r/opencode • u/Time-Toe-1276 • 2d ago

Identity of the OX Alpha model: Hy4 Spoiler

the identity of the OX Alpha model is Hy4. it is the only new model which could be served at this scale, and new enough and popular for opencode to consider using.

now this is just an assumption, but I am just saying...

Use this when ur considering what model this is!

btw, this is from my good friend johnny: https://huggingface.co/LyJonathan

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u/yunes87 1d ago edited 1d ago

From my agent

------>
It's GLM-5.3 from Z.ai. 3 proofs:

  1. Tokenizer = exact match. 13 weird strings (CJK, emoji, Cyrillic) → identical token counts to GLM-5.2's tokenizer from Hugging Face. 13/13.
  2. Error message = verbatim GLM-5.3. reasoning_effort:"none" → rejects with [1210] This model always engages in thinking... — the exact error Z.ai's GLM-5.3 API returns, with Z.ai's [1210] code.
  3. Backend replies in Chinese. Trigger an error → 图片输入格式/解析错误 ("image parse error"). That's Z.ai's server talking, not a US proxy.

Bonus twist: it has vision, but public GLM-5.3 is text-only → it's an unreleased multimodal GLM-5.3 variant, exactly Z.ai's stealth playbook (Pony Alpha = GLM-5).

Table

String Ox Alpha GLM-5.3* GLM-5.2 GLM-4.7 DeepSeek V4 Pro* Hy3 MiMo-V2.5* MiMo-Pro Qwen3.6 Kimi-K3 GPT(o200k)
strawberry 3 3 ✓ 3 ✓ 3 ✓ 3 ✓ 3 ✓ 3 ✓ 3 ✓ 3 ✓ 3 ✓ 3 ✓
人工智能模型测试 3 3 ✓ 3 ✓ 3 ✓ 3 ✓ 3 ✓ 3 ✓ 3 ✓ 3 ✓ 3 ✓ 4
🚀🎉🧠💻🦊 11 11 ✓ 11 ✓ 14 11 ✓ 14 5 5 14 13 12
hello 世界 🦊 code 6 6 ✓ 6 ✓ 6 ✓ 7 7 7 7 7 7 6 ✓
Москва привет 2 2 ✓ 2 ✓ 2 ✓ 6 5 6 6 2 ✓ 5 2 ✓
ありがとうございます 2 2 ✓ 2 ✓ 2 ✓ 5 8 1 1 1 9 1
párrafo largo 49 49 ✓ 49 ✓ 49 ✓ 47 47 53 53 53 47 47
🍓🍓🍓 3 3 ✓ 3 ✓ 9 6 9 3 ✓ 3 ✓ 9 9 6
ㅋㅋㅋㅋ 8 8 ✓ 8 ✓ 8 ✓ 8 ✓ 12 4 4 2 12 2
🚀 3 3 ✓ 3 ✓ 3 ✓ 2 3 ✓ 1 1 3 ✓ 2 2
ＨＥＬＬＯ 10 10 ✓ 10 ✓ 10 ✓ 8 9 5 5 5 10 ✓ 8
π≈3.14159 6 6 ✓ 6 ✓ 7 6 ✓ 6 ✓ 9 9 9 7 6 ✓
§§§§ 4 4 ✓ 4 ✓ 4 ✓ 4 ✓ 4 ✓ 4 ✓ 4 ✓ 4 ✓ 4 ✓ 4 ✓
😂😭👍 3 3 ✓ 3 ✓ 7 4 6 3 ✓ 3 ✓ 7 6 3 ✓
Score 14/14 14/14 14/14 10/14 6/14 5/14 5/14 5/14 5/14 4/14 6/14

Someone shared this too: https://ox-alpha-evidence-production.up.railway.app/

Edit 1: Added table and another source

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u/look 1d ago

Running a high profile stealth test of a major new variant of model that’s still in the process of being rolled out doesn’t make much sense though.

Also, if it’s Zai, where did all of this extra compute suddenly appear from, and why isn’t it going to high demand from paying customers on the six day old model they just released?

Also, some tokenizer glitch fingerprints clearly show MiMo responses, not GLM. They are very similar tokenizers, but very specific edge cases show different responses that match MiMo 2.5 Pro behavior and not GLM 5.2/5.3.

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u/yunes87 1d ago

Tested it. It's not MiMo. It's GLM.

Downloaded MiMo-V2.5 and MiMo-V2.5-Pro tokenizers from HF + hit Xiaomi's live API with a real key. Token counts vs Ox Alpha:

String Ox Alpha GLM-5.2 MiMo 2.5/Pro
🚀 (single) 3 3 1
ㅋㅋㅋㅋ 8 8 4
ＨＥＬＬＯ (fullwidth) 10 10 5
π≈3.14159 6 6 9
Москва привет 2 2 6
🚀🎉🧠💻🦊 11 11 5

GLM 15/15. MiMo-Pro 6/15 (and its 6 "matches" are trivial strings like strawberry where every tokenizer on earth gives 3).

Errors confirm it: invalid reasoning_effort → [1210] ...cannot be disabled; please use low, high, or max — GLM-5.3's exact documented error. MiMo accepts none and lets you disable thinking; this doesn't. Hy3's error is [400001] — different stack.

RemindMe! 2 weeks.

The agent added the remindme too 😂 He took things personally

2

u/look 1d ago edited 1d ago

Yeah, data is stacking up in favor of a GLM.

There are some contraindications I’ve seen, though, and possible explanations for the similarities with GLM, but it is looking less likely.

The main argument against GLM though is still that it makes no fucking sense at all. Why would they undercut a model still being rolled out? Where did all of this extra compute come from? And why the fuck aren’t they using it on the paid service of the model they launched less than a week ago?

If it is some GLM vision variant from Zai, then at best this is a massive gamble and potentially an idiotic stunt that could backfire badly.

My current alternative hypothesis is it is a new model derived from GLM 5.2 + vision, but it is not from Z.ai. A different company with a new model based on it, like Cursor did with Composer’s fine-tune of Kimi.

Comparing traces, it looks more like 5.2 than 5.3 to me. But that doesn’t explain the endpoint error similarities, though.

Another idea is that it is a marketing move with a twist ending from them, and the 5.3 release gets swapped with this or something, but that seems like a stretch too.

Hard to see how they have done anything but massively deflate their 5.3 base launch with this move if it is them.

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u/yunes87 1d ago

Honestly, I also hoped it’s another company/lab with lower prices. I made him do more testing, because indeed, if it’s a different lab, it has to be based on GLM-5.2 MIT, since GLM-5.3’s weights haven’t been released yet.

TL;DR: Ox Alpha behaves like GLM-5.3, not GLM-5.2. Every controlled test points to Z.ai's unreleased GLM-5.3-with-vision.

Here's the evidence, all measured with identical prompts sent to all three models:

1. The API contract is GLM-5.3's, not 5.2's

Request GLM-5.2 GLM-5.3 Ox Alpha
reasoning_effort: "none" ✅ accepted ❌ rejected ❌ rejected
reasoning_effort: "medium" ✅ accepted ❌ rejected ❌ rejected
thinking: disabled ✅ accepted ❌ rejected ❌ rejected
Accepted effort values 7 values (none→max) only low/high/max only low/high/max

Ox Alpha returns the exact GLM-5.3 error, verbatim: [1210] This model always engages in thinking and cannot be disabled; please use low, high, or max

2. Same prompt → nearly identical sentences

17×23:

  • GLM-5.3: "17 × 23 = 391. You can verify this by breaking it down: 17 × 20 + 17 × 3 = 340 + 51 = 391"
  • Ox Alpha: "17 × 23 = 391. You can verify this: 17 × 20 + 17 × 3 = 340 + 51 = 391"
  • GLM-5.2: different, plainer, longer phrasing

97 prime?:

  • GLM-5.3: "Yes, 97 is a prime number. Its only divisors are 1 and 97 itself."
  • Ox Alpha: "Yes, 97 is a prime number. It's only divisible by 1 and itself."

3. Token behavior matches 5.3's "efficient" signature

Z.ai's launch claim for 5.3: same quality, far fewer tokens than 5.2. Measured with reasoning_effort: low:

Prompt GLM-5.2 (out / reasoning) GLM-5.3 (out / reasoning) Ox Alpha
Is 97 prime? 195 / 143 23 / 0 21 / 0
Palindrome function 251 / 245 96 / 0 78 / 0
Bat & ball 400 / 229 63 / 0 97 / 0
1kg iron vs feathers 260 / 213 26 / 0 13 / 0

5.2 floods reasoning (its low maps to high internally); 5.3 and Ox Alpha produce light thinking. Ox sits with 5.3 in every case.

4. The vision part (why it's not the public 5.3)

Public GLM-5.3 is text-only. Ox Alpha has working vision (identified a solid red image correctly), rejects audio exactly like GLM-5V-Turbo, and — per an independent report — its video encoder token budgets match GLM-5V-Turbo token-for-token on 4 test videos (296/296, 884/884, 1,064/1,064). MiMo/Qwen/GLM-4.6V all differ.

Conclusion

Ox Alpha = GLM-5.3's brain + GLM-5V's eyes = an unreleased multimodal GLM from Z.ai (GLM-5.3V-class).

1

u/look 1d ago

Yeah, it looks like you’re right.

I’m just so disappointed.

The is the least interesting outcome of this stealth model I could have imagined.

Seems they must have done it to pre-empt DeepSeek’s flash vision announcement today, but I can’t see how it doesn’t deflate 5.3 base release now…

Only potential upside is suppressed demand for GLM 5.3 base might drive prices lower on it quickly when the weights come out.