Both are agent-first Chinese flagships under permissive licenses. GLM-5.2 is the coding specialist — 1M context, MCP-native, plain MIT. K2.5 is the multimodal generalist — video understanding, 76.8% SWE-bench, Agent Swarm. Coding harnesses lean GLM; agents that need eyes lean Kimi.
GLM-5.2 vs Kimi K2.5 at a glance
| GLM-5.2 | Kimi K2.5 | |
|---|---|---|
| Vendor | Zhipu AI (Z.ai) (China) | Moonshot AI (China) |
| Open weights | Yes — downloadable | Yes — downloadable |
| License | MIT — weights free to download, self-host, fine-tune, and use commercially | Modified MIT — free commercial use; attribution required above 100M monthly active users or $20M monthly revenue |
| Parameters | 753B (~40B active) | 1T (32B active) |
| Context window | 1M tokens | 256K tokens |
| Modalities | text | text, image, video |
| Pricing | Varies by hosting provider (open weights) | $0.60 in / $2.50 out per 1M tokens |
| Released | 2026-06-13 | 2026-01-27 |
Specs and pricing verified July 2026.
About GLM-5.2
GLM-5.2 is Zhipu AI's June 13, 2026 flagship: a ~753B-parameter mixture-of-experts model with ~40B active parameters, a 1-million-token context window, up to 128K output tokens, and MIT-licensed weights on Hugging Face. It is built deliberately as a coding and agent model — configurable thinking effort, native tool calling, MCP integration, structured JSON output — rather than a general-purpose chat model.
The engineering hook is IndexShare, Zhipu's sparse-attention refinement that reuses indexers across sparse-attention layers to cut per-token compute at long context. That is what makes the 1M-token window usable in practice for long-horizon coding agents, not just impressive on a spec sheet.
Full specs, benchmarks, and hardware guidance: the GLM-5.2 page.
About Kimi K2.5
Kimi K2.5 is Moonshot AI's trillion-parameter multimodal agent model, released January 27, 2026. Built by continual-pretraining on ~15 trillion mixed visual and text tokens on top of the Kimi-K2 base, it natively understands text, images, and video, activates 32B parameters per token, and ships both instant and thinking modes.
Its defining feature is agentic: K2.5 introduced Agent Swarm, coordinating up to 100 specialized agents on a single task, and posted 76.8% on SWE-bench Verified — frontier-class coding from an open-weight release. The Modified MIT license is effectively free for everyone below 100M monthly users or $20M monthly revenue, at which point attribution (not payment) kicks in.
Full specs, benchmarks, and hardware guidance: the Kimi K2.5 page.
Choosing between them
Choose GLM-5.2 for:
- Long-horizon coding agents (1M-token context built for repository-scale work)
- Teams that want an MIT-licensed Claude-for-coding alternative
- Tool-driven agentic workloads (native tool calling, MCP, JSON output)
Choose Kimi K2.5 for:
- Multimodal agents that need vision and video, not just text
- Frontier coding (76.8% SWE-bench Verified) on open weights
- Multi-agent orchestration workloads (Agent Swarm)
Frequently asked questions
Is GLM-5.2 better than Kimi K2.5?
Both are agent-first Chinese flagships under permissive licenses. GLM-5.2 is the coding specialist — 1M context, MCP-native, plain MIT. K2.5 is the multimodal generalist — video understanding, 76.8% SWE-bench, Agent Swarm. Coding harnesses lean GLM; agents that need eyes lean Kimi.
Which is cheaper: GLM-5.2 or Kimi K2.5?
GLM-5.2: Varies by hosting provider (open weights). Kimi K2.5: $0.60 in / $2.50 out per 1M tokens. Both are open-weight, so self-hosting costs depend on your hardware and utilization.
Can I self-host GLM-5.2 and Kimi K2.5?
GLM-5.2: yes — weights are published under MIT. Kimi K2.5: yes — weights are published under Modified MIT.