GLM-4.6 vs Kimi K1.5 Chat: which model should you choose?
We compared GLM-4.6 and Kimi K1.5 Chat on price, context window and 12 benchmarks. GLM-4.6 and Kimi K1.5 Chat are effectively tied on the index average; GLM-4.6 is cheaper on a blended 3:1 basis.
GLM-4.6
GLM-4.6 is a multimodal model from Zhipu AI. It offers a 128,000-token context window, costs $5.10 per million input tokens and $18.45 per million output tokens, and averages 80.2 across the index's benchmark suite.
- Input
- $5.10 / 1M
- Output
- $18.45 / 1M
- Context
- 128,000
- Avg score
- 80.2
- Open weights
- Yes
Kimi K1.5 Chat
Kimi K1.5 Chat is a multimodal model from Moonshot AI. It offers a 128,000-token context window, costs $5.11 per million input tokens and $26.59 per million output tokens, and averages 80.2 across the index's benchmark suite.
- Input
- $5.11 / 1M
- Output
- $26.59 / 1M
- Context
- 128,000
- Avg score
- 80.2
- Open weights
- Yes
Specification comparison
| Spec | GLM-4.6 | Kimi K1.5 Chat | Edge |
|---|---|---|---|
| Input price / 1M | $5.10 | $5.11 | A |
| Output price / 1M | $18.45 | $26.59 | A |
| Context window | 128,000 | 128,000 | Tie |
| Max output | 8,192 | 32,768 | B |
| Average score | 80.2 | 80.2 | Tie |
| Arena Elo | 1440.7 | 1422.6 | A |
| Open weights | Yes | Yes | Tie |
Benchmark comparison
GLM-4.6 wins 7, Kimi K1.5 Chat wins 5, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | GLM-4.6 | Kimi K1.5 Chat | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 84.0 | 81.3 | 2.7 | GLM-4.6 |
| GPQA Diamond | 78.3 | 78.1 | 0.2 | GLM-4.6 |
| SWE-bench Verified | 67.4 | 69.9 | 2.5 | Kimi K1.5 Chat |
| HumanEval | 83.8 | 84.3 | 0.5 | Kimi K1.5 Chat |
| MATH-500 | 83.4 | 81.7 | 1.7 | GLM-4.6 |
| AIME 2025 | 80.2 | 81.4 | 1.2 | Kimi K1.5 Chat |
| LiveCodeBench | 71.6 | 75.7 | 4.1 | Kimi K1.5 Chat |
| IFEval | 86.4 | 88.2 | 1.8 | Kimi K1.5 Chat |
| TruthfulQA | 82.5 | 80.3 | 2.2 | GLM-4.6 |
| HellaSwag | 89.4 | 87.2 | 2.2 | GLM-4.6 |
| MMMU | 75.4 | 73.6 | 1.8 | GLM-4.6 |
| Arena Elo | 1440.7 | 1422.6 | 18.1 | GLM-4.6 |
Price analysis
On a blended 3:1 input-to-output basis, GLM-4.6 costs about $8.44 per million tokens and Kimi K1.5 Chat costs about $10.48. GLM-4.6 is roughly 19% cheaper than Kimi K1.5 Chat. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
Both models list a 128,000-token context window. That is enough for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, GLM-4.6 wins 7, Kimi K1.5 Chat wins 5, and 0 are tied. The two models are effectively tied on the index average at 80.2.
The price picture favours GLM-4.6. The context picture is effectively a tie. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.
If you need a single default, start with GLM-4.6; it is cheaper on a blended basis and has the larger context window. Test it on your own traffic before committing.
Choose GLM-4.6 if
- Unit cost matters and you want the cheaper blended price.
Choose Kimi K1.5 Chat if
- You need the larger 32,768-token output limit.
FAQ
Is GLM-4.6 better than Kimi K1.5 Chat?
The two models are effectively tied on the index average at 80.2. The better choice depends on price, context and your task. GLM-4.6 wins 7 benchmarks, Kimi K1.5 Chat wins 5.
Which is cheaper, GLM-4.6 or Kimi K1.5 Chat?
GLM-4.6 is cheaper on a blended 3:1 basis at about $8.44 per million tokens, versus $10.48 for Kimi K1.5 Chat.
Which has the larger context window?
Both models list a 128,000-token context window.
Are these models open weights?
GLM-4.6 is open weights; Kimi K1.5 Chat is open weights.
Which should I choose for production?
If you need a single default, start with GLM-4.6; it is cheaper on a blended basis and has the larger context window. Test it on your own traffic before committing.