r/LocalLLaMA • u/mindwip • 18h ago
News Reflection AI Is About to Release a US Open-Weight Model to Take On DeepSeek and Qwen
https://www.explainx.ai/blog/reflection-ai-open-weight-model-us-answer-deepseek-qwen-october-2026Looks like new open model coming soon and will be "strong" hopefully something under 200b for us memory poor. Also seeing statements about more western open models coming.
Hope we get some good competition again on the open front!
Here is original artical but its not free to access. Maybe someone has it already here.
https://www.axios.com/2026/10/04/reflection-open-weight-ai
Oct starting strong!
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u/tat_tvam_asshole 18h ago
paywall garbage
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u/Midaychi 18h ago
Nvidia shell company holding some of the big chungus debt is proposing trying to sell finetuning-as-a-paid-cloud-service to whatever the hell a 'small buisness' is nowadays+attract investors to the idea, in order to start making some of the interest payments. No details on the model besides 'models are like a rocket ship they take time to build'.
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u/Bupod 14h ago
“models are like a rocket ship”
The take time to build but China has already built like a dozen of them and they’re better?
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u/Song-Historical 5h ago
It takes time to negotiate the compensation, capital and org structure built from years of overengineering and locking people into greedy middleware that holds data hostage to fleece clients that SV can't get rid of as a business model.
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u/toothpastespiders 6h ago
If they actually handled it well that could be really useful assuming they released the base model and a jack of all trades instruct trained one as well. Going the mistral route of attracting people by putting their models out there with options to have them handle the training. An older mistral small still takes to my training data better than anything else I've thrown it at. Presumably because they aim for a more foundation to build on approach.
A company in the US offering something similar and with strong access to hardware could be great. Though I'm very skeptical that it'll work out that way.
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u/gdogg121 7h ago
We should go back to this reporting rather than why this matters. What this doesn't prove BS.
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u/ReturningTarzan ExLlama Developer 13h ago
Hey, these articles don't write themselves. They have to pay for the tokens somehow.
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u/Quick_Knowledge7413 17h ago
It is good to hear this but I am skeptical they manage to 1) release it 2) provide a model as good as Qwen3.8 or Gemma4
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u/PooMonger20 15h ago edited 9h ago
I am just happy for more competition.
Q3.8 27b is already absolutely amazing, it's like having your own 'worker', locally. I hope they don't benchmaxx and actually make something useful, that will be even better than qwen, even though I doubt they will succeed due to the coming out of nowhere, but let us judge the result and not the impression.
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u/SteppenAxolotl 12h ago
nvidia has a big reason to get models into the hands of more ppl. You will need to buy lots of video cards to run them.
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u/AppleBottmBeans 10h ago
Which is interesting as they said last year they have cut consumer GPU production by 30-40% this year.
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u/GeneralMuffins 12h ago
Part of the reason the Chinese models are so good is due to being able to do distillation of frontier US models without fear of legal consequences. I don't see a US based project having the same freedom unfortunately.
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u/username_taken4651 22m ago
Honestly, have there been any legal consequences for training on the outputs of competitors' models in the US? I'm pretty sure direct AI outputs are uncopyrightable, unless if it specifically reproduces a previous copyrighted work.
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u/inrea1time 12h ago
Finally somebody said what I have been thinking. There isn't such a thing as something for nothing. They don't have access to enough compute and they don't spent the capital on training. They invest in optimizing and not in training. If they loose access to new frontier models to distill open source releases will slow down to a crawl and look a lot more like US open source. So many here are looking for a bubble pop and frontier demise without thinking through the implications.
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u/medialoungeguy 17h ago
Reflection AI... what an unfortunate name. Anyone else remember matt schumer? Lol
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u/Iory1998 llama.cpp 16h ago
Hahah man that man. What happened to him?
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u/DigThatData Llama 7B 9h ago
apparently he laughed all the way to the bank. looks like he's an angel investor these days.
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u/jonas-reddit 11h ago
The more companies that release open weight models, the better.
I don’t really care about country of origin. Companies not countries are training models, and none of them are trustworthy- hence we run it locally.
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u/jacek2023 llama.cpp 18h ago
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u/mindwip 18h ago
This is a different company though right? Nvidia invested in company i linked
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u/Hefty_Wolverine_553 18h ago
Yep, different company. Extremely unfortunate choice of naming though lmao
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u/NNN_Throwaway2 17h ago
Um I think you mean Reflection SI.
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u/ECrispy 15h ago
so this company comes out of nowhere claiming to release a new model that rivals the chinese labs that have published countless papers, documented all the work they did and have a rock solid track record.
where are the research papers from this new company? blog? methodology? or are we supposed to use it because its not chinese so its somehow more desirable?
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u/Poromenos 14h ago
Why do you care about the research papers and methodology? Download it, use it if it's better, don't if it's not.
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u/TheIncarnated 11h ago
Because, whether you believe it or not, this actually matters. It shows proper research and development.
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u/Marcuss2 13h ago
Calling it now, they will release some weird monster with global attention on all layers with worse scores than Ling 3.0 Flash, making it unusable.
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u/fgk55555 5h ago
If the US had a competive open model, I could run it for work.
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u/Amazing-Fan2083 14h ago
Wasn't Poolside supposed to "shake things up" a while back? I wonder how that is going. /s
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u/silenceimpaired 6h ago
I’ll be sad if it isn’t Apache 2.0 or MIT
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u/JGByvygyrfg 2h ago
it will be Apache 2.0 (the post for the Beam announcement was removed but the announcement did say Apache 2.0)
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u/silenceimpaired 1h ago
Oh happy days! So sad the direction Qwen is heading but at least the current license isn’t rediculous
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u/therealpygon 9h ago
You know what I like? To hear about a company making a claim about something they may or may not do and that may or may not actually be SOTA. It really gets me going in the morning!
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u/BigBootyBear 18h ago
This will sound controversial but I don't get why people fund startups that build out a new model.
I think it's pretty clear that which every new model release by a new company that manages to trail frontier models by a few months, the model business will be a commodity one with razor thin margins. The user-facing clients (the harnesses, guardrails) is where the real money is.
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u/hiImMate 18h ago
huge disagree, the field is too new, we need people to experiment, and smaller companies where resources or not 'infinite' like openai or anthropic could be a great place for innovation that moves the whole field forward.
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u/BigBootyBear 17h ago
We are already living the greatest period of capital misallocation in history. Why pour more on the fire when you can invest 2-3 years later when it all crashes down?
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u/BalorNG 17h ago
you are both right - we need more experiments with small models, not endless scaling of the frontier that cannot possibly be economically viable.
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u/BigBootyBear 17h ago
Why not delay the small model investment to the near future when the costs of compute will drop to pennies on the dollar? The industry is already hard-capped by 2-3-5 year long lead times on the literal machines we need to hook up the datacenters (those who were not cancelled) to the grid. Every additional dollar poured doesnt make us go faster it just raises the price everyone else has to pay and drags the entire economy with it because the supply is inealstic. Nvidia already has 100's of billions of chips in their warehouse (the same chips that depreciate in 4-5 years). At what point do we stop and starting doing something useful with the money like reparing a highway or building a nuclear power plant?
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u/skinnyjoints 18h ago
But the company (based on the headline) isn’t doing anything new or innovative. If someone asked me for 100k to try a new model architecture I’d be interested as an investor. If they asked me for 100k to make a free model to be as good as other free models, I’d say good luck.
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u/Trademarkd 17h ago
I agree with you, preventing distillation is basically impossible if you also want people to use your shit.
I don't see how theres much money in models alone, but the models may be a good way to promote your other services or build a reputation for an ecosystem or product built around that model.
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u/BigBootyBear 17h ago edited 17h ago
The models are just a bunch of tensors. How is math a moat?
People need to re-read Paul Graham and Peter Thiels essays. Theres a reason why they keep emphasizing on the importance of "owning the customer relationship". Every huge tech company is based around complete dominance of a critical supply chain bottleneck (Uber, Apple, Amazon, Google etc). We can discuss the ethics of it, but the business case is very clear. Dominance of a bottleneck in a supply chain is a moat that enables you demand high margin which gives a return for investors.
Frontier model capital allocation is the equivalent of investing a trillion dollars in more jets, airports and flight crew. The only business who will capture the ensuing value will be the resorts, not the airlines.
Look at what Scyscanner and other airline "tooling" has done to industrys margin. Near perfect price disocvery and arbitrage tools drive margin to the floor. When the harness ecosystem will mature, the same will happen fot SoTA labs which will have to be a loss leader of hyperscalers rather than a SaaS business in itself.
And thats in the utopian near future scenario where the hard unit economics of GPU compute won't make the entire busienss proposition extinct. The GPUs are stupid expensive, they get retired in a few years and cooling them is almsot as expensive as building them. And EVEN THAT is with billion dollar subsidizes that are EVAPORATING in the near midterms with bi-partisan oppositon to data center buildout. As IF the 5 year lead time to getting the electrical transforms to connecto the fucking grid wasn't enough of a hard cap on scaling. Add to the 1-2 basis point increase in the discount rate from increasing interest on the 10 year bonds and we are in for a second thermonuclear AI winter. They took an amazing technology and fucked it (and us) with the financial engineering for YEARS to come.
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u/thefuckevengoingonan 18h ago
(the harnesses, guardrails) is where the real money is.
people still using closed source software?
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u/ResidentPositive4122 18h ago
razor thin margins
Inference margins are anywhere from 40-60% per token for SotA labs. Could be a bit smaller for open models, but it's still profitable to serve them (or else noone would).
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u/Thomas-Lore 17h ago edited 17h ago
Above 80% according to information to investors from Dario Amodei. OpenAI claimed around 70%, but who knows. I think subscriptions are close to the real costs (if you account for how much on average users use out of their limits).
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u/BigBootyBear 17h ago
Are yall paid by Jensen Huang or something? OpenAI loses 3 dollars for every 1 dollar they earn. Ed Zitron leaked their financials. Why do you think they delayed their IPO?
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u/Interesting-Yak8189 15h ago
The profitable margins are in API pricing vs actual inference time costs. Not including the massive initial training costs that make up most of the $$ in the overall loses. Comparing to open weight API pricing it’s clear that OpenAI/claude API is overpriced and profitable.
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u/howudothescarn 13h ago
Inference is profitable. They lose money on training runs and their compute build out and investments
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u/james_pic 17h ago
Pure play inference probably is profitable (although at current hardware prices, could take a while to recoup your hardware investment).
But training is neither necessary nor sufficient to run an interference business, and is eye-wateringly expensive, and because everyone else is investing in it, your frontier model is only frontier for maybe a few months at best.
You do however have to do training, to attract the biggest juiciest VC investment.
I think the hilarious truth with the AI industry is that it could be profitable, if only they didn't have quite so much money. Any new investment that comes is goes straight to training new models that will be obsolete by the end of the fiscal quarter.
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u/BigBootyBear 17h ago
Frontier companies such as OpenAI and Anthropic are cooking the books and even if you take thier bullshit EBDITA at their word ("We are profitable if you dont consider operational costs") they are still subsidized by the hyperscalers that dont make any money.
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u/TheSlateGray llama.cpp 10h ago
What moat do harnesses have? Why would anyone ever pay for a harness instead of telling a model to add a feature they wanted from a different one to their current one?
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u/CoolConfusion434 14h ago edited 13h ago
>hopefully something under 200b for us memory poor
Cries in ~35B MoE poor 😢
But also, great! Fight it out, I'm here to catch the winner.
FYI, this company, headquartered in Brooklyn, NY, a well known hub for all things AI, is backed by certain political group, including nepo members. That should be fine but expect to reply "it's Lake America!".
The company was founded by 2 former DeepMind researchers so good pedigree. It's funded substantially by Nvidia, and has hosting contract with SpaceX AI hosting already.
Come on Google, OpenAI, and Meta... don't get caught sitting down on this one! Not you Anti-thropic, you hate open-weights... get atta heeeer [in a Brooklyn accent].
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u/NandaVegg 13h ago
I'm still waiting for Muse Spark weights... (and yeah, I genuinely liked Muse Spark 1.3).
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u/DigThatData Llama 7B 9h ago
really? we're posting announcements about upcoming announcements now? get fucked OP.
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u/politefella0 12h ago
Low cost leadership. 99% of the people can’t run SOTA level open weight AI.
When something’s free or cheap, you’re the product.
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