kimi-k3 vs gpt-5.6-luna
Side-by-side comparison of kimi-k3 and gpt-5.6-luna: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. kimi-k3 outperforms gpt-5.6-luna on 5 of 5 shared benchmarks.
kimi-k3
Input / 1M
$3.00
Output / 1M
$15.00
Context
1.0M
Model ID
moonshot/kimi-k3
gpt-5.6-luna
Input / 1M
$0.20
Output / 1M
$1.20
Context
1.1M
Model ID
openai/gpt-5.6-luna
Benchmark comparison
Intelligence Indexreasoning
kimi-k350.2%
gpt-5.6-luna43.4%
Coding Indexcoding
kimi-k376.2%
gpt-5.6-luna71.4%
GPQA Diamondreasoning
kimi-k393.5%
gpt-5.6-luna91.1%
SciCodecoding
kimi-k359.5%
gpt-5.6-luna53.6%
Humanity's Last Examreasoning
kimi-k346.9%
gpt-5.6-luna39.5%
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-k3 | gpt-5.6-luna | |
|---|---|---|
| Input price / 1M | $3.00 | $0.20 |
| Output price / 1M | $15.00 | $1.20 |
| Context window | 1.0M tokens | 1.1M tokens |
| Max output | 1.0M 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 | OpenAI Inc. |
Questions people ask
Is kimi-k3 better than gpt-5.6-luna?
kimi-k3 outperforms gpt-5.6-luna on 5 of 5 shared benchmarks. See the benchmark comparison above for specifics: kimi-k3 and gpt-5.6-luna have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, kimi-k3 or gpt-5.6-luna?
gpt-5.6-luna is cheaper. kimi-k3 costs $3.00/$15.00 per 1M input/output tokens, while gpt-5.6-luna costs $0.20/$1.20.
Can I use kimi-k3 and gpt-5.6-luna 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-k3" and "openai/gpt-5.6-luna", no other code changes needed.
What are the context windows?
kimi-k3 supports up to 1.0M tokens of context. gpt-5.6-luna supports up to 1.1M 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-k3 and gpt-5.6-luna with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.