kimi-k2 vs gpt-5
Side-by-side comparison of kimi-k2 and gpt-5— benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. gpt-5 outperforms kimi-k2 on 7 of 11 shared benchmarks.
kimi-k2
Input / 1M
$0.60
Output / 1M
$2.50
Context
262K
Model ID
vertex/kimi-k2
gpt-5
Input / 1M
$1.25
Output / 1M
$10.00
Context
400K
Model ID
openai/gpt-5
Benchmark comparison
Intelligence Indexreasoning
kimi-k240.9%
gpt-544.6%
Coding Indexcoding
kimi-k234.8%
gpt-536.0%
Math Indexmath
kimi-k294.7%
gpt-594.3%
GPQA Diamondreasoning
kimi-k283.8%
gpt-585.4%
AIME 2025math
kimi-k294.7%
gpt-594.3%
LiveCodeBenchcoding
kimi-k285.3%
gpt-584.6%
Terminal-Bench Hardagentic
kimi-k231.1%
gpt-532.6%
τ²-Benchagentic
kimi-k293.0%
gpt-584.8%
SciCodecoding
kimi-k242.4%
gpt-542.9%
MMLU Proknowledge
kimi-k284.8%
gpt-587.1%
Humanity's Last Examreasoning
kimi-k222.3%
gpt-526.5%
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 | gpt-5 | |
|---|---|---|
| Input price / 1M | $0.60 | $1.25 |
| Output price / 1M | $2.50 | $10.00 |
| 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 | — | — |
| Provider | Google LLC (Vertex AI) | OpenAI Inc. |
Questions people ask
Is kimi-k2 better than gpt-5?
gpt-5 outperforms kimi-k2 on 7 of 11 shared benchmarks. See the benchmark comparison above for specifics — kimi-k2 and gpt-5 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper — kimi-k2 or gpt-5?
kimi-k2 is cheaper. kimi-k2 costs $0.60/$2.50 per 1M input/output tokens, while gpt-5 costs $1.25/$10.00.
Can I use kimi-k2 and gpt-5 through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch — "vertex/kimi-k2" or "openai/gpt-5" — no other code changes needed.
What are the context windows?
kimi-k2 supports up to 262K tokens of context. gpt-5 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 and gpt-5 with one line of code
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