.

In my experience, yes. A bit more reliable than gemma for me. I mostly use A3B (35B, mix of experts) though, because it‘s faster, and in the same ballpark intelligence wise as the dense 27B, so it’s the sweetspot for me. I want to try cohere‘s mini code model next, but worried the runtimes aren‘t optimized for that yet.

Worth knowing that Unsloth have just put out another Gemma 4 release from Google's upstream updates which should improve reliability. Bugs in the chat template affecting tool calling and other issues, apparently. https://www.reddit.com/r/unsloth/s/MpC6Hzs4Wj

Wow, thanks. I didn't see Unsloth had already done their version; I was just about to go back to the google version to test this change.

Re: Qwen 3.8

#207

Post by akazantsev »

zer0gravity wrote: post #93
nsbk wrote: post #19

Bring it on! Hoping that they release smaller sizes of Qwen3.8. I use the 35B MoE and 27B dense models locally and most of the time I don’t need to reach out to Claude. Extremely useful specially when requests include sensitive and/or personal data

This seems more of a battle for frontier AI supremacy. I'm afraid that small capable models have been left in the dust. Big labs don't really want to hand over the golden eggs goose to the end user. Possibly the hardware vendors(e.g. Nvidia) may want to play in that area as well, to pull money from all parties.

Google makes Gemma 4 31B QAT; that's not a small lab. It's one of the better models out there for consumer hardware. Allows me to run it on a 7900XTX with 64k context.

Re: Qwen 3.8

#208

Post by VladVladikoff »

porksoda wrote: post #164
chewz wrote: post #122

Earlier quoted context omitted.

> If by Opus you mean Opus 4 and not Opus 4.8, then sure I meant Opus 4.8 which is rather dumb and ineffective in coding harness, especially with higher thinking levels.

My experience was so much different to this, that I have the unfortunate impression that you're shilling. It really was not a capable model, it felt like the old oai models back when we were all excited but couldn't actually trust them even in the littlest ways. What harness were you using, did you do any work to make it better? What was I doing wrong? I just pointed opencode at it, with a pretty simple (large-ish) d…

It’s so fascinating watching people on here bicker about models like fine wines. Wild times we live in. Wild times.

Re: Qwen 3.8

#209

Post by fidotron »

baq wrote: post #78
gardnr wrote: post #6

Earlier quoted context omitted.

It's hard to say what their motivation is. The Chinese firms seem to be working hard to commoditize intelligence which may be the most effective way to debase American frontier labs. And yeah: it also happens to be really good for humanity.

There’s a Twitter thread making rounds by Dean Ball about deceleration in AI development caused by open models and I can’t understand how people don’t see that it’s true: open models dismantle the frontier lab capex spend potential by reducing the training budget to zero in the limit. Tokens from different providers are not fungible, but customers are nevertheless very price sensitive and close enough is good enough,…

The big decelerationist threat is a sudden reduction in competition. If either OpenAI or Anthropic drop out or the open weights stuff is banned/becomes uncompetitive then the motivation and tolerance for taking risks with the larger training runs tanks.

The closest we've seen to this in tech in recent decades was iOS vs Android, where Android only really was competitive for a very short window of time (approx 4.x) and it was during that period that both Android and iOS actually improved dramatically for end users. Once Android lost the plot again, and especially in the US market, all that energy started going in some very silly directions.

Re: Qwen 3.8

#210

Post by 5701652400 »

2Gkashmiri wrote: post #157
5701652400 wrote: post #99

in my experience of 1 month daily use, Qwen 3.7 Pro is just unusable. wastes too much time, goes off track, useless stuck loops, cannot debug at all. Deepseek V4 Pro is night-and-day compare to Qwen. actually Qwen models seems the worst SWE experience so far. and it is super expensive compare to Deepseek. cannot delegate anything to it, cannot use it real-time low-level tasks either. totally unusable.

Can you tell me more about deepseek? I paid $2 for deepseek api, put the key in void editor and made a crypto tool in html. It turned out to be around 67kb. I used sample files in CSV that were a few hundred lines. It spent around $1.8 in the hour or two or light coding and follow up bugs. Is it really really this much? I can't imagine spending a month using it for a day job, it would cost more than the salary so wha…

so Deepseek 4 Pro cannot go on own sessions for too long.

I delegate small-medium tasks: refactors, summaries, research, writing tests + have very good codebase already + extensive history / architecture / docs / linters. so it picks up and does decent small-medium scope work. it is fast, accurate, cheap. does exactly what I want directly and does not waste time nor tokens.

definitely not "implement me complex greenfield project".

Post reply on HN