Side-by-side comparison
R1 vs Kimi K2 0711
| R1 | Kimi K2 0711 | |
|---|---|---|
| Provider | DeepSeek | MoonshotAI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 64,000 | 131,072 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | tools | tools |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.7000 | 0.5700 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 2.5000 | 2.3000 |
Frequently asked questions
Which is cheaper, R1 or Kimi K2 0711?
Kimi K2 0711 is cheaper than R1 on a 50/50 input/output blend by about $0.165 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, R1 or Kimi K2 0711?
Kimi K2 0711 has the larger context window at 131k tokens versus 64k tokens for R1. That means Kimi K2 0711 can ingest about 2.0x as much text per request.
What is the difference between R1 and Kimi K2 0711?
R1 comes from DeepSeek; Kimi K2 0711 comes from MoonshotAI. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.