Ox Alpha scores 63% on DeepSWE benchmark with mixed user feedback
AccBalanced · x · 2026-08-23
Developer @davis7 ran the DeepSWE benchmark on the mysterious Ox Alpha model, resulting in a 63% score, comparable to DeepSeek V4 Pro and Grok 4.6. Hands-on reviews highlight its superior "voice" and design over Claude/GPT, along with strong handling of sub-agents and complex coding tasks. However, users noted issues like leftover dead code and significant latency at higher reasoning levels. If it is a small open-weight model (like GLM) with low compute needs, it offers insane value.
Related event: Ox Alpha scores 63% on full DeepSWE, debunking earlier 80% claim(6 posts)→
More from Models
- Decoding OpenCode's Mystery Model: 600 Calls Confirm It as GLM-5 — zainhas · 2026-08-23
- Qwen3.8-27B GGUF Release with Speculative Decoding Support — z-lab · 2026-08-23
- MiniMax H3's high prompt adherence creates stiff, frozen videos lacking subtle motion — DifficultAd5938 · 2026-08-23
- Princeton's i1: A fully open text-to-image model backed by 300 controlled experiments — 机器之心 · 2026-08-23
- AI models exhibit 'Fablish' writing quirks: garbled negations and OSV word order — alexisgallagher · 2026-08-23
- Hands-on: Terra beats Sonnet, Flash unmatched on speed and quality — cgarciae88 · 2026-08-23