GLM-5 vs Kimi K2 Thinking
Benchmarks, API pricing and specs, head to head. Data updated 2026-06-10.
GLM-5
Z.ai (Zhipu) · Feb 2026
Z.ai's 744B open-weights MoE — within ~4 points of Opus 4.6 on SWE-bench Verified at $1/$3.20 per million tokens.
Kimi K2 Thinking
67.6Moonshot AI · Nov 2025
A trillion-parameter open reasoning agent that can chain 200–300 tool calls — the open-weights agentic standout of late 2025.
The verdict
GLM-5 wins 1 of the 1 benchmarks these models share, against 0 for Kimi K2 Thinking. Kimi K2 Thinking is about 1.4x cheaper per blended million tokens (3:1 input:output mix). Kimi K2 Thinking also takes 262K of context versus 200K for GLM-5.
Benchmark head-to-head 1–0
Specs & pricing
| GLM-5 | Kimi K2 Thinking | |
|---|---|---|
| modhub Index | — | 67.6 |
| Input price / 1M | $1 | $0.6 |
| Output price / 1M | $3.2 | $2.5 |
| Context window | 200K | 262K |
| Max output | 128K | — |
| Open weights | yes (MIT) | yes (Modified MIT) |
| Reasoning model | yes | yes |
| Multimodal input | text | text |
| Knowledge cutoff | Dec 2025 | Apr 2025 |
| Released | Feb 2026 | Nov 2025 |
| Example monthly cost* | $14.80 | $9.75 |
* 10M input + 1.5M output tokens per month at list prices, no caching. Green = better value on that row.
Frequently asked questions
- Which is better, GLM-5 or Kimi K2 Thinking?
- GLM-5 wins 1 of the 1 benchmarks these models share, against 0 for Kimi K2 Thinking. Kimi K2 Thinking is about 1.4x cheaper per blended million tokens (3:1 input:output mix). Kimi K2 Thinking also takes 262K of context versus 200K for GLM-5.
- Which is cheaper, GLM-5 or Kimi K2 Thinking?
- GLM-5 costs $1/$3.2 per million input/output tokens, while Kimi K2 Thinking costs $0.6/$2.5. For a typical workload of 10M input and 1.5M output tokens per month, that's $14.80 versus $9.75.
- Which model is better for coding, GLM-5 or Kimi K2 Thinking?
- On SWE-bench Verified — the standard agentic-coding benchmark — GLM-5 scores ~77.8% versus 71.3% for Kimi K2 Thinking, making GLM-5 the stronger pick for coding agents.