kimi-k2.5 vs glm-5.3
Side-by-side comparison of kimi-k2.5 and glm-5.3: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. glm-5.3 outperforms kimi-k2.5 on 4 of 4 shared benchmarks.
kimi-k2.5
Input / 1M
$0.60
Output / 1M
$3.00
Context
262K
Model ID
moonshot/kimi-k2.5
glm-5.3
Input / 1M
$1.40
Output / 1M
$4.40
Context
1M
Model ID
zai/glm-5.3
Benchmark comparison
Intelligence Indexreasoning
kimi-k2.527.6%
glm-5.348.6%
Coding Indexcoding
kimi-k2.546.8%
glm-5.374.8%
GPQA Diamondreasoning
kimi-k2.587.9%
glm-5.391.7%
Terminal-Bench Hardagentic
kimi-k2.534.8%
glm-5.3N/A
τ²-Benchagentic
kimi-k2.595.9%
glm-5.3N/A
SciCodecoding
kimi-k2.5N/A
glm-5.359.0%
Humanity's Last Examreasoning
kimi-k2.530.7%
glm-5.342.3%
Scores sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and don't capture every aspect of model quality.
Pricing & specifications
| kimi-k2.5 | glm-5.3 | |
|---|---|---|
| Input price / 1M | $0.60 | $1.40 |
| Output price / 1M | $3.00 | $4.40 |
| Context window | 262K tokens | 1M tokens |
| Max output | 262K tokens | 128K tokens |
| Vision input | Yes | Yes |
| Tool calling | Yes | Yes |
| Reasoning | Yes | Yes |
| Prompt caching | Yes | Yes |
| Computer use | N/A | N/A |
| Provider | Moonshot AI | Z.ai |
Questions people ask
Is kimi-k2.5 better than glm-5.3?
glm-5.3 outperforms kimi-k2.5 on 4 of 4 shared benchmarks. See the benchmark comparison above for specifics: kimi-k2.5 and glm-5.3 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, kimi-k2.5 or glm-5.3?
kimi-k2.5 is cheaper. kimi-k2.5 costs $0.60/$3.00 per 1M input/output tokens, while glm-5.3 costs $1.40/$4.40.
Can I use kimi-k2.5 and glm-5.3 through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch between "moonshot/kimi-k2.5" and "zai/glm-5.3", no other code changes needed.
What are the context windows?
kimi-k2.5 supports up to 262K tokens of context. glm-5.3 supports up to 1M tokens. Longer context means you can feed larger documents or codebases in a single prompt, though quality often degrades past 128K for most models.
Switch between kimi-k2.5 and glm-5.3 with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.