Ox Alpha Scores 63 Percent on DeepSWE Subset
Posts discuss Ox Alpha results on DeepSWE benchmark and comparisons to other models.
A retweet from @theo shares @winkey_h noting Ox Alpha reached around 63 percent at 47K average output tokens on a DeepSWE subset, calling the result pareto optimal. A quote from @kimmonismus states that @davis7 fully tested Ox Alpha on the DeepSWE set, with overall performance described as more or less on par with GPT-5.6 Sol mid. The same post speculates the model may be GLM-5.3 Flash capable of local runs on hardware such as a DGX Spark. One generated headline in the packet refers to Ox Alpha as a stealth model from Opencode with 1M context length and multimodal support.
Combined views
547.3K
5 posts, first seen 3d ago
Reactions from ranked influencers
5 posts
Ok ox-alpha has that big model smell I'm getting around 63% at 47K avg output tokens on a DeepSWE subset This is pareto optimal amongst open models and just shy of Grok 4.6 compared to closed models!
Ox Alpha (stealth model) is free for the next week - 1M Context - Multi-modal - Zero Data Retention Generous rate limits, near unlimited usage We have capacity for 100T tokens per day, lets see what you can do
Ox Alpha has now been fully tested against the DeepSWE set by @davis7 . Overall, it's performing more or less on par with GPT-5.6 Sol mid. But he makes a good point. If it really is GLM-5.3 Flash that's now performing at the level of 5.6 Sol mid and could run locally on a DGX…
Actual DeepSWE run on the ox alpha mystery model is done. Ended at ~63% NOT the 80% my first subset test got, which makes way more sense. I've been using this thing a ton and it is definitely a very good model. - Much better "voice" than Claude or GPT - Decent design - Handles…
alternative results I think 60-61% is realistic
Actual DeepSWE run on the ox alpha mystery model is done. Ended at ~63% NOT the 80% my first subset test got, which makes way more sense. I've been using this thing a ton and it is definitely a very good model. - Much better "voice" than Claude or GPT - Decent design - Handles…
lot of guesses on what ox alpha is but they are all wrong, kinda disappointed so just going to tell you ox alpha is a new kind of llm that recursively updates a persistent latent state instead of reasoning entirely through tokens this lets internal representations converge…
ox is incredible for a relatively new category of model: long-horizon small subagent. It's meticulous, proactive, and smart, but not very ambitious. it tries to carefully solve tasks on the job it's dispatched to. Forward deployed janitor with a Ph.D GLM 5.5 will drive it hard
