NEW Tencent Hy3 is here for FREE!

2026-07-15 · Source: 1littlecoder · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Robotics & Autonomous Systems · Depth: Intermediate, long

Summary

Tencent Hy3, a new Mixture of Experts (MoE) large language model, has rapidly gained prominence, ranking number one on Open Router's LLM usage leaderboard by serving over six trillion tokens. This 295 billion parameter model, with only 21 billion active parameters, offers high inference speed and throughput, making it suitable for agentic coding and development. Available for free on Open Router until July 21st, Hy3 is also open-source under an Apache 2.0 license, allowing local deployment. It features a 256,000 context window and text-to-text modality. Benchmarks show Hy3 outperforming models like Deepseek V4 Pro and competing closely with larger models such as GLM 5.2 and Claude Opus, scoring 71.7% on Terminal Bench 2.1 and 57.9% on Sweep Bench Pro, highlighting its strong agent capabilities.

Key takeaway

For AI Engineers or Prompt Engineers developing agentic applications, Tencent Hy3 offers a compelling, cost-effective solution. Its MoE architecture with 21 billion active parameters ensures high throughput for complex coding tasks and artifact generation. You should explore Hy3 on Open Router for free until July 21st, or integrate it into your Open Code environment to leverage its strong benchmarked agentic capabilities for your next project.

Key insights

Tencent Hy3, an efficient MoE LLM, excels in agentic coding with high performance and strong benchmarks against larger models.

Principles

• MoE architecture enhances inference speed and throughput.
• Agentic workflows benefit from high-performance LLMs.
• Benchmarks like Terminal Bench 2.1 validate agentic capabilities.

Method

To use Hy3 for agentic coding, access it via Open Router's API or integrate it into environments like Open Code by configuring the API key.

In practice

• Generate complex HTML/CSS/JavaScript applications with agentic prompts.
• Create functional 2D simulation games from single HTML files.
• Develop launch trailers using third-party libraries like Hyperframes.

Topics

• Tencent Hy3
• Mixture of Experts
• Large Language Models
• Agentic AI
• Open Router
• Code Generation
• LLM Benchmarks

Best for: AI Engineer, Machine Learning Engineer, Prompt Engineer

Related on AIssential

• tencent/Hy3 — Tencent's Hy3 MoE model delivers competitive performance against much larger models while maintaining a more efficient active parameter count.
• TencentCloud / TencentDB-Agent-Memory — Layered and symbolic memory architectures significantly boost LLM agent efficiency and task success.
• Tencent HY3 IS REALLY GOOD! Best Open-Weight Model? (FULLY FREE) — Tencent's HY3 is a 295B MoE model offering competitive performance against larger models at a lower cost, especially for coding and creative tasks.
• How to Access and Use Qwen3-Coder-Next? — Qwen3-Coder-Next is an open-weight, agentically trained coding model optimized for local execution and low inference costs.
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• INTELLECT-3.1 Brings Open-Source RL Reasoning to 106B MoE Scale — INTELLECT-3.1 is a 106B MoE model optimized with RL for advanced reasoning, coding, and agentic tasks.

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Editorial summary, takeaway, and curation by AIssential. Original article published by 1littlecoder.