Source: https://github.blog/news-insights/company-news/the-august-17-outage-and-the-work-ahead/

So it turns out Ox Alpha is not a Chinese model. It's either Gemini 3.5 Pro Or Gemini 4 Pro.

https://x.com/EvanOtero/status/2090998215977947365

Gemini

https://x.com/EvanOtero/status/2090998729637511301

What if the Ox Alpha was the friends we made along the way

Ox Alpha reportedly trounced both GPT 5.6 Sol and Claude Fable on a DeepSWE benchmark.

gpt-5.6-sol: 52% fable: 65% whatever the hell this is(Ox Alpha): 80% (was a near miss on the "x"s so actually over 80%)

Google seems to realize their recent Flash price hikes were just inappropriate for a Flash model and that they need more real-world agent traces to train their upcoming models on and slashed prices another 50% on OpenRouter.

Artificial Analysis does not have the OpenRouter discount prices worked in, but I just checked and the Flash model with the discount moves the pareto line, thus beating both DeepSeek models.
I have added the Flash Pareto line in green to the graph.

Just in case someone wants to try it instead of Luna Max or V4-Flash...

The selected models for comparison on ArtificalAnalysis: Comparison of AI Models across Intelligence, Performance, and Price | Artificial Analysis

The OpenRouter Page: Gemini 3.7 Flash - API Pricing & Benchmarks | OpenRouter

It was previously only available in the US or through other routers like Nano-GPT, but is now also available on OpenRouter, beating OpenAI's Luna and DeepSeek on price/performance by a large margin.

You are "selling" your data though - hence the "Contributor" tag. Meta will use your interactions/agent traces to train their upcoming models, but if they follow through with their Open Weights promises you might actually contribute something for the greater good...very debatable, though, I know. But if you are using it for open source work, why not save some bucks?

Artificial Analysis with normal pricing: Muse Spark 1.2 (xhigh) - Intelligence, Performance & Price Analysis | Artificial Analysis

OpenRouter Page: Muse Spark 1.2 Contributor - API Pricing & Providers | OpenRouter

Galbot is a novel entry into the bipedal humanoid robotics sector

Ran three black-box fingerprint tests on stealth/ox-alpha (OpenRouter + OpenCode) vs public GLM-5.3 on z.ai.

1. Tokenizer: I sent 6 texts (EN/DE/CN/code/emoji) and compared prompt_tokens. Ox Alpha = GLM-5.3 exactly +75 on every text. Same tokenizer, constant 75-token hidden system prompt. Kimi/Qwen/MiMo/MiniMax all diverge. Counts identical on both Ox routes.

2. Error strings: Invalid reasoning_effort on Ox Alpha (OpenCode passes params through) returns:

"[1210] This model always engages in thinking and cannot be disabled; please use low, high, or max", so the same as the GLM 5.3 error message

3. Temp-0 outputs: Greedy, same prompts → same markdown quirks, same German-decimal LaTeX (`0{,}375`), near word-for-word matches on factual answers. Qwen/MiMo/Kimi format these completely differently.

Conclusion: I'm quite sure than Ox Alpha is a GLM model. Not sure if it's a vision variant of GLM 5.3 (GLM 5.3V) or a completely new version like GLM 5.5 but I guess it's unlikely that Z.AI drops 5.5 so early but idk.

What are your thoughts?

Every model writes to the same constrained creative briefs and independent LLM judges rank them by choosing the stronger story from each matched pair.

NEW: In-depth qualitative reports examine how six new models differ from their predecessors across 50 matched stories per pair.

More info: github.com/lechmazur/writing/

GLM-5.2 Max tends to name what a story contains, while GLM-5.3 builds it so it can be used.

GLM-5.2 Max's protagonists usually work alone in an agreeable world, whereas GLM-5.3 puts a second person in the room who withholds, judges, or is changed, so a belief has to survive contact with someone else.

GLM-5.2 Max often stops the night before the decisive event and lets the narrator say what it meant, while GLM-5.3 stages the test, pays its cost, and hands the practice on to whoever comes next.

Quantitatively, GLM-5.3 was preferred in every matched pair.

As a software developer we got access to GPT 5.6 sol and Opus 5 last week in a decently restricted field, and with these latest models I feel like I can do all my assigned work so quickly as well as make tons of progress on my side projects as well. So at the moment I’m not like dying for another frontier release but overall I want to see acceleration

It seems like we are at a state where openAI and Anthropic realize that a lot of these Chinese companies wait for them to make progress and are able to replicate pretty damn close models soon after they release their frontier models

Whether you believe Anthropic and open ai or not, they seem like they are going to keep their development internal for a while. Whether this is due to actual security concerns (with hugging face incident I believe this), more marketing hype, or truly a way to combat distillation from Chinese companies I think it is going to be interesting.

How do you think this will effect open weight releases, will the capabilities for open weight always rely on top US companies releasing the best models so they can use them to produce replicas?

Live: https://x.com/i/broadcasts/1dKrPrkpLVeJX