DeepSeek's R1 is a thinking model, scoring very well on all benchmarks at low cost. This version runs on open-source providers and never sends requests to DeepSeek directly.
Added May 28, 2025
Model weightsContext Window
128.0K
Max Output
8.2K
Avg output tokens (7d)
1.3K tokens
Input Price (Auto)
$0.42/1M
Output Price (Auto)
$1.78/1M
Cache Read (Auto)
$0.21/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
20.1
Coding Index
24.6
Agentic Index
3.1
Reasoning
GPQA Diamond
Graduate-level scientific reasoning
81.3%
Better than 79% of models compared
HLE
Humanity's Last Exam
14.9%
Better than 77% of models compared
IFBench
Instruction-following benchmark
39.6%
Better than 39% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
36.5%
Better than 45% of models compared
AA-LCR
Long context reasoning evaluation
54.7%
Better than 67% of models compared
GDPval-AA
Economically valuable tasks
1.4%
CritPt
Research-level physics reasoning
0.6%
Coding
SciCode
Python programming for scientific computing
40.3%
Better than 78% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
15.9%
Better than 54% of models compared
LiveCodeBench
Contamination-free coding benchmark
77.0%
Better than 88% of models compared
Math
AIME 2025
American Invitational Mathematics Examination 2025
76.0%
Better than 71% of models compared
AIME
American Invitational Mathematics Examination
89.3%
Better than 95% of models compared
Math-500
Diverse mathematical problem solving benchmark
98.3%
Better than 94% of models compared
Knowledge
MMLU-Pro
Professional and academic subject knowledge
84.9%
Better than 90% of models compared
AA-Omniscience Accuracy
Proportion of correctly answered questions
30.5%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
90.3%
Last updated Jun 28, 2026
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