deepseek-r1-turbo is a advanced-tier language model from DeepSeek. deepseek-r1-turbo is a proprietary model available exclusively through DeepSeek's API. It is a reasoning model that uses extended chain-of-thought (CoT) processing before producing a final answer — significantly more capable on complex math, science, and multi-step logic tasks, but slower and more expensive per query than standard models. DeepSeek is a Chinese AI lab's open-weights model family, known for competitive performance at very low API prices — particularly strong on coding and math benchmarks.
deepseek-r1-turbo is priced at $0.7/1M input tokens and $2.5/1M output tokens. Output tokens are 3.6× more expensive than input tokens — this ratio reflects the sequential nature of autoregressive generation, which requires a separate forward pass per output token versus parallel processing of all input tokens simultaneously. At a typical usage pattern of 1,000 input tokens and 500 output tokens per call, deepseek-r1-turbo costs approximately $1.95 per 1,000 API calls. DeepSeek does not publish a prompt caching rate for this model, so repeated long contexts are billed at the standard $0.7/1M input rate.
Its 64K-token context window is sufficient for most production use cases, handling documents up to ~25,000 words or multi-turn conversations spanning dozens of exchanges. Median latency (P50 time-to-first-token) is approximately 3000ms — better suited to batch or async workloads where latency is less critical. Throughput is approximately 80 tokens/second — adequate for streaming at comfortable reading speed. Maximum output length is 33K tokens — sufficient for long-form content generation, detailed code files, and extended reports.
deepseek-r1-turbo is best suited to reasoning, coding, speed. Supported capabilities include streaming token output for real-time UIs. When evaluating this model for a specific workload, the most important factors are: context window (does your input fit?), output price (how long are your generations?), and latency (is this interactive or batch?). The pricing table above shows how deepseek-r1-turbo compares to similar models across these dimensions.
deepseek-r1-turbo sits in the advanced tier — strong general-purpose models balancing capability and cost, suitable for most production applications. Unlike open-weights alternatives, deepseek-r1-turbo is only available via DeepSeek's API — there is no self-hosted option, which simplifies deployment but creates vendor dependency. When comparing deepseek-r1-turbo to alternatives, use the similar models section on this page to find models at comparable price points with different capability tradeoffs. The intelligence score (84/100) reflects aggregate benchmark performance — a useful proxy for general capability, though real-world performance varies significantly by task type. Always test with your specific prompts and use case before committing to a model for production.
Composite quality score based on reasoning, coding, and instruction-following benchmarks.
Input price vs 184 advanced models tracked. Avg: $1.38/1M.
| Model ID | deepseek-r1-turbo |
| Provider | DeepSeek |
| Model Family | DeepSeek R1 |
| Tier | Advanced |
| Context Window | 64,000 tokens (64K) |
| Max Output Tokens | 32,768 tokens |
| Input Price | $0.7 / 1M tokens |
| Output Price | $2.5 / 1M tokens |
| Cached Input Price | Not available |
| Throughput | 80 tokens/sec |
| Latency (P50) | 3.0s |
| Intelligence Score | 84/100 |
| LiveBench Score | — |
| Cost per Task (LiveBench) | — |
| Data Confidence | — |
| HLE Score | — |
| GPQA Diamond | — |
| SWE-bench Score | — |
| OSWorld Score | — |
| BrowseComp Score | — |
| Terminal-Bench Score | — |
| AutoBench Score | — |
| Parameters | — |
| Vision Support | No |
| Function Calling | No |
| Streaming | Yes |
| Reasoning Model | Yes |
| Open Weights | No |
| Data Source | Static (verified) |
| Last Updated | 2026-07-01 |
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Self-hosting deepseek-r1-turbo? These GPUs are well-matched for this model's compute and memory requirements.