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Grok 4 Heavy vs Kimi K2 Thinking

Grok 4 Heavy (2025) and Kimi K2 Thinking (2025) are frontier reasoning models from xAI and Moonshot AI. Grok 4 Heavy ships a 256k-token context window, while Kimi K2 Thinking ships a 256K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Grok 4 Heavy is safer overall; choose Kimi K2 Thinking when reasoning depth matters.

Specs

Released2025-07-092025-01-01
Context window256k256K
Parameters
Architecture-decoder only
LicenseProprietaryProprietary
Knowledge cutoff--

Pricing and availability

Grok 4 HeavyKimi K2 Thinking
Input price-$0.6/1M tokens
Output price-$2.5/1M tokens
Providers-

Capabilities

Grok 4 HeavyKimi 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 Heavy, reasoning mode: Kimi K2 Thinking, and structured outputs: Kimi K2 Thinking. Both models share the core language-model surface, 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.

Pricing coverage is uneven: Grok 4 Heavy has no token price sourced yet and Kimi K2 Thinking has $0.6/1M input tokens. Provider availability is 0 tracked routes versus 5. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Grok 4 Heavy when provider fit are central to the workload. Choose Kimi K2 Thinking when reasoning depth 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 Heavy or Kimi K2 Thinking?

Grok 4 Heavy 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.

Is Grok 4 Heavy or Kimi K2 Thinking open source?

Grok 4 Heavy 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 Heavy or Kimi K2 Thinking?

Grok 4 Heavy 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 Heavy or Kimi K2 Thinking?

Kimi K2 Thinking has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for structured outputs, Grok 4 Heavy or Kimi K2 Thinking?

Kimi K2 Thinking has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Grok 4 Heavy and Kimi K2 Thinking?

Grok 4 Heavy is available on the tracked providers still being sourced. 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.