KOL predicts DeepSeek V4.1 Pro may not beat Flash, blaming RL budget over pretraining
teortaxesTex · x · 2026-10-18
@teortaxesTex echoes @laopai1990's "bold prediction" that DeepSeek V4.1 Pro might score worse reception than V4.1 Flash-1017. His reasoning: not a pretraining issue, but that Pro is capped by RL budget, environment quality, and distilled data — the bottleneck lies in post-training rather than the base model. The quoted post adds that Flash set expectations so high that Pro risks disappointing. (Unverified speculation.)
More from Models
- User: GPT-5.5 is stronger but acts without approval, while GPT-5.0 understood intent better — PawelHuryn · 2026-10-18
- Muse Spark runs on a single Mac Studio M3 Ultra at 18 t/s decode — challis88ocarina · 2026-10-18
- Kaggle LLM attribution contest: GLM text is flagged as Claude 44% of the time — HarveenChadha · 2026-10-18
- Google's Gemini deletes all chat history if you turn off data sharing — cyber_red0028 · 2026-10-18
- Gemini 4 Argon scores 20.2% on agentic WeirdML v3 benchmark, between Claude models — scaling01 · 2026-10-18
- Reddit thread crowdsources the real failure modes of frontier coding models like Opus 5.5 and GPT-6 — SadPossibility2338 · 2026-10-18