Side-by-side comparison
Relace Search vs Kimi K2 0711
| Relace Search | Kimi K2 0711 | |
|---|---|---|
| Provider | Relace | MoonshotAI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 256,000 | 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 → | 1.0000 | 0.5700 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 3.0000 | 2.3000 |
Frequently asked questions
Which is cheaper, Relace Search or Kimi K2 0711?
Kimi K2 0711 is cheaper than Relace Search on a 50/50 input/output blend by about $0.565 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, Relace Search or Kimi K2 0711?
Relace Search has the larger context window at 256k tokens versus 131k tokens for Kimi K2 0711. That means Relace Search can ingest about 2.0x as much text per request.
What is the difference between Relace Search and Kimi K2 0711?
Relace Search comes from Relace; 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.