Side-by-side comparison
R1 0528 vs Kimi K2 0905
| R1 0528 | Kimi K2 0905 | |
|---|---|---|
| Provider | DeepSeek | MoonshotAI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 163,840 | 262,144 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | tools, json_mode | tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.5000 | 0.6000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 2.1500 | 2.5000 |
Frequently asked questions
Which is cheaper, R1 0528 or Kimi K2 0905?
R1 0528 is cheaper than Kimi K2 0905 on a 50/50 input/output blend by about $0.225 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 0528 or Kimi K2 0905?
Kimi K2 0905 has the larger context window at 262k tokens versus 164k tokens for R1 0528. That means Kimi K2 0905 can ingest about 1.6x as much text per request.
What is the difference between R1 0528 and Kimi K2 0905?
R1 0528 comes from DeepSeek; Kimi K2 0905 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.