AI model comparison
Kimi K2 0905 vs GLM 4.5
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
Moonshot AI
Kimi K2 0905
Kimi K2 0905 is the September update of [Kimi K2 0711](moonshotai/kimi-k2).
- Input / 1M
- $0.60
- Output / 1M
- $2.50
- Context
- 262K
Z.ai
GLM 4.5
GLM-4.5 is our latest flagship foundation model, purpose-built for agent-based applications. It leverages a Mixture-of-Experts (MoE) architecture and supports a context length of up to 128k tokens.
GLM 4.5 is scheduled to be retired on December 31, 2026. Consider GLM 5.3 instead.
- Input / 1M
- $0.60
- Output / 1M
- $2.20
- Context
- 131K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
GLM 4.5
1.1x cheaper for a typical chat
Higher intelligence score
Kimi K2 0905
15.3 vs 12.8 on Artificial Analysis
Larger context window
Kimi K2 0905
262K vs 131K tokens
Newer release
Kimi K2 0905
Released September 4, 2025
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
Kimi K2 0905 vs GLM 4.5 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.60 | $0.60 |
| Output tokensPer 1M tokens | $2.50 | $2.20 |
| Cached input (read)Per 1M tokens | Not available | $0.11 |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 262K tokens | 131K tokens |
| Max output | 98K tokens | 98K tokens |
| Input types | Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | September 4, 2025 | July 25, 2025 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Not supported |
| JSON mode | Supported | Supported |
| Reasoning | Not supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Not supported |
| Deterministic seed | Supported | Not supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
- Kimi K2 0905 vs Gemini 3.1 Flash Lite
- Kimi K2 0905 vs Gemini 2.5 Flash
- Kimi K2 0905 vs Qwen3.5-122B-A10B
- Kimi K2 0905 vs Claude Haiku 4.5
- Kimi K2 0905 vs o4 Mini
- Kimi K2 0905 vs Gemini 2.5 Pro
- Kimi K2 0905 vs DeepSeek V3.1 Terminus
- Kimi K2 0905 vs Nova 2 Lite
- Kimi K2 0905 vs R1 0528
- Kimi K2 0905 vs Kimi K2 0711
Our take
GLM 4.5 is 1.1x cheaper for a typical chat. Kimi K2 0905 scores higher on the Artificial Analysis Intelligence Index (15.3 vs 12.8). Kimi K2 0905 has the larger context window (262K vs 131K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is Kimi K2 0905 or GLM 4.5 cheaper?
GLM 4.5 is cheaper for a typical chat (2K input tokens and 500 output tokens). GLM 4.5 costs $0.60 per 1M input tokens and $2.20 per 1M output tokens, while Kimi K2 0905 costs $0.60 per 1M input tokens and $2.50 per 1M output tokens.
Which has a bigger context window, Kimi K2 0905 or GLM 4.5?
Kimi K2 0905 supports up to 262K tokens of context, compared with 131K for GLM 4.5.
Is Kimi K2 0905 smarter than GLM 4.5?
On the Artificial Analysis Intelligence Index, Kimi K2 0905 scores 15.3 and GLM 4.5 scores 12.8, putting Kimi K2 0905 ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use Kimi K2 0905 and GLM 4.5 at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Kimi K2 0905 and GLM 4.5 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to Kimi K2 0905 and GLM 4.5 at the same time. Compare the answers side by side and keep the best one.