Benchmark Almanac

Step-SWE-Bench

Step 3.7 Flash 67.1% Fading

Models fix software issues inside several coding agent harnesses, such as Claude Code, OpenCode and Hermes Agent. The score is the average over harnesses.

StepFun calls it in-house. The post gives per-harness scores for six harnesses and does not describe the tasks.

Made by StepFun Released May 2026 Fixing real repositories Tasks kept private Last in a launch post May 2026 , dropped before it saturated Last model added May 2026
Level
Expert Specialists with years of training, often over hours of work
Scored
Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
Answers
Agent task Many steps in a terminal, browser, desktop, app, game or robot.
1
Model scored in lab cards
1
Launch post lists it, from 1 lab

Step 3.7 Flash leads with 67.1%

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

  1. 1 Step 3.7 Flash 67.1%
#ModelScoreSettingDateSource
1 Step 3.7 Flash 67.1% May 2026 Model card

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

Reported by the lab in its model card
0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Step 3.7 Flash 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Step 3.7 Flash

Labs headline it less often now, last in May 2026

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

StepFun
DateLaunch postScoreAs the post writes it
29 May 2026 Step 3.7 Flash 67.1 Step-SWE-Bench avg over six harnesses

More in Coding

All 243 in Coding
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  • SWE-bench Multilingual In use 300 GitHub-issue tasks across nine programming languages in SWE-bench format. Patch graded by repository tests. Claude Opus 5.5 93.9%
  • LiveCodeBench v6 In use Competitive programming problems collected after model cutoffs from LeetCode, AtCoder, Codeforces. Scored pass@1 on hidden tests. DeepSeek-V4-Pro 93.5%
  • DeepSWE In use 113 original long-horizon engineering tasks across 91 repos and five languages, written from scratch. Hand-written verifiers accept alternative solutions. GPT-6 Astra 74.1%
  • SciCode In use Scientist-curated research coding problems split into subproblems across natural sciences. Code checked against test cases. Seed2.1 Pro 59.8%
  • Codeforces rating In use Model solves recent Codeforces contest problems. An Elo-style rating is computed from simulated contest performance. DeepSeek V4.1 Flash 3,471