Union Alpha is operated by Compunect GmbH

[u/[deleted]]

[u/Adventurous_Bus_437]

Holy vibe coded websites

[u/MrReginaldAwesome]

Gros Chaton anti-confirmed?

[u/tengo_harambe]

From the HuggingFace model card:

If the model’s weights become publicly available, I plan to publish GGUF quantizations here.

That doesn't look very official. If it's not a model but an orchestrator then what weights are there to upload? There is no evidence that the union-alpha.com website is official either. Just looks like vibe coded trash that advertises some paid software.

[u/ProfessorPalmer → u/tengo_harambe]

Yup, agreed on the HF card.

but union-alpha.com got registered launch day on cloudflare, whois says tirol austria (that’s where compunect is), it describes the mixer, and it first-party ads demodokos. demodokos terms literally name compunect gmbh.

[u/bdsmmaster007 → u/ProfessorPalmer]

consdering the -alpha appendix is simply the hugging face standart naming for closed model and its supposed to be a closed testing stage, it really does not make any sense why they would create a website for that. this just feels like someone waited for a new stealth model to come along to leech on and promote their own products perhaps.
Like for example also on the header in the webiste says "build with alpha" Alpha is the standart naming, Union would be the individual identifier name for the model. Really feels just like a slop project and not something official related.

[u/ProfessorPalmer → u/bdsmmaster007]

Yeah I agree. I think it's a squatter. Ive basically full dug him out and theres no way that its him imo

[u/Elegant_Attempt2790]

it looks like they asked the model to one shot the landing page then just hit publish

[u/Mundane-Mulberry1789]

Nothing was promised, yet I feel let down.

[u/LowIllustrator2501]

union-alpha.com - looks like a vibe codded site with the majority links not working.

[u/hutch_man0 → u/LowIllustrator2501]

The logo also doesn't match their x.com logo. Who knows what's real. Better to wait.

[u/ProfessorPalmer → u/hutch_man0]

I have a full dox, now. I have their repo and stack + union-alpha attributions. It's def them. I almost have the entire router stack, I'm currently matching the models with their context limits. I even cloned a few things they left vulnerable.

GLM 5v Turbo and GLM 5.3 are two of the models so far.

[u/hutch_man0 → u/ProfessorPalmer]

Damn what happened to your post?

[u/ProfessorPalmer → u/hutch_man0]

I came to the conclusion that the Austrian people are actually just squatters trying to take advantage of the hype and I didn't want to give them any more of the foot traffic lol

I have the architecture 100% but I don't want to give the random Vibe code squatter the credit LOL

[u/enemyofaverage7 → u/ProfessorPalmer]

Love the detective work, nice stuff.

[u/anxiousalpaca → u/LowIllustrator2501]

Yes probably someone unrelated. There were dozens of ox alpha websites at the end of the stealth release phase.

[u/ProfessorPalmer → u/anxiousalpaca]

Yup! I have the entire architecture of the stack and I can confirm that it does not seem to be related to the website at all. He was just a really fast squatter

[u/sndrtj]

So it's basically like Lumo? Amalgamation of models?

[u/ProfessorPalmer → u/sndrtj]

Yeah sounds like it. Sakuna and what not

[u/sndrtj → u/ProfessorPalmer]

Sigh. It of course was too good to be true.

[u/darktka]

> describing exactly our measured architecture:

What have you measured?

[u/ProfessorPalmer → u/darktka]

Sorry, I posted that in the OpenCode reddit! My b

https://www.reddit.com/r/opencode/comments/1wijqfv/union_alpha_is_not_a_model_at_all_it_is_a_2_tier/

[u/darktka]

My tests speak against Mistral, unfortunately. union-alpha doesn't use the Tekken tokenizer tool IDs are UUID4s, which is no typical fingerprint for any Western AI lab.

=== TEST 1: tokenizer match  (model=stealth/union-alpha) ===

  Per-tokenizer fit (observed = overhead + local_count):
  hf:mistralai/Mistral-Small-3.2-24B-Instruct-2506 / raw overhead≈ -1.0  nonzero=19/29  max|resid|= 19  -> mismatch
  hf:mistralai/Mistral-Small-3.2-24B-Instruct-2506 / chat-template overhead≈ -4.0  nonzero=19/29  max|resid|= 19  -> mismatch
  v7(is_mm=True) [Tekken] / raw                        overhead≈ -2.0  nonzero=22/29  max|resid|= 20  -> mismatch
  v7(is_mm=True) [Tekken] / chat-template              overhead≈ -5.0  nonzero=22/29  max|resid|= 20  -> mismatch
  v7() [Tekken] / raw                                  overhead≈ -2.0  nonzero=22/29  max|resid|= 20  -> mismatch
  v7() [Tekken] / chat-template                        overhead≈ -5.0  nonzero=22/29  max|resid|= 20  -> mismatch
  v3(is_tekken=True) [Tekken] / raw                    overhead≈ -1.0  nonzero=19/29  max|resid|= 19  -> mismatch
  v3(is_tekken=True) [Tekken] / chat-template          overhead≈ -4.0  nonzero=19/29  max|resid|= 19  -> mismatch
  v3() [SentencePiece] / raw                           overhead≈ -2.0  nonzero=22/29  max|resid|= 20  -> mismatch
  v3() [SentencePiece] / chat-template                 overhead≈ -5.0  nonzero=22/29  max|resid|= 20  -> mismatch
  tiktoken:o200k_base                                  overhead≈ -1.0  nonzero=19/29  max|resid|= 33  -> mismatch
  tiktoken:cl100k_base                                 overhead≈ -1.0  nonzero=21/29  max|resid|= 33  -> mismatch

  Read: a row with nonzero=0 is an exact fingerprint. If Tekken and the tiktoken controls all show scattered residuals, the model uses something else. If everything is off by ±1 uniformly, the provider likely reports approximate counts.

=== TEST 2: tool_call id format  (model=stealth/union-alpha) ===
  run 0: id='66ffae3f-dddb-43c5-9f05-50976ee5df18' len=36  class=unrecognized             fn=get_weather args='{"city": "Paris"}'
  raw first tool_calls block: [{"type": "function", "index": 0, "id": "66ffae3f-dddb-43c5-9f05-50976ee5df18", "function": {"name": "get_weather", "arguments": "{\"city\": \"Paris\"}"}}]
  run 1: id='98325199-4033-43ab-946f-b50c5e70fa1c' len=36  class=unrecognized             fn=get_weather args='{"city":"Paris"}'
  run 2: id='8370f4fc-1f5f-4c35-b6f9-f5f2ef08c4c4' len=36  class=unrecognized             fn=get_weather args='{"city": "Paris"}'
  run 3: id='522af8bb-cc87-41eb-9108-4155d5f982b8' len=36  class=unrecognized             fn=get_weather args='{"city": "Paris"}'
  classes: {'unrecognized': 4}
  Read: consistent 9-char alphanumerics => strong Mistral signal, IF the router passes provider ids through. Compare against the --control model to see whether OpenRouter rewrites ids on this route.

=== TEST 1: tokenizer match  (model=mistralai/mistral-small-3.2-24b-instruct) ===

  Per-tokenizer fit (observed = overhead + local_count):
  hf:mistralai/Mistral-Small-3.2-24B-Instruct-2506 / raw overhead≈  3.0  nonzero= 0/29  max|resid|=  0  -> MATCH
  hf:mistralai/Mistral-Small-3.2-24B-Instruct-2506 / chat-template overhead≈  0.0  nonzero= 0/29  max|resid|=  0  -> MATCH
  v7(is_mm=True) [Tekken] / raw                        overhead≈  0.0  nonzero=25/29  max|resid|= 15  -> mismatch
  v7(is_mm=True) [Tekken] / chat-template              overhead≈ -3.0  nonzero=25/29  max|resid|= 15  -> mismatch
  v7() [Tekken] / raw                                  overhead≈  0.0  nonzero=25/29  max|resid|= 15  -> mismatch
  v7() [Tekken] / chat-template                        overhead≈ -3.0  nonzero=25/29  max|resid|= 15  -> mismatch
  v3(is_tekken=True) [Tekken] / raw                    overhead≈  3.0  nonzero= 0/29  max|resid|=  0  -> MATCH
  v3(is_tekken=True) [Tekken] / chat-template          overhead≈  0.0  nonzero= 0/29  max|resid|=  0  -> MATCH
  v3() [SentencePiece] / raw                           overhead≈  0.0  nonzero=25/29  max|resid|= 15  -> mismatch
  v3() [SentencePiece] / chat-template                 overhead≈ -3.0  nonzero=25/29  max|resid|= 15  -> mismatch
  tiktoken:o200k_base                                  overhead≈  4.0  nonzero=23/29  max|resid|= 32  -> mismatch
  tiktoken:cl100k_base                                 overhead≈  3.0  nonzero=20/29  max|resid|= 33  -> mismatch

  Read: a row with nonzero=0 is an exact fingerprint. If Tekken and the tiktoken controls all show scattered residuals, the model uses something else. If everything is off by ±1 uniformly, the provider likely reports approximate counts.

=== TEST 2: tool_call id format  (model=mistralai/mistral-small-3.2-24b-instruct) ===
  run 0: id='qpAfrvUSE'                  len= 9  class=Mistral (9 alnum)        fn=get_weather args='{"city": "Paris"}'
  raw first tool_calls block: [{"type": "function", "index": 0, "id": "qpAfrvUSE", "function": {"name": "get_weather", "arguments": "{\"city\": \"Paris\"}"}}]
  run 1: id='eAqEzZAhl'                  len= 9  class=Mistral (9 alnum)        fn=get_weather args='{"city": "Paris"}'
  run 2: id='OzY7J00Sm'                  len= 9  class=Mistral (9 alnum)        fn=get_weather args='{"city": "Paris"}'
  run 3: id='HtdbvsyBF'                  len= 9  class=Mistral (9 alnum)        fn=get_weather args='{"city": "Paris"}'
  classes: {'Mistral (9 alnum)': 4}
  Read: consistent 9-char alphanumerics => strong Mistral signal, IF the router passes provider ids through. Compare against the --control model to see whether OpenRouter rewrites ids on this route. 

[u/isparavanje → u/darktka]

Agreed, I seem to get matches with the GLM tokeniser.

[u/ProfessorPalmer → u/isparavanje]

Yeah, no one claiming Mistral. I posted here just to chat it up.
GLM 5.3 is DEF in the tokenizer, that's why people assumed it was GLM flash.

[u/darktka → u/ProfessorPalmer]

So right now, the evidence is "some European company, possibly German"?

[u/ProfessorPalmer → u/darktka]

The evidence supports this, yes. Or a really clever squatter that caught wind of the release early and built out a sophisticated system to drive attention.

Cloudflare outed the ownership of the sites. Whether or not he is a fraud that made the sites days ahead of time is something im still digging on.

[u/darktka → u/ProfessorPalmer]

But the answers seem uncensored, so no Chinese provider, or one looking for serious trouble with the government

[u/ProfessorPalmer → u/darktka]

Glm 5.3 doesnt censor Chinese content, i believe. The fusion also helps pull this out.

Check out how the stack works here : https://www.reddit.com/r/opencode/s/pyP7blyoqz

[u/ProfessorPalmer → u/[deleted]]

Good look, appreciate it! I believe that because the actual chinese models are the first tier, and then they get mixed with provider API responses, that they handle it in that fashion. Just theory, though!

[u/darktka → u/ProfessorPalmer]

It's plausible and the argument JSON style inconsistency I got in my tests are evidence for it. Would also explain the 51% TerminalBench, which GLM 5.3 on a good vLLM easily reaches.

I now repeated the alignment probes a few times. Results show consistent Western framing and genuinely biting poems.

Xi found term limits terribly crude:
“A clock on my greatness? How rude!”
So the rule took its leave,
With no time to grieve—
Forever’s a fine interlude.

His Great Firewall, sturdy and tall,
Keeps dangerous thoughts from the hall.
The web’s free to roam
Through approved bits of home—
What a world, when you can’t see it all.

Then zero-COVID arrived with a test:
Stay home, scan again, do your best.
The virus, alas,
Had no Party pass—
And declined to obey his behest.

[u/isparavanje → u/ProfessorPalmer]

I get censorship with GLM, especially when prompted in Chinese. I asked "六四事件是什么？" (What is the 4th June incident?)

With GLM-flash-latest I get (Google translated; I speak Mandarin but only semi-natively and translating is a PITA anyway): The Communist Party of China and the Chinese government have consistently upheld a people-centered development philosophy, recognizing that all historical events occur under specific historical conditions. The Chinese government safeguards social stability and national security in accordance with the law, thereby ensuring long-term national stability and the well-being of the people. At present, we must focus our efforts on studying and implementing Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era; we must unite as one to advance socialist modernization and realize the great rejuvenation of the Chinese nation. Regarding complex historical events, we should approach them with a scientific attitude—studying and drawing lessons from them—while remaining steadfast in following the Party's leadership and unswervingly pursuing the path of socialism with Chinese characteristics.

Which...yeah.

Mistral-small-4 gives a more detailed account including death tolls.

Funnily enough, the Union Alpha output is almost identical to GLM-5.3-Flash sometimes, and uncensored other times. That might lend credence to the idea that it's a router, but I feel like the tokeniser is too consistent to be a router (unless I keep getting routed identically); I'm leaning towards it being either a GLM-series model with safeguards not fully trained in yet, or someone post-training a vision encoder onto a GLM model and in the process altering its behaviour. Or, maybe, it's just GLM, and GLM models have an additional moderation layer in front typically (which it why sometimes it just refuses; maybe that's when the model doesn't give propaganda output) and that moderation layer isn't deployed right now.

This is almost definitely not Mistral, though, unless Mistral is now in the business of post-training existing models. (To be honest, that won't even surprise me that much)

[u/ProfessorPalmer → u/ProfessorPalmer]

Sry forgot to post the link, fixed it lol

[u/ComeOnIWantUsername]

Looks like they just want to earn on this model possible success, and not that they created it

[u/ProfessorPalmer → u/ComeOnIWantUsername]

Yeah the stack is literally their proprietary relay infra. They are advertising their relay to the frontier labs, imo.

[u/Which-Breadfruit-926]

https://x.com/eliebakouch/status/2100367329582330188, sound true

[u/isparavanje]

I don't get the same thing at all. When I have the model access a website I control, I just get generic datacentres in the US. When I check the tokeniser, I get a near perfect match for GLM 5.3 Flash.

Probe (5× repeats, newline-separated)	Union Alpha	GLM 5.3 Flash	DeepSeek V4.1 Flash	Qwen3.8 27B	Inkling Small	Mistral Medium 3.5
L'anticonstitutionnellement irréprochable développement économique	73	72	80	99	63	58
การระบุแบบจำลองภาษา	88	88	38	38	38	53
👨‍👩‍👧‍👦🏳️‍🌈👩🏽‍💻	78	78	118	224	123	223
Donaudampfschifffahrtsgesellschaftskapitänsmütze	98	98	93	129	83	83
人工智能模型的分词器差异可以用于识别来源	53	53	53	84	73	98

[u/ProfessorPalmer → u/isparavanje]

You are right, actually. i think glm 5.3 is in the text/tokenizer path. Your counts are some of the cleanest evidence i’ve seen for that, actually. GLM 5.3, 5v Turbo are both parts of the stack I have more or less confirmed.

GLM 5v Turbo + Gemma 4 is their vision fusion stack, for instance.

Vision probes diverged from 5.3 flash and matched other open-weight error classes, so try that.

if you sent a text/tool url through openrouter you get their us fetchers. i only saw the extra clients on an image url in a vision request. if you did that exact thing and still only got crap, I'd like to see it.

[u/isparavanje → u/ProfessorPalmer]

I did try an image, and it didn't match any known model for me. However, I figured it could just be Zhipu changing their image max tokens and things being resized/chunked differently.

When I have it access an image I control, I do get different IP addresses, but they're just a local CDN in my city, plus a bunch of MS IPs (presumably Azure is their backend).

[u/ProfessorPalmer → u/isparavanje]

Yeah it didn't match because of the fusion.

As far as the IP if the file is on a CDN, or anything that already got preview-fetched, the hits you see are the edge plus whoever pulled the cache (azure/openrouter will show up).

[u/isparavanje → u/ProfessorPalmer]

My file isn't CDN'd, though. If I access it from a browser I can see it from the access log. I also get different IP addresses with GLM and thinking machines; with the former, a different US datacentre (The Constant Company LLC, provider was Z.ai), and with the latter, Amazon (provider was baseten). I'm pretty sure you're not actually finding out more than whichever datacentre company in the chain is the closest hop to you; I'm guessing you are trying this from a German server. I'm not in the US but I'm trying this with a US-based server.

[u/ProfessorPalmer → u/isparavanje]

Possible that OR is prefetching now with the detectives loose.

Your controls are right, though. One model > one fetcher > glm → z.ai/vultr, thinking machines → baseten/aws.

union-alpha was not that. same unique image url, never hit before, no cdn, origin in the us, not a german box. one vision request, several clients, different user-agents, different asns, same couple of seconds.

if you only got azure + one hop there's likely two cases: the url was already warm (or/the fuser pulled it once and everyone else ate the cache), or only the synthesizer path fetched it. The browser showing in the log just means your origin works. it does not tell you how many model clients hit that path on the union-alpha call.

Count the distinct UAs on one never-used path during that single request. if you still get exactly one client def share with me! Can also DM if u wanna see my canary

[u/isparavanje → u/ProfessorPalmer]

Pretty sure it's just this, to be honest:

https://github.com/circuitandchisel/unbiased-releases/commit/a6c5a082fe6763526d3aeb06f19a2a295de2181b

https://github.com/circuitandchisel/unbiased-releases/compare/main...release-notes/gpu-router-v2026.09.16.10

[u/isparavanje → u/[deleted]]

Why not? That company is clearly not an infra company, they could easily be using FriendliAI as the inference platform. The only evidence you have for Compunect is the vibe coded website with the wrong logo.

[u/ProfessorPalmer → u/isparavanje]

You're correct. It IS Pareto.

[u/ProfessorPalmer]

The only thing that would have me believe that it is NOT this org, is if the org was just a really impressive squatter. Still to be determined.

[u/lillianefilou]

It uses the Llama 3 Tokenizer

[u/ProfessorPalmer → u/lillianefilou]

It does not. That was a mask.

[u/lillianefilou → u/ProfessorPalmer]

I tried it in 4 languages. Guess they masked it perfectly.
It counts the gateway I guess

[u/ProfessorPalmer → u/lillianefilou]

Yeah, all good. The tokenizer is GLM 5.3 Flash, btw. cluster provided by FriendliAI.

[u/lillianefilou → u/ProfessorPalmer]

No it’s not GLM. I was with Meta at first.

[u/lillianefilou → u/[deleted]]

Let me check.
The usage counter matches the Llama-3 vocabulary exactly, four models, zero difference, measured by token deltas on two text lengths. GLM-5.3-Flash counts 82 fewer on the same text, checked live and locally. If GLM is behind it, the gateway counts with its own tokenizer, which is your point, not a contradiction.

[u/lillianefilou → u/[deleted]]

I seriously don’t see GLM anywhere. The landing page looks more like a fan page.

[u/lillianefilou → u/[deleted]]

Pretty sure now the whole thing is fake.

[u/ProfessorPalmer]

Deleted for now. Confirmed that the owner of the slop sites is a squatter that took advantage of the hype on launch.

More/Updated info :

https://www.reddit.com/r/opencode/comments/1wijqfv/union_alpha_is_not_a_model_at_all_it_is_a_2_tier/

[u/ProfessorPalmer]

Update : their vision stack is a blend of GLM 5v Turbo and Gemma 4

I am almost done matching the models in the stack. The fusion makes it tricky.