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GPT-OSS 20B TEE

TEE/gpt-oss-20b
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GPT-OSS 20B TEE

TEE/gpt-oss-20b

Open-source GPT model with 21B parameters (3.6B active) using MoE architecture. Running inside a TEE (Trusted Execution Environment), with provider attestation support.

Context Window

131.1K

Max Output

8.2K

Avg output tokens (7d)

75 tokens

4%

Input Price (Auto)

$0.040/1M

Output Price (Auto)

$0.15/1M

Cache Read (Auto)

$0.020/1M

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

9.0

Better than 38% of models compared

Coding Index

20.7

Better than 24% of models compared

Agentic work

AutomationBench-AA

Workflow automation with guardrail penalties

0.2%

Better than 2% of models compared

AA-Briefcase

Agentic knowledge work (Elo)

0 Elo

Better than 2% of models compared

GDPval-AA v2

Economically valuable tasks (Elo)

514 Elo

Better than 22% of models compared

Document reasoning

GDP.pdf

Professional PDF reasoning: all-pass rate

2.0%

Better than 19% of models compared

AA-LCR v1.1

Long context reasoning with updated grading

34.7%

Better than 35% of models compared

Reasoning

HLE

Humanity's Last Exam

11.0%

Better than 57% of models compared

IFBench

Instruction-following benchmark

65.1%

Better than 77% of models compared

Coding

Terminal-Bench v4.0

Practical coding and terminal tasks

0.0%

Better than 17% of models compared

SciCode

Python programming for scientific computing

38.9%

Better than 24% of models compared

LiveCodeBench

Contamination-free coding benchmark

77.7%

Better than 89% of models compared

Math

AIME 2025

American Invitational Mathematics Examination 2025

89.3%

Better than 88% of models compared

Knowledge

MMLU-Pro

Professional and academic subject knowledge

74.8%

Better than 47% of models compared

Legacy benchmarks

GPQA Diamond (legacy)

Graduate-level scientific reasoning

68.8%

Better than 46% of models compared

Terminal-Bench Hard (legacy)

Agentic coding and terminal use

10.6%

Better than 45% of models compared

T²-Bench Telecom (legacy)

Conversational AI agents in dual-control scenarios

60.2%

Better than 57% of models compared

AA-LCR (unversioned / legacy)

Long context reasoning evaluation

34.7%

Better than 35% of models compared

Last updated Sep 13, 2026

Artificial Analysis

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