DeepSeek V3.2 (thinking/reasoner mode) — official successor to V3.2-Exp. Reasoning-first model built for agents with GPT-5 level performance. Balanced inference vs. output length. First DeepSeek model with thinking-in-tool-use capability. FP8.
Added Dec 1, 2025
Model weightsContext Window
163.0K
Max Output
65.5K
Avg output tokens (7d)
1.6K tokens
Input Price (Auto)
$0.21/1M
Output Price (Auto)
$0.31/1M
Cache Read (Auto)
$0.022/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
32.8
Coding Index
44.2
Reasoning
GPQA Diamond
Graduate-level scientific reasoning
84.0%
Better than 78% of models compared
HLE
Humanity's Last Exam
24.6%
Better than 80% of models compared
IFBench
Instruction-following benchmark
60.7%
Better than 72% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
90.6%
Better than 85% of models compared
AA-LCR
Long context reasoning evaluation
70.7%
Better than 81% of models compared
GDPval-AA
Economically valuable tasks
18.3%
CritPt
Research-level physics reasoning
2.9%
Coding
SciCode
Python programming for scientific computing
38.9%
Better than 66% of models compared
Terminal-Bench Hard
Agentic coding and terminal use
35.6%
Better than 82% of models compared
LiveCodeBench
Contamination-free coding benchmark
86.2%
Better than 97% of models compared
Math
AIME 2025
American Invitational Mathematics Examination 2025
92.0%
Better than 94% of models compared
Knowledge
MMLU-Pro
Professional and academic subject knowledge
86.2%
Better than 95% of models compared
AA-Omniscience Accuracy
Proportion of correctly answered questions
33.0%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
82.7%
Last updated Aug 16, 2026
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