Qwen3-4B-Thinking-2507
36 comments
·August 6, 2025svnt
It is interesting to think about how they are achieving these scores. The evals are rated by GPT-4.1. Beyond just overfitting to benchmarks, is is possible the models are internalizing how to manipulate the ratings model/agent? Is anyone manually auditing these performance tables?
film42
Is there a crowd-sourced sentiment score for models? I know all these scores are juiced like crazy. I stopped taking them at face value months ago. What I want to know is if other folks out there actually use them or if they are unreliable.
hnfong
Besides the LM Arena Leaderboard mentioned by a sibling comment, if go to the r/LocalLlama/ subreddit, you can very unscientifically get a rough sentiment of the performance of the models by reading the comments (and maybe even check the upvotes). I think the crowd's knee-jerk reaction is unreliable though, but that's what you asked for.
nurettin
This has been around for a while https://lmarena.ai/leaderboard/text/coding
klohto
openrouter usage stats
setsewerd
Since the ranking is based on token usage, wouldn't this ranking be skewed by the fact that small models' APIs are often used for consumer products, especially free ones? Meanwhile reasoning models skew it in the opposite direction, but to what extent I don't know.
It's an interesting proxy, but idk how reliable it'd be.
esafak
https://openrouter.ai/rankings
The new qwen3 model is not out yet.
esafak
This one should work on personal computers! I'm thankful for Chinese companies raising the floor.
johndhi
[flagged]
whimsicalism
You can see not from clicking on their name, I wouldn’t assume every positive comment about China is a ‘shill’ - there are many people unhappy with our current neo-cold war.
Astroturf/shill accusations are also against the HN ethos. https://news.ycombinator.com/item?id=11257034
redman25
I’m American. Just giving some background to the feeling. There’s some discontent with some western communities (localllama) that Chinese developers have been open weighting all of their models while most western models have been closed weights.
evilduck
Meta seems to have now stepped out of the running despite being the local LLM catalyst. Anthropic has done nothing. IBM's Granite and Microsoft's Phi are both very far behind. AWS doesn't even attempt to compete. Grok failed to make good on their promise. OpenAI only even entered the game yesterday so it's hard to tell if they're actually serious since they released such an overly censored model that isn't really better than Qwen options and at its smallest still requires a decent computer. Google seems to be the only domestic contender on the level of what Chinese companies are doing and they're being very careful to not cannibalize Gemini with Gemma.
Right now though China is dropping huge improvements across the entire spectrum of model sizes with Qwen, Kimi, DeepSeek, GLM, and Yi. We've also got Mistral doing competitive self-hosted models too, but they're French. Local AI tooling is plainly _not_ being driven forwards by the United States.
thatwasunusual
Let's say any country create the most powerful - and thus best - LLMs. They over time infiltrate it with their political will. Over 20-30 years, I'd imagine people asking those LLMs will have their minds' shifted.
But. That's just me, my pessimism-sci-fi scenario.
Imustaskforhelp
I think that just as how perplexity had actually created a deepseek(fine-tune?)[1], then there is more and more incentive towards making uncensored models though I am gonna be honest, Kimi K2 isn't that censored but I tried the gguf variant of this model on local pc and it definitely is censored / biased towards china (like taiwan is part of them and so on)
But still, the most recent version of american foss model gpt-oss is just so filled with censorship that its just not worth it in the name of "safety", so to me both are doing censorship but I'd much rather use chinese censorship since its only censored on chinese topics and I mean, I personally wouldn't be ever asking chinese models chinese questions but maybe that's just me.
And even if I would, I would probably ask it on some uncensored, in fact I was actually thinking of creating a fine tune like the perplexity, or just this idea to break chinese censorship.
I also think that some better idea needs to come up with multi modal approach so that censorship could be removed by mixing and matching american and chinese models, I do think it is far from reality but I read a recent comment about harmony which gpt-oss uses and it does look promising I am not sure.
whimsicalism
individualized recommendation systems are enough to drive everyone nuts
frontsideair
According to the benchmarks, this one is improved in every one of them compared to the previous version, some better than 30B-A3B. Definitely worth a try, it’ll easily fit into memory and token generation speed will be pleasantly fast.
GaggiX
There is a new Qwen3-30B-A3B, you are compare it to the old one. https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507
gok
So this 4B dense model gets very similar performance to the 30B MoE variant with 7.5x smaller footprint.
smallerize
It gets similar performance to the old version of the 30B MoE model, but not the updated version. https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507
Imustaskforhelp
I still think that its still very commendable though.
I am running this beast on my dumb pc with no gpu, now we are talking!
jampa
I am reading this right, is this model way better than Gemma 3n[1]? (For only the benchmarks that are common among the models)
=====
LiveCodeBench
E4B IT: 13.2
Qwen: 55.2
===== AIME25
E4B IT: 11.6
Qwen: 81.3
meatmanek
Reasoning models do a lot better at AIME than non-reasoning models, with o3 mini getting 85% and 4o-mini getting 11%. It makes some sense that this would apply to small models as well.
tolerance
Is there like a leaderboard or power rankings sort of thing that tracks these small open models and assigns ratings or grades to them based on particular use cases?
esafak
cowpig
Compare these rankings to actual usage: https://openrouter.ai/rankings
Claude is not cheap, why is it far and away the most popular if it's not top 10 in performance?
Qwen3 235b ranks highest on these benchmarks among open models, but I have never met someone who prefers its output over Deepseek R1. It's extremely wordy and often gets caught in thought loops.
My interpretation is that the models at the top of ArtificialAnalysis are focusing the most on public benchmarks in their training. Note I am not saying XAI is necessarily nefariously doing this, could just be that they decided it's better bang for the buck to rely on public benchmarks than to try to focus on building their own evaluation systems.
But Grok is not very good compared to the anthropic, openai, or google models despite ranking so highly in benchmarks.
threeducks
OpenRouter rankings conflate many factors like price, popularity, output quality and legal concerns. They can not tell us whether a model is popular because it is free, or because many people have heard about it, or because a model is genuinely good, or because the lawyers trust the provider.
byefruit
The openrouter rankings can be biased.
For example, Google's inexplicable design decisions around libraries and APIs means it's often worth the 5% premium to just use OpenRouter to access their models. In other cases it's about which models particular agents default to.
Sonnet 4 is extremely good for tool-usage agentic setups though - something I have found other models struggle to do over a long-context.
ImageXav
Thanks for sharing that. Interesting that the leaderboard is dominated by Anthropic, Google and DeepSeek. Openai doesn't even register.
esafak
I shared a link to small, open source models; Claude is neither.
GaggiX
Claude Opus is in the top 10, also people via OpenRouter mostly use these models for coding and Claude models are particularly good at this, the benchmark doesn't account only for coding capacities tho
whimsicalism
grok is not bad, i think 4 is better than claude for most things other than tool calling.
of course, this is a politically charged subject now so fair assessments might be hard to come by - as evidenced by the downvotes i've already gotten on this comment
If you want to have an opinion on it,
just install lmstudio and run the q8_0 version of it i.e. here https://huggingface.co/bartowski/Qwen_Qwen3-4B-Instruct-2507....
you can even run it on a 4gb raspberry pi Qwen_Qwen3-4B-Instruct-2507-Q4_K_L.gguf https://lmstudio.ai/
Keep in mind if you run it at the full 262144 tokens of context youll need ~65gb of ram.
It's pretty good for summaries etc, can even make simple index.html sites if you're teaching students but it can't really vibecode in my opinion. However for local automation tasks like summarizing your emails, or home automation or whatever it is excellent.
It's crazy that we're at this point now.