GLM-4.7 is now live on VOLT Intelligence. Z.ai's flagship open-source model delivers Claude-tier coding performance at open-source pricing.
What makes it interesting isn't raw benchmark numbers. It's Preserved Thinking, a mechanism that retains reasoning across multi-turn conversations. Most models lose context or contradict themselves after a few turns. GLM-4.7 was built specifically to avoid that failure mode, which makes it unusually well-suited for agentic coding workflows where conversations run long.
Benchmarks
The numbers back this up. On LiveCodeBench v6, GLM-4.7 scores 84.9% compared to Claude Sonnet 4.5's 64.0%. Tool use performance on τ²-Bench matches Anthropic's best at 87.4%. Math reasoning hits 95.7% on AIME 2025.
That said, GLM-4.7 isn't the best choice for everything. It trails on MMLU-Pro (84.3% vs Gemini's 90.1%), making it less suited for general knowledge tasks. And while 73.8% on SWE-bench is strong for open-source, Claude's 77.2% still leads for real-world software engineering accuracy.
Where GLM-4.7 Excels
The model shines in multi-turn coding sessions, automated code review, and tool-heavy agentic workflows. Z.ai also highlights improved frontend generation to assist when ‘vibe coding', with cleaner HTML/CSS output and better visual spacing. Multilingual coding improved 12.9% over the previous version.
For teams building coding agents or automated development pipelines, GLM-4.7 offers Claude-level performance without Claude-level costs.
Running GLM-4.7 on VOLT Intelligence
Self-hosting a 355B parameter model requires serious GPU resources. Through VOLT Intelligence, GLM-4.7 is accessible via a single API alongside the full model library.
OpenAI-compatible endpoints mean minimal code changes to integrate.
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