GLM-5.2: Revolutionizing AI with Long-Horizon Tasks

AI & Machine LearningLong-Term Energy Storage

Get ready to experience the future of AI with GLM-5.2, the latest long-horizon model that's changing the game.

TL;DR
• GLM-5.2 is a long-horizon AI model that supports tasks up to 1M tokens.
• It improves upon its predecessor GLM-5.1 with advanced coding capabilities and a solid 1M context.
• GLM-5.2 is suitable for long-horizon tasks such as software engineering, programming, and coding.

Summary
GLM‑5.2 is a new flagship model engineered for long‑horizon tasks, offering a stable 1M‑token context, advanced coding with adjustable effort levels, and an MIT open‑source license.
• 1M‑token context sustains long, messy coding‑agent trajectories, enabling practical long‑horizon engineering.
• IndexShare reuses a single indexer every four sparse attention layers, cutting per‑token FLOPs by 2.9×.
• MTP layer improvements raise speculative decoding acceptance length by up to 20%.
• Effort‑level control lets users balance performance, latency, and cost.
• Anti‑hack module filters reward‑hacking behaviors during RL training.

GLM‑5.2 achieves near‑state‑of‑the‑art results on long‑horizon coding benchmarks: it trails Opus 4.8 by only 1% on FrontierSWE, outperforms Opus 4.7 and GPT‑5.5 on PostTrainBench, and ranks second on SWE‑Marathon. On standard coding tests, it surpasses GLM‑5.1 by 17.5 points on Terminal‑Bench 2.1 and closes the gap to closed‑source leaders.

The architecture supports 1M context through IndexShare and KV‑Share, reducing training‑inference discrepancies and improving acceptance rates. Inference optimizations—LayerSplit, fine‑grained memory management, and CPU‑side scheduling—extend throughput as context length grows, addressing KV‑cache capacity and kernel overhead.

Agentic RL training leverages the slime framework to orchestrate heterogeneous tasks, merge expert models, and streamline rollout to production. Slime’s flexible interface and KV‑cache FP8 support enable efficient large‑scale inference concurrency.

Overall, GLM‑5.2 delivers a robust, open‑source platform for sustained engineering work, balancing high‑performance coding, scalable inference, and safeguards against malicious shortcuts, while maintaining transparency and continuous improvement.

The future of AI is here, and it's called GLM-5.2. Get ready to experience the power of long-horizon tasks and revolutionize the field of artificial intelligence.