kimi-k2.6 vs gpt-5.3-codex
Side-by-side comparison of kimi-k2.6 and gpt-5.3-codex: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. gpt-5.3-codex outperforms kimi-k2.6 on 4 of 5 shared benchmarks.
kimi-k2.6
Input / 1M
$0.95
Output / 1M
$4.00
Context
262K
Model ID
moonshot/kimi-k2.6
gpt-5.3-codex
Input / 1M
$1.75
Output / 1M
$14.00
Context
400K
Model ID
openai-responses/gpt-5.3-codex
Benchmark comparison
Intelligence Indexreasoning
kimi-k2.635.8%
gpt-5.3-codex36.9%
Coding Indexcoding
kimi-k2.661.8%
gpt-5.3-codexN/A
GPQA Diamondreasoning
kimi-k2.691.1%
gpt-5.3-codex91.5%
Terminal-Bench Hardagentic
kimi-k2.643.9%
gpt-5.3-codex53.0%
τ²-Benchagentic
kimi-k2.695.9%
gpt-5.3-codex86.0%
Humanity's Last Examreasoning
kimi-k2.637.5%
gpt-5.3-codex42.5%
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-k2.6 | gpt-5.3-codex | |
|---|---|---|
| Input price / 1M | $0.95 | $1.75 |
| Output price / 1M | $4.00 | $14.00 |
| Context window | 262K tokens | 400K 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 | OpenAI Responses |
Questions people ask
Is kimi-k2.6 better than gpt-5.3-codex?
gpt-5.3-codex outperforms kimi-k2.6 on 4 of 5 shared benchmarks. See the benchmark comparison above for specifics: kimi-k2.6 and gpt-5.3-codex have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, kimi-k2.6 or gpt-5.3-codex?
kimi-k2.6 is cheaper. kimi-k2.6 costs $0.95/$4.00 per 1M input/output tokens, while gpt-5.3-codex costs $1.75/$14.00.
Can I use kimi-k2.6 and gpt-5.3-codex 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-k2.6" and "openai-responses/gpt-5.3-codex", no other code changes needed.
What are the context windows?
kimi-k2.6 supports up to 262K tokens of context. gpt-5.3-codex supports up to 400K 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-k2.6 and gpt-5.3-codex with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.