| ▲ | 5701652400 a day ago |
| 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. |
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| ▲ | 3abiton a day ago | parent | next [-] |
| > 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. I have used both Qwen3.6-35B and Qwen3.6-27B locally (both Q8 quantized with llama.cpp). I have also used antirez's quant of DS4-flash. They all performed within the same tier, DS4 being a bit more efficient, but they all gave really good results, mainly used for bash scripting, debugging, python and some C++. I am curious what type of applications/langauges failed with Qwen? One thing to note, the chat templates were "broken" for qwen models and had to debug it, there are already effort on this. Tbh, the same with gemma. |
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| ▲ | chewz a day ago | parent | prev | next [-] |
| 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 with is right now but too early to say anything. At 10% of regular price it is a steal so far. |
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| ▲ | gchamonlive a day ago | parent | next [-] | | It's useless to talk about models and harnesses without context and method. Depending on how you use the model and what the model is used for, experience may vary drastically. Also, different models with different harnesses require different approaches. I've been using https://gitlab.com/gabriel.chamon/orisun which is my own simplified methodology, for coding web apps in python and elixir and have been very successful using qwen3.6 27b Q4 locally with help of larger models for architecture, so I get very suspicious when people talk how useless larger models are. They are either using it for a domain that models don't perform well or just not using it right. | | |
| ▲ | taosx a day ago | parent [-] | | I'm not sure about "useless" but from my experience agentic coding leads to death by a thousand cuts for all projects I've seen so far. Small decisions missed in a codebase that leads to degradation in correctness, reliability and performance. At some point it only takes one engineer to be careless, others skipping PR because they are AI generated... | | |
| ▲ | dofm a day ago | parent | next [-] | | I got into a bit of an argument a while back when I used the word "crass" to describe some of the code decisions I've seen Claude make (in someone else's project that I have to work with). But it is how I feel and it feels like the right word for the job. Because as you say, good code projects start out with good decisions. It's like when you see a CAD design with a sequence of features that exist only to fix problems caused by starting from the wrong principles or the wrong baseline. Sure the resulting part may end up identical as a solid for that specific need, but it could have been done in a way that was more robust, simple, easier to understand and modify, and where the design doesn't break in an unexpected way due to a small change of an early measurement. (CAD has made my instincts much more visible to me) | | |
| ▲ | taosx a day ago | parent [-] | | Exactly, and even when humans make bad decisions there is some friction, I feel that llm's don't have/notice that friction, they just bulldoze without caring about anything else. | | |
| ▲ | whstl 18 hours ago | parent [-] | | Yeah. IME, LLMs actually introduces a lot of friction when you want to improve the design. They are 100% biased towards the status quo. |
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| ▲ | gchamonlive a day ago | parent | prev | next [-] | | All of which you had with only humans in the loop. Catalogue problems so they become technical debt and tackle them periodically. Seems to me like this is less of an AI problem and more of bad management. | |
| ▲ | voxgen a day ago | parent | prev [-] | | It's a solvable problem if you're willing to throw more tokens at it. Frontier models have gotten very good at cleaning up their own messes. You just need the right skills/loops, and to stick to models that consistently follow instructions (i.e. GPT-5.5/GPT-5.6-Sol). |
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| ▲ | exceptione a day ago | parent | prev | next [-] | | > 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. | |
| ▲ | nullbio a day ago | parent | prev | next [-] | | If by Opus you mean Opus 4 and not Opus 4.8, then sure. | | |
| ▲ | chewz a day ago | parent [-] | | > 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. | | |
| ▲ | porksoda a day ago | parent | next [-] | | 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) data cleaning project. | | |
| ▲ | VladVladikoff a day ago | parent | next [-] | | It’s so fascinating watching people on here bicker about models like fine wines. Wild times we live in. Wild times. | | |
| ▲ | nozzlegear a day ago | parent [-] | | It's not a frontier LLM if it's not made in the Silicon Valley region of California, otherwise it's just a sparkling LLM. |
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| ▲ | Planktonne a day ago | parent | prev | next [-] | | > My experience was so much different to this, that I have the unfortunate impression that you're shilling I think you might both just be reading way too much into one-off random experiences that you've decided are evidence of significant and stable capability. | |
| ▲ | chewz a day ago | parent | prev [-] | | Have you actually used Opus 4.8 in Claude Code? It takes way too long to do any practical task on higher thinking levels due to over-engineering. And I am not the only one complaining. Lots of people downgrade to Opus 4.6 exactly for this reason. Opus 4.8 training works well for agentic work. Not for code harness. EDIT: ``` stronger on coding and raw capability but can be more argumentative, verbose, and costly. Reliability and instruction-following
Many users say 4.6 felt more reliable and followed instructions better. "With 4.6, when I tell it something, it actually remembers the spirit of what I asked for and keeps applying it." Others report 4.8 drifts from preferences and can be frustrating to control. "I still find myself getting frustrated when it ignores preferences and drifts from instructions" Some people find 4.7/4.8 push back more and act more adversarial than 4.6. "The biggest complaint against 4.8 is that it is argumentative and "pushes back" constantly" Coding quality and capability
Several users praise 4.8’s coding strength and thoroughness. "4.8 is technically impressive, especially for coding" Other reports say 4.6 could be better for certain coding workflows and breaks less. "4.6 still >> 4.8 for anyone else as well? Maybe I'm in the minority, but for my use cases Opus 4.6 is still better than" Some recommend mixing models: use 4.8 for key tasks and 4.6 for general work to save tokens. "What I do is... use 4.8 for key moments, and for everything else 4.6" Cost, speed and token behavior
Users note 4.8 often uses more tokens and can feel slower because it “thinks” more. "4.8 is much more cautious, and as a result - slower. It checks everything, thinks for a long time etc." ``` [https://www.reddit.com/answers/601770d4-4059-478d-aa52-b445c...] | | |
| ▲ | anonzzzies a day ago | parent | next [-] | | Works extremely well for us. I never know what other people are doing when we read these stories. | | |
| ▲ | rapind a day ago | parent [-] | | Yeah I found 4.7 and 4.8 to be downgrades from 4.6. I don't know if it was the model or just Anthropic's scaling issues though TBH. I found working with the Claude Code max (20x) sub would work awesome in between new models. A week before up to 2 weeks after, it would go to crap, dumber, slower, outages, harness churn, etc. I'm finding the same with ChatGPT recently since the 5.6 release. Not as bad though, but sluggishness at times, harness churn (creating bugs and crashed), and occasional availability issues that cause me to downgrade to 5.5. It's gotten to the point where I dread a new model release from these companies because it's guaranteed to be disruptive! I assume the pay per use API is less impacted. |
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| ▲ | sunaookami a day ago | parent | prev [-] | | Reddit is the absolute worst way to find real experience. Opus 4.8 is a very capable model and no chinese model can outdo it. |
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| ▲ | Narciss a day ago | parent | prev | next [-] | | I can’t believe that anyone would actually think this. This | |
| ▲ | a day ago | parent | prev | next [-] | | [deleted] | |
| ▲ | mattmanser a day ago | parent | prev [-] | | 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? | | |
| ▲ | piguin a day ago | parent | next [-] | | My own experience is that the vast majority of programmers have experience with one model and maybe some short usage of earlier models from a competing choice but want to be using the model with the highest popularity and reputation. I've worked with people who actually had to test multiple choices for their team who didn't understand why they were pressured to select Claude for programmer morale. | | |
| ▲ | AussieWog93 a day ago | parent | next [-] | | I went from cycling between models all the time in Cursor (some would randomly be better at certain tasks than others) to just going pure Opus 4.5 when that came out - it was so far ahead of anything else at the time. Interestingly with Fable vs GPT-5.6 I think they've lost their lead a bit. I'm finding Fable can't do certain work that 5.6 Sol Ultra can - especially when it comes to webpage design. Grok 4.5 was fast but made mistakes that GPT/Fable just don't. I'm curious to try Kimi. | |
| ▲ | WarmWash a day ago | parent | prev [-] | | When iOS users are given an Android phone, they complain about how awful of an OS it is. In reality, they just aren't used to it. | | |
| ▲ | Levitz a day ago | parent [-] | | What exactly is there to get used to? Do people really use each model very differently? There's a learning curve as in everything, but there is nothing that comes to mind for me when I use codex as opposed to claude |
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| ▲ | ivewonyoung a day ago | parent | prev | next [-] | | > is wildly successful with legions of programmers virtually demanding access while abandoning ChatGPT and Copilot in droves Do you have a source for that? Codex went from 5 million users to 9 million users in the past few weeks since GPT 5.6 released. It was so popular that Claude was forced to extend Fable access by a week and then permanently for some plans. | |
| ▲ | gigatexal a day ago | parent | prev [-] | | Exactly what I’m thinking, too. |
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| ▲ | amelius a day ago | parent | prev | next [-] | | Can we please include information of what languages we use when making claims like these? It makes a huge difference if you're writing Javascript/HTML/CSS, Python, or C++/Rust. Also the application type matters, e.g. user interfaces or scientific computing. | | |
| ▲ | 5701652400 a day ago | parent [-] | | me: Go, Swift, Kotlin, bash k8s/gcloud domain: typical web backend tier, mobile apps. not particularly complex, but requires OOP/architecture/system design. |
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| ▲ | gigatexal a day ago | parent | prev [-] | | What the difference between your experience and https://news.ycombinator.com/user?id=5701652400? ‘s? Such diametrically different ones. |
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| ▲ | big-chungus4 a day ago | parent | prev | next [-] |
| Qwen3.7 pro is meh, but 3.7 max is a very good model |
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| ▲ | Demiurge a day ago | parent [-] | | Are these different models or different efforts for thinking (internal back and forth review) using the same model? |
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| ▲ | 2Gkashmiri a day ago | parent | prev | next [-] |
| 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 what gives? I understand the local ai and all that but do cloud providers cost this much? Earlier I thought "billion tokens" but now not sure |
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| ▲ | 5701652400 a day ago | parent | next [-] | | 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". | |
| ▲ | k__ a day ago | parent | prev | next [-] | | My 2 weeks with DeepSeek V4: Pro is ~50% more expensive than Flash. Both need babysitting. Plan, split in small tasks, give it docs, types, tests, linter, best practice examples, etc. Always start a new session when starting a task. Do regular manual sanity checks, and tell it to find issues in the codebase. I pay like $1,50 per day for Pro. | | |
| ▲ | p1necone 18 hours ago | parent | next [-] | | I use GLM-5.2 as an orchestrator model which delegates to Deepseek subagents (v4 flash or pro depending on complexity) and it works pretty well for a quite complex compiler codebase when I do deep enough up front planning for features/fixes. If you believe the benchmarks Deepseek v4 is pretty shitty at long running work in large codebases, but really really good at self contained algorithmic/math reasoning - which is basically ideal for a compiler for a language with a relatively complex type system. And with its cache pricing it's very cheap. GLM-5.2 is too expensive at api pricing for my taste though even when it's not producing the bulk of the output tokens - I pay for the mid-tier subscription and switch the orchestrator over to other models via open router when I run out - Minimax M3 feels okay but definitely a step down from GLM-5.2. | |
| ▲ | h2aichat a day ago | parent | prev | next [-] | | I had a similar experience | |
| ▲ | 5701652400 a day ago | parent | prev [-] | | very simlar experience. I would also add that I run it this way ~12hour a day non-stop. 300M / tokens per day (99.7% cache hit). |
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| ▲ | aduwah a day ago | parent | prev [-] | | A local AI is not about cost. In fact you will likely pay more for it than with most providers. Just look up the advantages of having access to a technology like this that can be self hosted |
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| ▲ | ph4rsikal a day ago | parent | prev [-] |
| > 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. |
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| ▲ | chewz a day ago | parent [-] | | > 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) | | |
| ▲ | RazorBucksICO a day ago | parent [-] | | Appealing to the Belsheviks for moral authority is, well I will just say an interesting approach. I do not have that much sympathy for Anthropic, but I do not have much sympathy for publishing companies either whose rights to a revenue stream they violated either. Are Chinese AI companies the Robin Hood in this story? Would they be so magnanimous if they had the upper hand? I don’t think so. | | |
| ▲ | trollbridge a day ago | parent | next [-] | | Considering the results from Kimi K3, it appears most the accusations of them “stealing” via distillation are unfounded accusations. | |
| ▲ | zobzu a day ago | parent | prev | next [-] | | how many hn posts do you believe arent propaganda these days? its billions, trillions were talking about. imo hn should display posters origin, such as country, bon, datacenter registered ips, and the discourse will change dramatically. | |
| ▲ | neonstatic a day ago | parent | prev [-] | | [flagged] |
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