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kimi-k2 vs grok-4

Side-by-side comparison of kimi-k2 and grok-4 — benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. grok-4 outperforms kimi-k2 on 7 of 7 shared benchmarks.

Benchmark comparison

MMLU Proknowledge
kimi-k282.3%
grok-487.5%
GPQA Diamondreasoning
kimi-k270.0%
grok-487.5%
HumanEvalcoding
kimi-k289.9%
grok-493.8%
SWE-Bench Verifiedcoding
kimi-k265.8%
grok-472.5%
MATHmath
kimi-k289.2%
grok-494.1%
AIME 2024math
kimi-k280.1%
grok-490.1%
MMMUmultimodal
kimi-k2
grok-477.9%
LiveBenchreasoning
kimi-k268.3%
grok-475.4%

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-k2grok-4
Input price / 1M$0.60$3.00
Output price / 1M$2.50$15.00
Context window262K tokens256K tokens
Max output262K tokens
Vision inputYesYes
Tool callingYesYes
ReasoningYes
Prompt cachingYesYes
Computer useYes
ProviderGoogle LLC (Vertex AI)xAI Corp.

Questions people ask

Is kimi-k2 better than grok-4?
grok-4 outperforms kimi-k2 on 7 of 7 shared benchmarks. See the benchmark comparison above for specifics — kimi-k2 and grok-4 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper — kimi-k2 or grok-4?
kimi-k2 is cheaper. kimi-k2 costs $0.60/$2.50 per 1M input/output tokens, while grok-4 costs $3.00/$15.00.
Can I use kimi-k2 and grok-4 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 "xai/grok-4" — no other code changes needed.
What are the context windows?
kimi-k2 supports up to 262K tokens of context. grok-4 supports up to 256K 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 grok-4 with one line of code

Requesty provides a single OpenAI-compatible API for 400+ models. Change the model parameter, not your code.

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