R1 0528 vs GPT-3.5 Turbo (older v0613)
GPT-3.5 Turbo (older v0613)
| R1 0528 | GPT-3.5 Turbo (older v0613) | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary β | 163,840 | 4,095 |
| 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 β | 0.5000 | 1.0000 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3β5Γ pricier than input. Glossary β | 2.1500 | 2.0000 |
Frequently asked questions
Which is cheaper, R1 0528 or GPT-3.5 Turbo (older v0613)?
R1 0528 is cheaper than GPT-3.5 Turbo (older v0613) on a 50/50 input/output blend by about $0.175 per 1M tokens. Exact savings depend on your input-vs-output ratio β use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, R1 0528 or GPT-3.5 Turbo (older v0613)?
R1 0528 has the larger context window at 164k tokens versus 4k tokens for GPT-3.5 Turbo (older v0613). That means R1 0528 can ingest about 40.0x as much text per request.
What is the difference between R1 0528 and GPT-3.5 Turbo (older v0613)?
R1 0528 comes from DeepSeek; GPT-3.5 Turbo (older v0613) comes from OpenAI. They differ in pricing, context window, and supported capabilities β see the side-by-side table on this page for the exact figures, refreshed nightly.