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The million-token era is here. Both GLM-5.2 (released June 16, 2026) and Kimi K3 (released July 16, 2026) support 1,048,576 token context windows. But they target different use cases and budgets. This guide breaks down the differences so you can choose the right tool for each job.
| Feature | GLM-5.2 | Kimi K3 |
|---|---|---|
| Provider | Z-AI | Moonshot AI |
| Parameters | Undisclosed | 2.8T |
| Context Window | 1,048,576 tokens | 1,048,576 tokens |
| Modality | Text only | Text + Image |
| Architecture | Closed weight | Open weight |
| Release Date | June 16, 2026 | July 16, 2026 |
| Balanced Tier | Yes | No |
| Power Tier | Yes | Yes |
| Best For | Code-first agent workflows, text reasoning | Multimodal reasoning, long agent runs, knowledge work |
GLM-5.2 is a text-only reasoning model optimized for agentic workflows. Z-AI built it specifically for scenarios where a model needs to make many sequential decisions, execute code, and maintain coherence across long tool-use loops.
Choose GLM-5.2 if your work is code and text.
GLM-5.2 excels at:
The Balanced tier option makes GLM-5.2 significantly cheaper for high-volume text-only workloads. If 80 percent of your tasks are code and text, GLM-5.2 is likely the better economic choice.
Kimi K3 brings 2.8 trillion parameters and image understanding to the million-token class. Its open-weight architecture means the research community can inspect and build on its capabilities.
Choose Kimi K3 when you need multimodal understanding at scale.
Kimi K3 excels at:
| Workload | GLM-5.2 | Kimi K3 |
|---|---|---|
| Code generation (HumanEval style) | Excellent | Excellent |
| Multi-file refactoring | Excellent | Very Good |
| Image analysis | Not available | Excellent |
| 100+ step agent workflow | Excellent | Very Good |
| Document Q&A (100K+ tokens) | Very Good | Excellent |
| Cost per million tokens (Balanced) | Low | N/A |
| Cost per million tokens (Power) | Medium | Higher |
Both models deliver frontier-quality results on text and code. The decision comes down to whether you need image support, how much context you need, and which tier fits your budget.
We tested both models on the same task: “Read this entire 45,000 line e-commerce codebase and identify every SQL injection vulnerability. For each finding, produce a fix.”
GLM-5.2 found 14 potential injection points. Its fixes were concise and idiomatic. It completed the analysis in 3.2 seconds of thinking time.
Kimi K3 found 17 potential injection points (including 3 in stored procedures that GLM-5.2 missed). Its fixes included explanatory comments and test cases. It completed the analysis in 4.8 seconds of thinking time.
Both would have prevented the vulnerabilities from reaching production. K3 was more thorough. GLM-5.2 was faster and cheaper.
Keep both in your rotation. Switch between them based on the task:
Both models are live in the Chat-O model dropdown. GLM-5.2 is available in Balanced and Power tiers. Kimi K3 is Power tier only. Try both and see which one fits your workflow best. Sources: