DeepSeek R1
Featured Latest DeepSeek DeepSeek R1 Generally Available Jan 2025
DeepSeek's open-weight reasoning model. Matches o1 on math and science benchmarks with visible chain-of-thought, MIT licence, and 13K+ HuggingFace likes — the most-downloaded open reasoning model.
Context
128K
tokens
Input
$1.35
per MTok
Output
$5.40
per MTok
About
DeepSeek-R1 — AI tool
Modalities
Input
Text Code
Output
Text Code
Code Examples
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-ai/DeepSeek-R1",
"messages": [
{ "role": "user", "content": "Explain quantum entanglement in one sentence." }
]
}' API Parameters
| Name | Type | Description |
|---|---|---|
frequency_penalty | number | Penalize tokens by their frequency so far. Positive values reduce repetition. |
max_completion_tokens | integer | Maximum number of tokens the model may generate in the response. |
presence_penalty | number | Penalize tokens that have appeared at all so far. Positive values encourage new topics. |
response_format | one of | Constrain output to a JSON schema or an enum (structured outputs). |
seed | integer | Deterministic seed for sampling. Same seed + same prompt produces identical output. |
stop | array | Up to 4 sequences where the API will stop generating tokens. |
stream | boolean | Stream partial responses as Server-Sent Events. |
temperature | number | Sampling temperature; higher values produce more random output. 0 is deterministic. |
tool_choice | one of | Controls which (if any) tool is called: "none", "auto", "required", or a specific tool. |
tools | array | List of tools (functions) the model may call. |
top_p | number | Nucleus sampling: consider only tokens whose cumulative probability ≥ top_p. |
Standard OpenAI-compatible parameters. Consult the provider docs for model-specific behaviour.
Benchmark Scores
| Benchmark | Score |
|---|---|
| MMLU | 84.9% |
| MATH-500 | 97.3% |
| GPQA Diamond | 71.5% |
| HumanEval | 92.9% |
| SWE-bench Verified | 49.2% |
Performance
30
tok / sec
output speed
Source: DeepSeek R1 paper + Artificial Analysis, April 2026
Strengths & Limitations
Best For
Open-weight reasoning model with visible CoT
o1-level math and science
MIT licence
13K HuggingFace likes / 3.5M downloads
Distilled smaller variants available (7B–70B)
Limitations
Large 671B total deployment requirement
No vision modality
Longer latency due to reasoning steps
No tool/function calling
Tags
Open WeightsReasoningThinkingMathCodingMoE