DeepSeek V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. Running inside a TEE (Trusted Execution Environment), with provider attestation support.
Context Window
164.0K
Max Output
65.5K
Avg output tokens (7d)
470 tokens
Input Price (Auto)
$0.50/1M
Output Price (Auto)
$1.00/1M
Cache Read (Auto)
$0.25/1M
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
18.3
Reasoning
GPQA Diamond
Graduate-level scientific reasoning
75.1%
Better than 57% of models compared
HLE
Humanity's Last Exam
11.2%
Better than 58% of models compared
IFBench
Instruction-following benchmark
49.0%
Better than 58% of models compared
T²-Bench Telecom
Conversational AI agents in dual-control scenarios
78.9%
Better than 69% of models compared
AA-LCR
Long context reasoning evaluation
45.7%
Better than 44% of models compared
Coding
Terminal-Bench Hard
Agentic coding and terminal use
32.6%
Better than 76% of models compared
LiveCodeBench
Contamination-free coding benchmark
59.3%
Better than 66% of models compared
Math
AIME 2025
American Invitational Mathematics Examination 2025
59.0%
Better than 56% of models compared
Knowledge
MMLU-Pro
Professional and academic subject knowledge
83.7%
Better than 86% of models compared
Last updated Sep 7, 2026
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