Grok 4 vs Kimi K2 Thinking
Grok 4 (2026) and Kimi K2 Thinking (2025) are frontier-tier reasoning models from xAI and Moonshot AI. Grok 4 ships a 256k-token context window, while Kimi K2 Thinking ships a 256K-token context window. On pricing, Kimi K2 Thinking costs $0.6/1M input tokens versus $3/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Kimi K2 Thinking is ~400% cheaper at $0.6/1M; pay for Grok 4 only for coding workflow support.
Specs
| Released | 2026-03-01 | 2025-01-01 |
| Context window | 256k | 256K |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Grok 4 | Kimi K2 Thinking | |
|---|---|---|
| Input price | $3/1M tokens | $0.6/1M tokens |
| Output price | $15/1M tokens | $2.5/1M tokens |
| Providers |
Capabilities
| Grok 4 | Kimi K2 Thinking | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on multimodal input: Grok 4 and code execution: Grok 4. Both models share reasoning mode and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Grok 4 lists $3/1M input and $15/1M output tokens, while Kimi K2 Thinking lists $0.6/1M input and $2.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Kimi K2 Thinking lower by about $5.43 per million blended tokens. Availability is 3 providers versus 5, so concentration risk also matters.
Choose Grok 4 when coding workflow support are central to the workload. Choose Kimi K2 Thinking when provider fit, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Grok 4 or Kimi K2 Thinking?
Grok 4 supports 256k tokens, while Kimi K2 Thinking supports 256K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Grok 4 or Kimi K2 Thinking?
Kimi K2 Thinking is cheaper on tracked token pricing. Grok 4 costs $3/1M input and $15/1M output tokens. Kimi K2 Thinking costs $0.6/1M input and $2.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Grok 4 or Kimi K2 Thinking open source?
Grok 4 is listed under Proprietary. Kimi K2 Thinking is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for multimodal input, Grok 4 or Kimi K2 Thinking?
Grok 4 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for reasoning mode, Grok 4 or Kimi K2 Thinking?
Both Grok 4 and Kimi K2 Thinking expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Grok 4 and Kimi K2 Thinking?
Grok 4 is available on Microsoft Foundry, OpenRouter, and Replicate API. Kimi K2 Thinking is available on Fireworks AI, GCP Vertex AI, NVIDIA NIM, AWS Bedrock, and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-27. Data sourced from public model cards and provider documentation.