6 ms·
Qwen 3.7 Preview
- kelsey98765431 5mo agohttps://xcancel.com/Alibaba_Qwen/status/2056403591464984753 https://xcancel.com/Alibaba_Qwen/status/2056403591464984753 > Qwen3.7 Preview lands on Arena ！ > Here come Qwen3.7-Max-Preview & Qwen3.7-Plus-Preview. Alibaba now #6 lab in Text, #5 in Vision. > Can't wait to release Qwen3.7 series models！Stay tuned! @arena
- Onavo 5mo agoWhere's Grok 4.3 on the leaderboard?
- rspoerri 5mo agoI am very interested in seeing new qwen models. Qwen3.6 27b is the first one that can do things and doesnt constantly loose "it's mind" and that can be run on a 3090 with a good context size. But it's sometimes getting into a loop.
- giancarlostoro 5mo agoI had a flavor of an older version of Qwen (I forget which one to be fair) that was coding along, then lost itself in a loop, I was so confused, it was just a random greenfield "lets see how it does" type of project anyway.
- tedivm 5mo agoI've completely replaced GitHub Copilot using Sonnet 3.6 with OpenCode using Qwen3.6 27b, and it's been a great experience.
- verdverm 5mo agoSimilar, but I'm using 35B A3B variation with experimental MTP support OpenCode is pretty good too
- 2001zhaozhao 5mo agoIs Sonnet 3.6 a typo? Claude Sonnet 3.6 (aka 3.5 New) is an ancient model from 2024
- satvikpendem 5mo agoPretty sure they meant 4.6
- tedivm 5mo agoYeah that was a typo, I meant 4.6.
- BillStrong 5mo agoLook on HuggingFace, there is a template that is supposed to fix the updates for the Qwen Models. https://huggingface.co/froggeric/Qwen-Fixed-Chat-Templates https://huggingface.co/froggeric/Qwen-Fixed-Chat-Templates Maybe will help you?
- deleted 5mo ago[deleted]
- Jach 5mo agoI sort of thought this about qwen3.5 35b, finally a local model that isn't a complete waste of electricity, but "upgrading" to 3.6 35b left me disappointed. It seemed more like a downgrade. But honestly I've barely used either. Subjectively they still seem far from the frontier models, but for what they can do, it's great to be able to do locally.
- boppo1 5mo agoHow are they just for chat / questions?
- Jach 5mo agoPretty decent, it's given similar book recommendations as Claude when I feed it my list of read books and thoughts on them. You'll have to tell them to never use emojis. I was using 3.5 a while ago to generate some flavor text while I was playing a bit of an old-school dungeon-crawler game (it's like Wizardry), a genre I don't particularly enjoy much, but it's funner with the flavor text. Worth setting up something like open webui or other front-ends since a pure CLI experience via ollama is pretty bad.
- giancarlostoro 5mo agoThere I was waiting on a smaller version of Qwen 3.6 to drop so I can run it on my Mac, and then bam, they drop this.
- hydra-f 5mo agoVision has become totally underappreciated, whereas I believe it brings important advantages to a model Also, a big caveat in using Qwen models has always been its speech patterns. I do wonder how Google made the Gemma lineup so good at this Let's hope Alibaba continues to open source its models
- jwr 5mo agoAgreed. Incidentally, in my testing, qwen models (qwen3.6-35b-a3b and earlier 3.5) are WAY better with vision than gemma4-26b-a4b. I would normally want to stick with gemma4 only (I use it for spam filtering), but it just doesn't cut it for vision work, and qwen models do.
- greenavocado 5mo agoGod I love qwen3.6-35b-a3b especially Q8
- verdverm 5mo agoI second this notion, I am impressed daily with what little Qwen can do
- tredre3 5mo agoThat has been my experience has well. Qwen 3.5/3.6 are far better at vision. Even the 9B model beats Gemma 4 31B in my use case. They describe the scene more accurately and they focus on the important elements like a human would. Gemma 4 frequently misses important element, doesn't understand what things are, and is very coy even if you ask for lots of detail. You have to give it hints "hey what's that round thing on the left" to get half decent answers. (Yes I did set the min-tokens correctly. I also tested bf16 and Q8 to make sure it wasn't a quant issue.) It's unfortunate because Gemma 4 is so so so much better at natural language interactions.
- argee 5mo ago> qwen models (qwen3.6-35b-a3b and earlier 3.5) are WAY better with vision than gemma4-26b-a4b Can you give an example? And/or is there a benchmark specifically for this?
- sleepyeldrazi 5mo agoI don't think I can handle another small model release by qwen, I'm still trying to find the limits of 3.6 27B and they are already threatening us with a new one? But jokes aside, I love the fast iteration, these are most probably again finetunes on the 3.5 architecture that appear better in internal testing, which is still very nice to see. Putting more and more pressure on the bigger labs to perform better is always a good thing.
- plutokras 5mo ago[dead]
- genxy 5mo agoHow good must their training pipelines be? Releasing publicly and at this rate has made them very efficient.
- sleepyeldrazi 5mo agoFinetuning takes little resources, the base model training is the slow and expensive part. Architecturally 3.5 models are identical to their 3.6 counterparts, that is why there is a consensus that those are probably finetunes and not re-trained from scratch, like you will se many people publish their own on huggingface.
- trilogic 5mo agoQwen 3.6 35B (finetuned) is so good that it became standard open weights for everyday use. Is not far at all from proprietary models if you give it tools, skills and agents etc, it can actually finish the job. (Thank you Qwen team, appreciated). Using opensource now we can definitely rely to design from scratch very complicated architecture and build pretty fast the full pack. Wish to see Europe AI unleashed, wake up.
- mettamage 5mo agoDo you have a good resource on how to finetune a model like Qwen? I am curious to try it out.
- verdverm 5mo agoUnsloth has good resources
- trilogic 5mo agoHere is a dataset you can choose from: https://huggingface.co/datasets/Avtrkrb/combined-reasoning-opus-4.6-opus-4.7-kimi-k2.5-kimi-k2.6-glm-5.1 https://huggingface.co/datasets/Avtrkrb/combined-reasoning-o... Get a 10000 samples from it according to your needs and go for it. The key (in my opinion) is not cutting the Sequence Length among other things. Whatever traditional finetuning repo will do, if your hardware supports it Unsloth is faster.
- Aurornis 5mo ago> Is not far at all from proprietary models if you give it tools, skills and agents etc, I use Qwen 3.6 27B, the dense version of this model which is slightly better. I don't agree that it's close at all. Maybe for some small, easy tasks, but not for working on real codebases. It's amazing for something I can run at home, but the difference between it and Opus or GPT-5.5 is huge.
- tedivm 5mo agoI've had the opposite experience, and have built multiple fantastic applications with Qwen3.6 27b. What quantization have you tested with?
- kethinov 5mo agoCan someone explain what the current state of model benchmarking is? If you try to look up what the best locally runnable model is, you get a bunch of random blog posts using idiosyncratic criteria to rank things seemingly based on one dude's opinion. Ideally I would love to see a leaderboard with relatively objective ranking criteria that 1. lets you filter by open weight / locally runnable, 2. filter by date of release (nothing older than x), and 3. is agnostic to hardware requirements. I just want to know what the best model is. Let me worry about how I will afford to run it. I love the llmfit project for seeing what will run on your hardware, but it would be nice to know what I'm missing out on by not having better hardware, thus why objective hardware-agnostic ratings would be helpful.
- vessenes 5mo agoThat would be nice, but it's not going to be possible. Any open benchmark has a very short life, since it will be pulled in and DPO / RL trained quickly for benchmaxxing purposes. So, you'll need a private test to have a hope of something fair. (These also get leaked over time, btw, so even then there's a window of usability). These are expensive to run. Now consider that there might be 15-20 viable quants for a given open model release; someone would have to want to pay for these private evals to be run on them. Even then, a good read through unsloth's commits and blog posts will remind you that there's quite a lot of engineering work to be done to get model inference working properly, even for models released by frontier or near-frontier labs. So, you'd want to make sure that you have a replicable 'best engineered' deployment to evaluate, or at least one that's closest to your hardware and fits the bill. Upshot - it's much faster to download and try out a model, and possibly cheaper too. Well, cheaper since hugging face is paying the bandwidth bills.
- cyanydeez 5mo agothere are benchmarks that have nothing to do with the training material, but with how the models are capable of things like reading code: https://needle-bench.cc/ https://needle-bench.cc/ Generally, you give them a document and you ask them to retrieve some subsection of the document then rate them on what they retrieved. You can always find enough random documents, or create your own, to always run these and you can make it arbitrarily long. It's definitely a valid non-maxxable context test.
- vessenes 5mo agoToday I learned Meta's new model is preferred to everything but claude. That is .. a real surprise! Congrats to the Meta team.
- vessenes 5mo agoI don’t mind a principled downvote, but can a downvoter explain his or her reasoning? Genuinely curious. I found the linked rankings surprising, and think of myself as relatively well informed. Please, enlighten me..
- mempko 5mo agoI love that open weight models are catching up so quickly. Also hilarious how far behind Grok is. I guess demand for Grok must be poor if Anthropic is able to rent resources from xAI.
- svachalek 5mo agoTo play devil's advocate I do feel like Grok has a unique "feel" to it. All the Chinese models feel like GPT or Claude distillations, but Grok has a certain unique way of saying and doing things. But that said, it also feels a year behind the state of the art.
- SwellJoe 5mo agoWith an Austrian accent, perhaps?
- kennywinker 5mo agoYes, but sortof mechanical… like a mecha… mecha something.
- martheen 5mo agoFor an artificial it's weirdly obsessed with farmers in a certain country across the ocean
- ac29 5mo agoJust to be clear, "Plus" and "Max" Qwen models are closed. Seems likely smaller open versions will be released, but that's not what was announced today
- throwa356262 5mo agoWould xAI do this if Grok was competitive? https://www.nytimes.com/2026/04/03/business/spacex-ipo-grok-elon-musk.html https://www.nytimes.com/2026/04/03/business/spacex-ipo-grok-...
- nubg 5mo agolmao at opus 4.7 being a downgrade
- SwellJoe 5mo agoThey made it less sycophantic. Which is a good thing for mental health, but maybe a bad thing for popularity contests.
- Havoc 5mo agoSo glad they’re holding steady on open weights. At least for now. Worried the Chinese team will change their mind once they have parity
- the_duke 5mo agoOf course they will. Right now they want to prevent the US labs from gaining any sort of self-reinforcing oligopoly on the space, and to let the ecosystem in China flourish. That will all die sooner or later.
- satvikpendem 5mo agoWill they release the large models as open weight too? So far it seems only 35 or 27 B etc models are being released with nothing larger unlike before.
- raffael_de 5mo agoI have a tangential question. Provided that it is correct that current proprietary models are offered at below cost-covering rates (I believe this is a consensus if I'm not mistaken¹); what factor (multiplication) would have to be applied approximately to current rates to reach break even? ¹: I think I read this a couple of times but I'm not sure if correct to begin with. Can this be substantiated based on annual financial reporting or other published business metrics by OpenAI, Anthropic et al.?
- bachmeier 5mo agoI'm not much interested in vibe coding (for those who aren't aware that LLMs have other uses). The specific model I've been using with Ollama is hf.co/unsloth/Qwen3-Coder-30B-A3B-Instruct-GGUF:UD-Q4_K_XL and it's amazing how fast it is on 64 GB of RAM and i5-13400 CPU. No GPU on this computer. Gemma 4 E4B will think for a couple of minutes vs 3-5 seconds for Qwen. It's hard to believe how much you can do with such limited hardware using their models.
- metalliqaz 5mo agoI have a much more powerful PC and I would not call Qwen3-Coder-30B-A3B "fast" on my machine by any stretch of the word. How are you running it?
- pancsta 5mo agoProbably in the chat / no sys prompt mode for docs only. Try to refac a codebase using a CPU only…
- maille 5mo agoWhat are your use cases?
- throwa356262 5mo agoSince you are using unsloth models from HF, why not use Unsloth Studio instead of Ollama? It is supposed to be faster + they will update the new models multiple times during the first month to correct bugs and performance issues https://unsloth.ai/docs/new/studio#quickstart https://unsloth.ai/docs/new/studio#quickstart
- 0xbadcafebee 5mo agoI stopped caring about benchmarks at MiniMax M2.5. I no longer want more advanced models. I want cheaper models that don't slow down when everyone else is online.
- brianwawok 5mo agoRun locally and you can now do it on an airplane
- monksy 5mo agoFor the safer link: https://xcancel.com/Alibaba_Qwen/status/2056403591464984753 https://xcancel.com/Alibaba_Qwen/status/2056403591464984753
- julianlam 5mo agoGemma 4 and Qwen 3.6 were when my local inference experiments graduated from toy challenges with much hand holding to actually full day back and forth with good ability to utilise tool calls to discover how things are glued together. I'm not talking about greenfield dev, I'm talking about interfacing with an existing decade old codebase.
- alfiedotwtf 5mo agoThe jump from 3.5 to 3.6 was noticeable and set the bar. If they can keep the momentum, I’d pretty much say Qwen and China won the AI wars