1T-param coder hitting 90% HumanEval, 1M+ context, open-sourced—and it fits on consumer GPUs. Mid-Feb drop incoming.
Tired of cloud bills killing your coding agent experiments? DeepSeek V4 promises to fix that with consumer-grade power.
Nathan Benaich’s State of AI newsletter buzzes about DeepSeek V4, slated for mid-February release: a 1-trillion parameter coding model with Engram memory for 1M+ token context. Claims 90% on HumanEval, topping Claude and GPT-4. Crucially, it’s engineered for dual RTX 4090s—open-source vibes strong, per patterns from prior DeepSeek drops.[2]
Devs, this rewrites local inference. Train/fine-tune massive coders without H100 farms. Pairs with V3/R1’s reasoning wins in coding/clinical tasks. Real workflow boost: longer contexts mean full-repo analysis, fewer API calls.[2][1]
Vs. proprietary: GPT-4o/Claude cap at lower scores; closed inference hikes costs. DeepSeek’s MoE efficiency (like V3’s $6M train) democratizes frontier coding AI. Nvidia/Eli Lilly’s $1B lab hints at hardware-pharma convergence, but DeepSeek keeps it accessible.[2]
Prep your rigs—download expected soon. Test on HumanEval forks, integrate into VS Code. If it delivers, does this kill SaaS coding tools?
Source: Nathan Benaich Substack