DeepSeek R1
DeepSeek's 671B MoE reasoning model (37B active) with chain-of-thought reasoning for math and code.
Key Specifications
- Context window
- 128K tokens
- Released
- Parameters
- 671B, 37B active
- Inputs
- Text
- Capabilities Show details
- Reasoning Thinks before it answers, always on or as a switchable mode. Function calling Connect to external tools, APIs, and systems. Structured output Return responses in structured formats like JSON.
Hosted API pricing
| Provider | Input /1M tokens | Output /1M tokens | Cached input /1M | Cost at 10M in + 2M out | |
|---|---|---|---|---|---|
|
|
$0.70 | $2.50 | $0.35 | $12.00 | View |
|
|
$1.35 | $5.40 | $24.30 | View | |
|
|
$3.75 | $10.00 | $57.50 | View |
Heads up: Base-tier, on-demand rates per 1M tokens; cached, batch and long-context tiers excluded. A provider may serve a shorter context or a quantized build than the creator's release. Verify before provisioning. More on how we price.
Estimated cost to self-host
DeepSeek R1 needs about 373 GB of GPU memory at 4-bit with 32K context. The cheapest rental that fits is 8× A100 at about $10,138 a month.
That costs the same as roughly 10B tokens a month on Novita's API. Self-hosting is more expensive below that volume.
| Precision | Memory | Cheapest fit (32K context) | Cost /mo | Break-even vs API |
|---|---|---|---|---|
| 4-bitINT4 / FP4 |
373 GB
|
$10,138
|
10B tokens /mo
|
|
| 8-bitFP8 / INT8 |
674 GB
|
$12,672
|
13B tokens /mo
|
|
| 16-bitFP16 / BF16 |
1,346 GB
|
$45,446
|
45B tokens /mo
|
Estimates based on median on-demand rates for Nvidia GPUs. Memory is weights plus KV cache for one request, using FP8 KV cache where supported and FP16/BF16 otherwise. Break-even assumes a 5:1 input-to-output ratio. No guarantee of runtime support, usable performance, or that a matching quantized build exists. How we estimate costs.
Similarly priced models
The models nearest DeepSeek R1 by blended rate, each at its own cheapest provider.
| Model | Blended /1M | Input /1M | Output /1M | Context | Cutoff | vs DeepSeek R1 |
|---|---|---|---|---|---|---|
|
|
$0.8667 | $0.60 | $2.20 | 205K | −13% | |
|
|
$0.9167 | $0.50 | $3.00 | 1M | Jan 2025 | −8% |
|
|
$0.9167 | $0.50 | $3.00 | 1M | −8% | |
|
|
$0.95 | $0.70 | $2.20 | 1M | −5% | |
|
|
$0.99 | $0.66 | $2.64 | 1M | Sep 2025 | −1% |
|
|
$1.00 | $0.70 | $2.50 | 128K | ||
|
|
$1.00 | $0.70 | $2.50 | 64K | 0% | |
|
|
$1.00 | $0.65 | $2.75 | 8K | Dec 2023 | 0% |
|
|
$1.00 | $0.40 | $4.00 | 262K | 0% | |
|
|
$1.0333 | $0.60 | $3.20 | 262K | +3% | |
|
|
$1.1667 | $1.00 | $2.00 | 256K | +17% |
Prices are USD per 1M tokens at each model's cheapest listed provider. Blended is the cost of 10M input plus 2M output tokens, spread over the 12M.
Frequently Asked Questions
What is DeepSeek R1 good for?
Math and code tasks that gain from step-by-step reasoning. MIT-licensed weights allow self-hosting or fine-tuning, on a multi-GPU node.
When is DeepSeek R1 not a good fit?
Cost-sensitive or multimodal work: it is text only and sits at the top of DeepSeek's price range. DeepSeek's later hybrid models fold R1-style reasoning into a single chat model.
What is the cheapest way to run DeepSeek R1?
Hosted, unless you push serious volume. Novita charges $0.70 in / $2.50 out per 1M tokens. The cheapest rental that fits is 8x A100 at $10,138 a month, which costs the same as about 10B tokens a month on that API.
Can I self-host DeepSeek R1?
Yes. The weights are MIT licensed. At 4-bit it needs about 373 GB of GPU memory, which starts at roughly $10,138 a month on the cheapest rental that fits.
More from DeepSeek
| Model | Context | Input /1M | Output /1M |
|---|---|---|---|
|
|
64K | $0.70 | $2.50 |
|
|
131K | $0.80 | $0.80 |
|
|
1M | $0.44 | $1.32 |
|
|
64K | $0.40 | $1.30 |
|
|
1M | $0.45 | $0.89 |
|
|
1M | $0.30 | $1.20 |
|
|
128K | $0.27 | $1.12 |
|
|
131K | $0.27 | $1.00 |