DeepSeek-R1
Open-weightLast verified: June 2026· DeepSeek DeepSeek-R1 pricing
Open-weight reasoning model. Confirm current pricing with the provider.
- Input / 1M
- $0.55
- Output / 1M
- $2.19
- Context
- 128K tokens
- Provider
- DeepSeek
Pricing verified June 2026. Prices change frequently. Always confirm against the provider’s official pricing page before relying on these figures for budgeting. Official pricing →
What DeepSeek-R1 is best for
Low-cost reasoning where you can tolerate an open-weight reasoning model.
Use it for cost-sensitive or data-sensitive workloads where an open-weight model clears your quality bar, including self-hosting. Avoid it for work that needs top-tier frontier quality, unless you’ve validated the model holds up with evals.
When to choose DeepSeek-R1
Low-cost reasoning: choose R1 over V3 when the task is reasoning-heavy, and over o4-mini when price is the deciding factor and you can tolerate an open-weight reasoning model. Validate on your own evals before trusting it on hard routes.
DeepSeek-R1 cost by volume
Estimated monthly cost at three realistic volumes, at $0.55 input / $2.19 output per million tokens.
| Scenario | Input / mo | Output / mo | Est. cost / mo |
|---|---|---|---|
| Prototype | 2M | 0.5M | $2 |
| Growing product | 50M | 10M | $49 |
| At scale | 500M | 100M | $494 |
Plug in your own numbers with the cost calculator.
Cutting your DeepSeek-R1 bill
The headline price isn’t the lever — usage pattern is. The reductions come from routing low-stakes calls to a cheaper tier, caching stable prefixes, batching non-urgent work, and gating it all behind evals so quality holds. The full method — the same one that takes 30–60% out without regressions — is the LLM cost optimization playbook.
Context window: 128K tokens
DeepSeek-R1’s context window bounds how much it can consider at once — system prompt, history, retrieved docs, and the response all draw from those 128K tokens. A larger window enables whole-codebase reasoning and long documents, but using more of it costs more per request — so retrieval and caching still matter even when the window is large.
Cheaper alternatives to DeepSeek-R1
By blended cost (3:1 input:output). The right swap depends on whether quality holds on your routes — always validate with evals.
Frequently asked questions
How much does DeepSeek-R1 cost?
DeepSeek-R1 costs $0.55 per million input tokens and $2.19 per million output tokens. A workload of 50M input and 10M output tokens per month would cost about $49.4. Confirm current pricing with the provider.
What is DeepSeek-R1's context window?
DeepSeek-R1 has a 128K-token context window. Open-weight reasoning model. Confirm current pricing with the provider.
Is DeepSeek-R1 the right model for my workload?
Low-cost reasoning where you can tolerate an open-weight reasoning model. The cheapest correct model is workload-specific — route low-stakes calls to a cheaper tier and reserve DeepSeek-R1 for work where its strengths matter, validated by evals.