DeepSeek Chat vs DeepSeek R1
Data reconciled August 15, 2026
Short answer
DeepSeek Chat and DeepSeek R1 each win on different axes — neither is simply cheaper or better across the board.
DeepSeek Chat is 2× cheaper on input.
DeepSeek Chat is 5.2× cheaper on output.
DeepSeek Chat holds a 2× larger context window.
Reasoning mode is supported only by DeepSeek R1.
Side by side
| Parameter | DeepSeek Chat | DeepSeek R1 |
|---|---|---|
| Provider | DeepSeek | DeepSeek |
| Input, $ per 1M tokens | $0.28 | $0.55 |
| Output, $ per 1M tokens | $0.42 | $2.19 |
| Cache read, $ per 1M | $0.028 | — |
| Context window | 131,072 | 65,536 |
| Max output | 8,192 | 8,192 |
| Vision | no | no |
| Tools | yes | yes |
| Reasoning | no | yes |
| Status | available | available |
What it costs on your own workload
A price gap per million tokens says little until your volumes are plugged in: on a long fixed system prompt the winner is the model with cheap cache reads, not the one with a cheap input rate. Run DeepSeek Chat and DeepSeek R1 against your own numbers.
Open the cost calculatorWhat is deliberately absent
We do not compare answer quality and we do not reprint third-party benchmarks. We have no quality measurements of our own, and external tables go stale faster than prices while being compiled, almost always, by someone with a stake in the result. What is here is only what we reconcile ourselves every day: prices, limits and supported capabilities.