DeepSeek V4 Pro 0813 is the general-availability release of DeepSeek V4 Pro, built for coding, tool use, cybersecurity, automation, and long-horizon agent workflows. DeepSeek reports strong gains over the preview and scores above Opus 4.8 on Terminal Bench 2.1, Cybergym, DeepSWE, and AutomationBench. It supports a 1M-token context window.
Added Aug 12, 2026
Model weightsContext Window
1.0M
Max Output
384.0K
Input Price (Auto)
$0.53/1M
Output Price (Auto)
$1.60/1M
Cache Read (Auto)
$0.017/1M
Capabilities
Benchmarks
Benchmarks
Performance metrics and benchmarks
Sourced from Artificial Analysis.
Intelligence Index
36.0
Coding Index
68.8
Agentic Index
41.3
Agentic work
AutomationBench-AA
Workflow automation with guardrail penalties
56.7%
Better than 84% of models compared
AutomationBench-AA Tasks Completed
Fully completed workflows without guardrail violations
25.9%
Better than 47% of models compared
AA-Briefcase
Agentic knowledge work (Elo)
1261 Elo
Better than 71% of models compared
GDPval-AA v2
Economically valuable tasks (Elo)
1441 Elo
Better than 83% of models compared
Document reasoning
GDP.pdf
Professional PDF reasoning: all-pass rate
11.4%
Better than 50% of models compared
AA-LCR v1.1
Long context reasoning with updated grading
80.3%
Better than 90% of models compared
MLCR-AA
Medical long-context reasoning
17.8%
Better than 63% of models compared
Reasoning
HLE
Humanity's Last Exam
41.0%
Better than 91% of models compared
CritPt
Research-level physics reasoning
18.0%
Coding
Terminal-Bench v4.0
Practical coding and terminal tasks
14.1%
Better than 75% of models compared
SciCode
Python programming for scientific computing
51.0%
Better than 63% of models compared
Knowledge
AA-Omniscience Accuracy
Proportion of correctly answered questions
49.1%
AA-Omniscience Hallucination Rate
Rate of incorrect answers among non-correct responses
94.8%
Legacy benchmarks
GPQA Diamond (legacy)
Graduate-level scientific reasoning
92.8%
Better than 95% of models compared
AA-LCR (unversioned / legacy)
Long context reasoning evaluation
80.3%
Better than 90% of models compared
GDPval-AA (unversioned / legacy)
Economically valuable tasks
47.1%
Last updated Sep 21, 2026
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