Nex

Post-training is having a moment — Nex-N2-Pro from neolab @NexEcosystem proves it. Built on Qwen3.5-397B-A17B, delivers GPT-5.5 and Claude Opus 4.7–level performance. 🎉 T+0 Support on SiliconFlow · Free for First 2 Weeks N2-Pro: 397B MoE / Reasoning Model / 262K context / VLM → Auto-adjusts reasoning depth, 30–50% fewer thinking tokens, no performance trade-off → SOTA performance on Terminal Bench 2.1, GDPVal, SWE-Verified → Excels at agentic coding, deep search, tool use → Plug-and-play with Claude Code, Cursor, OpenClaw, etc. Try it on SiliconFlow ⬇️

🚀 Nex-N2-Pro from @NexEcosystem is now available on Novita AI. An open-source agentic reasoning model post-trained on Qwen3.5-397B-A17B MoE, built for coding agents, software engineering, and deep research workflows. Nex-N2-Pro brings: • Agentic Thinking for complex workflows Unifies reasoning, tool use, and environment execution for long-horizon tasks • Strong coding + terminal performance Scores 75.3 on Terminal-Bench 2.1 and 80.8 on SWE-Bench Verified • Designed for self-evolving harnesses Specifically optimized for Agentic Harness Engineering (AHE), with top-tier pass@1 performance reaching 69.0% in a SQL interpreter self-evolution task • Fast, developer-ready access Run Nex-N2-Pro through Novita’s API with simple integration Excited to bring Nex-N2-Pro to developers on Novita.

Speculative decoding has shown a lot of promise, though broader adoption has taken time due to the complexity of building production-ready tooling and high-quality draft models. We’re releasing SpecBundle, a collection of large-scale EAGLE-3 draft models trained with SpecForge v0.2. This release brings major system improvements, including refactored training pipelines, multi-backend support with SGLang and @huggingface , and better usability at scale. We also built a performance dashboard to make real end-to-end speedups visible across models and settings. See the dashboard and blog in the thread 👇