Atlas

Benchmarks

Longtail-SWE

Longtail Swe

Longtail-SWE (Nebius, the SWE-rebench team) asks coding agents to resolve real GitHub issues in 13 programming languages that existing issue-resolution benchmarks barely cover: Clojure, Dart, Elixir, Erlang, F#, Haskell, Julia, Kotlin, Lua, OCaml, R, Scala and Swift. Its 202 tasks from 129 repositories each come from an issue and its merged pull request, with a Docker environment and tests; a solver-judge-repairer pipeline revised descriptions and tests that rejected valid solutions or accepted wrong ones, and tasks that Qwen 3.8 27B solved in all three calibration attempts were generally dropped. An attempt succeeds only when every fail-to-pass and pass-to-pass test passes. Pass@1, the headline, is the success rate over three attempts per task. Scores are for a model in the authors' SWE-agent-like scaffold, not for the model alone.

Models
7
Top score
81.5
Leader
Claude Opus 5.5
Updated
Nov 6, 2026
Resolution
—
Saturation
—

No signal or difficulty estimate. Too few models have been measured on this benchmark to estimate its difficulty.

Organizations
7 dated models · 3 frontier modelsClosed weightsOpen weights
Data: Nebiusatlas.village.dev
#ModelSettingScoreSource
1Claude Opus 5.5high · SWE-rebench swelike scaffold; 1M context
81.5
2GPT-6.1 Solhigh · SWE-rebench swelike scaffold; 1M context
78.4
3GPT-5.6 Solhigh · SWE-rebench swelike scaffold; 1M context
75.7
4GPT-5.6 Lunax-high · SWE-rebench swelike scaffold; 1M context
71.5
5Kimi K3max · SWE-rebench swelike scaffold; 262K context
63.7
6GLM-5.3 Flashnot reported · SWE-rebench swelike scaffold; 262K context
48.2
7Qwen3.6 27Bthinking · SWE-rebench swelike scaffold; 262K context
16.7
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