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Terminal-Bench

Choose a shared evaluation protocol to compare model scores. Versions, sources and configurations stay separate.

Atlas snapshot captured 10/19/2026, 10:20:28 AM UTC. This is an import timestamp, not the evaluation date. Coverage may be incomplete.

Reviewed recommendation and limits

Start with Terminal-Bench 4.0 for terminal-based agent work. Compare the same task release, agent and resource settings.

Terminal-Bench 4.0.0 on Harbor. Preserve agent, model, reasoning effort, task resources, trial count and resolution-rate uncertainty. Earlier 2.0, 2.1 and 3.0 results remain separate.. Imported groups below may use different protocols; this review does not certify each run. Public solutions, reward hacking and task-specific tuning can inflate results. Earlier editions and vendor-reported runs do not establish the current reviewed protocol. Terminal completion is different from repository issue repair.

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terminal-bench-2.1 · terminalbench 2 1

Source
Hugging Face eval result
Version
2.1
Measurement date
2026-08-31
Metric
% · Higher is better
Evaluation scope
Registered model evaluation · Model Card

Positions are withheld because at least one result lacks explicit independent provenance or a documented evaluation scope. Missing metadata is shown as unreported; matching imported metadata is not independent verification of the protocol.

  1. GLM 5.3

    z-ai/glm-5.3-20260816

    88.2%

    View modelEvidence Evidence class unreported
  2. Hy4 preview

    tencent/hy4-preview-20260827

    85.4%

    View modelEvidence Evidence class unreported
  3. DeepSeek V4 Flash Vision Exp

    deepseek/deepseek-v4-flash-vision-exp-20260821

    83.9%

    View modelEvidence Evidence class unreported
  4. Granite 4.2 30B

    ibm-granite/granite-4.2-30b

    29.2%

    View modelEvidence Evidence class unreported
  5. Granite 4.2 8B

    ibm-granite/granite-4.2-8b-20260831

    20.6%

    View modelEvidence Evidence class unreported
Terminal-Bench model results | VibeLeaderboard