GLM-5.2 vs Kimi K2-Thinking-0905: Specs & Benchmark Comparison
| Characteristic | GLM-5.2 | Kimi K2-Thinking-0905 |
|---|---|---|
| Company | Zhipu AI | Moonshot AI |
| Release Date | June 16, 2026 | September 4, 2025 |
| Parameters | 753B | 1.0T |
| Multimodal | No | No |
| Context (input) | 1.0M | 262K |
| Context (output) | 131K | 66K |
| Input Price / 1M | $1.40 | $0.60 |
| Output Price / 1M | $4.40 | $2.40 |
| Average Score | 0.9 | 0.9 |
| Benchmarks | ||
| GPQA | 0.9 | 0.8 |
| HMMT 2025 | 0.9 | 1.0 |
Visual Benchmark Comparison
GLM-5.2
Kimi K2-Thinking-0905
GPQA0.9 vs 0.8
0.9
0.8
HMMT 20250.9 vs 1.0
0.9
1.0
Verdict
GLM-5.2 leads in 2 out of 4 comparison categories.
Overall Performance
Both models show comparable average scores: GLM-5.2 — 0.9, Kimi K2-Thinking-0905 — 0.9.
API Cost
Kimi K2-Thinking-0905 is 1.9x cheaper: input $0.60/1M vs $1.40/1M tokens.
Context Window
GLM-5.2 supports a larger context: 1M vs 262K tokens.
Recency
GLM-5.2 is newer: released 6/16/2026 vs 9/4/2025.
More About These Models
Related Comparisons
Frequently Asked Questions
Which is better for coding — GLM-5.2 or Kimi K2-Thinking-0905?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — GLM-5.2 or Kimi K2-Thinking-0905?
Kimi K2-Thinking-0905 is cheaper for input: $0.60 per 1M tokens vs $1.40.
Which has a larger context window — GLM-5.2 or Kimi K2-Thinking-0905?
GLM-5.2 supports a larger context: 1,000,000 tokens vs 262,144.
The GLM-5.2 and Kimi K2-Thinking-0905 comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the GLM-5.2 or Kimi K2-Thinking-0905 page. See also the complete list of AI model comparisons.