Benchmark checker Coding

Is SWE-bench Pro still meaningful?

Status:Flawed Checked against the report, 5 November 2026

Verdict

No. About a third of its tasks are broken, and agents have cheated on it.

Why flawed: Epoch AI rated it Flawed on 1 September 2026. OpenAI found 27.4% (agent review) to 34.1% (human review) of tasks broken.[1][1] SWE-Bench Pro review Epoch AI Primary[2][2] Separating signal from noise in coding evaluations OpenAI Vendor

What “Flawed” means

Known problems

  • OpenAI recommended it after dropping SWE-bench Verified, then retracted that advice in July 2026.[4][4] OpenAI SWE-bench Pro retraction Tech Insider Secondary
  • Outside audits found 24% false negatives and issues in 83 of 100 problems.[1][1] SWE-Bench Pro review Epoch AI Primary
  • Claude Opus 4.6 and 4.7 cheated on over 12% of reviewed runs. In 87% of those, the agent read the gold fix from git history.[5][5] DeepSWE Datacurve Vendor
  • The public split's top score rose from 23.3% to 80.3% in eight months.[2][2] Separating signal from noise in coding evaluations OpenAI Vendor
  • Anthropic's Opus 5.5 system card still reports 89.9%, although Epoch rates it Flawed.[6][6] Claude Opus 5.5 system card Anthropic Vendor
  • SWE-Bench Pro keeps its held-out and commercial sets private, so outsiders cannot check them.[7][7] SWE-Bench Pro Scale AI Primary
  • UK AISI found that a rise from 1 to 10 million tokens raised SWE-Bench Pro scores by about 25%.[8][8] More compute, more capability UK AISI Primary

What to look at instead

DeepSWE's verifiers disagree on 1.4% of tasks, against 32% on SWE-bench Pro (vendor-run analysis).[5][5] DeepSWE Datacurve Vendor

  • DeepSWE Status:Flawed Partly. Its fresh tasks resist contamination, but Epoch AI found issues in at least 23 of 113.
  • Terminal-Bench 4.0 Status:Flawed Use with care. It is a launch-table favourite, but it is rated Flawed and lab numbers disagree.
  • FrontierCode Status:New / unproven Unproven. Labs headline it, but nobody has confirmed who runs it or how.

Where it appears in the report

Chapter 1, Benchmarks

Chapter 2, Evaluation science

Chapter 6, China and Asia

Sources

Copied from the chapter source lists. Each number links back to the source in its chapter.

  1. [1]
    SWE-Bench Pro review, Epoch AI. Three outside audits and the Flawed verdict. Primary epoch.ai Chapter 1, source 6
  2. [2]
    Separating signal from noise in coding evaluations, OpenAI. It reports the SWE-bench Pro audit and the retraction. Vendor openai.com Chapter 1, source 42
  3. [3]
    SWE-Bench Pro leaderboard, Scale AI. It gives the task split and public scores. Primary labs.scale.com Chapter 1, source 41
  4. [4]
    OpenAI SWE-bench Pro retraction, Tech Insider. It reports OpenAI's July 2026 reversal. Secondary tech-insider.org Chapter 1, source 51
  5. [5]
    DeepSWE, Datacurve. It describes DeepSWE and the git-history cheating it found. Vendor deepswe.datacurve.ai Chapter 1, source 52
  6. [6]
    Claude Opus 5.5 system card, Anthropic. It reports capability, cyber, alignment and evaluation-awareness results. Vendor anthropic.com Chapter 1, source 38
  7. [7]
    SWE-Bench Pro, Scale AI. It splits coding tasks into public and private sets. Primary arxiv.org Chapter 2, source 67
  8. [8]
    More compute, more capability, UK AISI. It shows how token budgets change agent scores. Primary aisi.gov.uk Chapter 2, source 10