Renewed Claude for Opus 4.6. Cancelled it After GLM-5, Again…
Summary
The author cancelled a Claude Opus 4.6 subscription just four hours after downloading GLM-5, a 744B-parameter, MIT-licensed AI model. GLM-5 achieved a 77.8% score on the SWE-bench benchmark, offering "Claude-level coding" capabilities at a significantly lower price point of $1 per million tokens. This rapid shift suggests GLM-5, trained on sanctioned Huawei chips, could disrupt the current $20/month AI subscription model by providing comparable performance at a fraction of the cost. The author had previously evaluated other models like Kimi K2.5 and GPT-5.3 before settling on GLM-5 for its compelling performance-to-price ratio.
Key takeaway
For AI Architects and NLP Engineers evaluating large language models for coding tasks, GLM-5 presents a compelling, cost-effective alternative to proprietary models like Claude Opus. Its 77.8% SWE-bench score and $1/M token pricing suggest you can achieve high-quality results at 6% of the cost, potentially eliminating the need for expensive monthly subscriptions. Consider integrating GLM-5 into your development workflow to optimize budget without sacrificing performance.
Key insights
GLM-5 offers Claude-level coding performance at 6% of the price, potentially ending $20/month AI subscriptions.
Principles
- Cost-performance ratio drives AI model adoption.
- Open-source models can rival proprietary offerings.
In practice
- Evaluate GLM-5 for coding tasks.
- Compare token pricing across models.
Topics
- GLM-5
- SWE-bench
- Large Language Models
- AI Subscription Models
- Code Generation
Best for: AI Architect, NLP Engineer, AI Product Manager, AI Engineer, Machine Learning Engineer, Prompt Engineer
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Editorial summary, takeaway, and curation by AIssential. Original article published by Towards AI - Medium.