Live data from Hacker News

Qwen 3.8

twitter.com

121–130 of 793 posts

Re: Qwen 3.8

#121
post #90

Earlier quoted context omitted.

DeepSeek V4 pricing is insane, 10x-30x cheaper to use than most other models, and it usually is good enough for most tasks.

Who do you buy DeepSeek from? I bought it through OpenRouter and used it with Pi agent. The model was good, but there appeared to be a pricing glitch or something, because it burned through $50 in under an hour on pretty trivial stuff. Pi agent claimed it only used like $1. OpenRouter claimed differently and said I used all $50.

sounds like a caching issue, and maybe other issues too

Re: Qwen 3.8

#122
post #111

Earlier quoted context omitted.

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…

If by Opus you mean Opus 4 and not Opus 4.8, then sure.

> 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.

Re: Qwen 3.8

#123
post #109

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

Is qwen 3.6 27b the best model you can run locally at the moment? Not that I have the VRAM for it, but just curious.

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.

Re: Qwen 3.8

#124
post #4

I assume that this announcement has been prompted by that of Moonshot AI, which has just announced a 2.8T parameter open-weights LLM, Kimi K3, to be published on Huggingface by 27 July. Now the response of Alibaba is that they will also publish soon a big open weights LLM, the 2.4T parameter Qwen 3.8. I wonder if Alibaba has always planned to make this big LLM open weights, or they have chosen to do this now, to bett…

They did not want to get brutally weightmogged

Re: Qwen 3.8

#125

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.

> Qwen 3.7 Pro is just unusable. wastes too much time, goes off track, useless stuck loops, cannot debug at all. D Anthropic should not have bugged their knowledge distillation attacks.

> Anthropic should not have bugged their knowledge distillation attacks.

It is like one of Pizzaro's men crying that someone have stolen his precious golden dublons

As Lenin have said - "Loot the looters" (Russian: Грабь награбленное)

Re: Qwen 3.8

#126
post #62

Earlier quoted context omitted.

How does this explain open weights? They could easily take the same closed route like their American friends

Well, if you look at Alibaba's financials for FY 2026 https://data.alibabagroup.com/ecms-files/1514443390/5b9061ed... their sales and marketing expenses rose by about 100 billion RMB (10% of revenue), "primarily attributable to the investment in user experiences of Alibaba China E-commerce Group and user acquisition of Qwen app." So it seems like it's very important to them that people use the Qwen app and they're wi…

They’re also trying to take an axe to the lead the US has in the field at a time when sovereignty and “owning your platform” are the words of the day. Open source/open weight LLMs can steal the lunch of US competitors even if they aren’t the best of the best.

Re: Qwen 3.8

#127
post #90

Earlier quoted context omitted.

DeepSeek V4 pricing is insane, 10x-30x cheaper to use than most other models, and it usually is good enough for most tasks.

Who do you buy DeepSeek from? I bought it through OpenRouter and used it with Pi agent. The model was good, but there appeared to be a pricing glitch or something, because it burned through $50 in under an hour on pretty trivial stuff. Pi agent claimed it only used like $1. OpenRouter claimed differently and said I used all $50.

I can highly recommend OpenCode Go.

I use it from pi.dev as well through the OpenCode Go $10 subscription ($5 first month).

Used more than 20M tokens at a cost of ~$20 (up to $60 is included in the $5 plan) Out of which deepseek pro had ~200 messages which is around 1.5M tokens (10+M cached)

Re: Qwen 3.8

#128
post #90

Earlier quoted context omitted.

DeepSeek V4 pricing is insane, 10x-30x cheaper to use than most other models, and it usually is good enough for most tasks.

Who do you buy DeepSeek from? I bought it through OpenRouter and used it with Pi agent. The model was good, but there appeared to be a pricing glitch or something, because it burned through $50 in under an hour on pretty trivial stuff. Pi agent claimed it only used like $1. OpenRouter claimed differently and said I used all $50.

Check cache hits in your logs. You can use Openrouter or pi config to pin providers with best cache hit rates (or disable ones with the worst).

I use Openrouter for everything except Deepseek. For Deepseek I use their API directly.

Re: Qwen 3.8

#129
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.

someone will keep putting out consumer level models. Once you have the larger models, you can derive the smaller onces.

Europe will definitely be interested in democratizing these things if China starts losing interests; from there, there'll be more countries looking to keep their citizens entrained in their own Country's infrastructure.

It'll especially be true if the memory cartel keeps prices high and NVIDIA tries to gouge higher memory models.

It's an arms race everyone can join because PC hardware was mostly democratized in the last decade.

Re: Qwen 3.8

#130

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.

Qwen3.7 pro is meh, but 3.7 max is a very good model
Post reply on HN