The Free Open Model Matching GPT-5.5 on Agentic Coding

2026-06-12 · Source: Towards AI - Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, quick

Summary

Nex-N2-Pro, a new free, open-weights agentic model from the Shanghai Innovation Institute-backed Nex-AGI alliance, has been released. This Apache-2.0 open-weights Mixture-of-Experts (MoE) model reports a 58.8 on SWE-Bench Pro, narrowly outperforming GPT-5.5's 58.6. Available for free on OpenRouter until June 23, Nex-N2-Pro offers a 262K context window, image input, function calling, and reasoning capabilities. Its weights, based on Qwen3.5, are accessible on Hugging Face and ModelScope. The launch showcases its agentic work through demos like Deep Search, Terminal Agent, OpenClaw, Web Building, and Math Reasoning, with exposed reasoning traces.

Key takeaway

For AI Engineers running coding agents, Nex-N2-Pro presents a compelling, free-to-try alternative that matches GPT-5.5's agentic coding performance on SWE-Bench Pro. You should test this Apache-2.0 open-weights MoE model, available on OpenRouter until June 23, to evaluate its 262K context, image input, and function calling capabilities for your specific workflows. This limited-time opportunity allows you to assess a top-tier open model without cost.

Key insights

Nex-N2-Pro, a free open-weights model, matches GPT-5.5's agentic coding performance on SWE-Bench Pro.

Principles

• Open-weights models can rival closed-source leaders.
• Agentic coding benchmarks validate model capabilities.
• Transparent reasoning traces enhance model trust.

Method

The article describes how Nex-N2-Pro's agentic work is demonstrated via demos like Deep Search, showing web searches, page visits, and synthesis with citations.

In practice

• Test Nex-N2-Pro for agentic coding tasks.
• Utilize 262K context for complex problems.
• Explore image input and function calling.

Topics

• Agentic Coding
• Open-weights Models
• Nex-N2-Pro
• SWE-Bench Pro
• Mixture-of-Experts
• Function Calling

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Scientist, Machine Learning Engineer, AI Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by Towards AI - Medium.