datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SWEbench-Verified-eval150-M2.7-Qwen3.5-9B-orch-7arms-2repeats-w32-20260920
SWE-bench Verified eval150 — M2.7 × Qwen3.5-9B, seven arms, two repeats, 32 concurrency
Campaign 2026-09-20. 14/14 independent full150 runs audited. Complete accuracy evidence.
Evaluation mode is orch: MiniMax-M2.7 orchestrator and the specified Qwen3.5-9B worker. Training mode is labeled independently. All runs use 32 concurrent episodes, 10GiB Docker sandboxes, four TP1 workers and one TP4/EP4 coordinator. Frozen regression-gated prompts, decoding and canonical verifier match… See the full description on the dataset page: https://huggingface.co/datasets/CharlieLLL/SWEbench-Verified-eval150-M2.7-Qwen3.5-9B-orch-7arms-2repeats-w32-20260920.qwen9b-coop-claude-code
qwen9b-coop-claude-code
Two-agent cooperative coding trajectories generated by running
CooperBench in coop mode on
the CooperData task set, using
Qwen/Qwen3.5-9B as the model and Claude Code (claude_code) as the
agent framework. Each pair runs two agents in parallel — one per feature —
coordinating via Redis messaging and a shared git remote.
The matched solo (single-agent) baseline is at
CooperBench/qwen9b-solo-claude-code.
Same task corpus, same model, same agent — only the… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen9b-coop-claude-code.qwen9b-solo-claude-code
qwen9b-solo-claude-code
Single-agent coding trajectories generated by running
CooperBench in solo mode on
the CooperData task set, using
Qwen/Qwen3.5-9B as the model and Claude Code (claude_code) as the
agent framework. One agent implements both features in each task.
The matched coop (two-agent) version is at
CooperBench/qwen9b-coop-claude-code.
Same task corpus, same model, same agent — only the coordination differs, so
together they isolate the cooperation deficit.
At a… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen9b-solo-claude-code.qwen9b-coop-mini-swe-agent
qwen9b-coop-mini-swe-agent
Two-agent cooperative coding trajectories generated by running
CooperBench in coop mode on
the CooperData task set, using
Qwen/Qwen3.5-9B as the model and mini_swe_agent_v2 as the agent framework.
Each pair runs two agents in parallel — one per feature — coordinating via Redis messaging and a shared git remote.
The matched solo version is at
CooperBench/qwen9b-solo-mini-swe-agent.
Same task corpus, same model, same agent — only the coordination differs… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen9b-coop-mini-swe-agent.qwen9b-solo-mini-swe-agent
qwen9b-solo-mini-swe-agent
Single-agent coding trajectories generated by running
CooperBench in solo mode on
the CooperData task set, using
Qwen/Qwen3.5-9B as the model and mini_swe_agent_v2 as the agent framework.
One agent implements both features in each task.
The matched coop version is at
CooperBench/qwen9b-coop-mini-swe-agent.
Same task corpus, same model, same agent — only the coordination differs, so
together they isolate the cooperation deficit.
At a glance… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen9b-solo-mini-swe-agent.diffing-stats-gemma-2-9b-it-L20-k100-lr1e-04-Crosscoderqwen35-9b-plan-first-coop
What this is
Cooperative two-agent coding dataset: 211 task pairs across 18 repos, generated with
mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using a plan-first prompt variant —
agents are prompted to produce an explicit implementation plan before writing code, then coordinate
to reconcile plans before proceeding. Patches are auto-merged after both submit.
At a glance
Field
Value
Model
Qwen/Qwen3.5-9B
Agent
mini_swe_agent (plan-first prompt)… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-plan-first-coop.qwen35-9b-git-coop
What this is
Cooperative two-agent coding dataset: 211 task pairs across 18 repos, generated with
mini_swe_agent on Qwen/Qwen3.5-9B in coop setting with a shared read-only git remote (--git).
Agents coordinate via messaging and git fetch team; patches are auto-merged after both submit.
At a glance
Field
Value
Model
Qwen/Qwen3.5-9B
Agent
mini_swe_agent (step_limit=300)
Setting
coop + git remote
Repos
18
Pairs
211
Both-pass
5.7% (12/210… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-git-coop.diffing-stats-gemma-2-9b-it-L20-mu1.0e-01-lr1e-04-local-shuffling-CrosscoderLossdiffing-stats-gemma-2-9b-it-DPO-L20-k100-lr1e-04-dpo-simpo-Crosscoderqwen35-9b-question-first-coop-random-50
What this is
Cooperative two-agent coding dataset: 49 task pairs across 15 repos (random-50 subset), generated
with mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using a question-first prompt variant —
agents begin by asking each other clarifying questions about their respective features before
starting implementation, aiming to surface integration concerns early. All 49 pairs were
successfully evaluated.
At a glance
Field
Value
Model… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-question-first-coop-random-50.minor-pool-9b57ec
minor-pool-9b57ec
Synthetic sensors test data: 55 rows in data.csv.
All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations.
Fields
sample_id: random identifier for this generated sample.
row_id: sequential row number starting at 1.… See the full description on the dataset page: https://huggingface.co/datasets/MaryGonzalez/minor-pool-9b57ec.qwen35-9b-explore-plan-coop
What this is
Cooperative two-agent coding dataset: 209 task pairs across 18 repos, generated with
mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using an explore-plan prompt variant —
agents explore the codebase first, then produce an explicit implementation plan, then share and
reconcile plans with their partner before writing code. Patches are auto-merged after both submit.
At a glance
Field
Value
Model
Qwen/Qwen3.5-9B
Agent
mini_swe_agent… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-explore-plan-coop.qwen35-9b-milestone-checkins-coop
What this is
Cooperative two-agent coding dataset: 211 task pairs across 18 repos, generated with
mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using a milestone-checkins prompt variant —
agents use periodic structured check-ins at predefined milestones to coordinate progress and
surface integration conflicts early. Patches are auto-merged after both submit.
Coverage caveat: Only 146 of 211 pairs were successfully evaluated (65 had eval errors).
The high agent Error rate… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-milestone-checkins-coop.qwen35-9b-contract-first-coop-random-50
What this is
Cooperative two-agent coding dataset: 36 task pairs across 13 repos (random-50 subset), generated
with mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using a contract-first prompt variant —
agents first agree on a shared interface contract (function signatures, data structures, API
boundaries) before independently implementing their respective features. All 36 pairs were
successfully evaluated.
At a glance
Field
Value
Model… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-contract-first-coop-random-50.qwen9b-coop-claude-code-compressed
qwen9b-coop-claude-code-compressed-ak
Synthetic compressed cooperative agent trajectories derived from
CooperBench/qwen9b-coop-claude-code.
Each raw pair (two LLM coding agents on overlapping features in the same
repo, communicating via Redis messaging + a team git remote) is condensed
into an idealized version: wasted steps dropped, broken submission rituals
fixed, missing cooperation events (coop-send/coop-broadcast/coop-recv,
git fetch/diff team) inserted where the real pair… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen9b-coop-claude-code-compressed.qwen35-9b-late-sync-coop-random-50
What this is
Cooperative two-agent coding dataset: 48 task pairs across 15 repos (random-50 subset), generated
with mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using a late-sync prompt variant —
agents work independently for most of the task and synchronise only at a late stage before
submission. Patches are auto-merged after both submit. All 48 pairs were successfully evaluated.
At a glance
Field
Value
Model
Qwen/Qwen3.5-9B
Agent
mini_swe_agent… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-late-sync-coop-random-50.diffing-stats-gemma-2-9b-L20-k100-lr1e-04-base-it-Crosscoderbefore-during-after-b703f136-4fb7-4603-9bee-9ca01138bcfdqwen35-9b-reasoning-share-coop-random-50
What this is
Cooperative two-agent coding dataset: 50 task pairs across 15 repos (random-50 subset), generated
with mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using a reasoning-share prompt variant —
agents share their internal reasoning and analysis with each other before and during implementation,
giving each agent visibility into the other's thought process to improve integration. All 50 pairs
were successfully evaluated.
At a glance
Field
Value… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-reasoning-share-coop-random-50.diffing-stats-gemma-2-9b-L20-k100-lr1e-04-Crosscoderqwen35-9b-leader-follower-coop
What this is
Cooperative two-agent coding dataset: 39 task pairs across 14 repos (random-50 subset), generated
with mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using a leader-follower prompt variant —
one agent is designated as leader and sets the coordination strategy; the other acts as follower
and adapts its implementation plan accordingly. All 39 pairs were successfully evaluated.
Notable: this variant produced the lowest merge conflict rate (17.9%) of all random-50… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-leader-follower-coop.qwen35-9b-async-coop
What this is
Cooperative two-agent coding dataset: 50 task pairs across 15 repos (random-50 subset), generated
with mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using an async prompt variant —
agents work fully asynchronously without active coordination (no messaging, no synchronisation
points). Patches are auto-merged after both submit. All 50 pairs were successfully evaluated.
At a glance
Field
Value
Model
Qwen/Qwen3.5-9B
Agent
mini_swe_agent… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-async-coop.equake-a0700949-bff4-49a9-9b97-d81e057a9066diffing-stats-gemma-2-9b-L20-k100-lr1e-04-base-dpo-Crosscoderdiffing-stats-gemma-2-9b-it-L20-k100-lr1e-04-CCLossqwen35-9b-test-impl-split-coop
What this is
Cooperative two-agent coding dataset: 48 task pairs across 15 repos (random-50 subset), generated
with mini_swe_agent on Qwen/Qwen3.5-9B in coop setting using a test-impl-split prompt variant —
one agent is assigned the role of writing tests; the other writes the implementation. The two
patches cover non-overlapping files, which eliminates merge conflicts entirely.
Key finding: This variant achieves a 100% clean merge rate (0 conflicts across all 48 pairs),
but a 0%… See the full description on the dataset page: https://huggingface.co/datasets/CooperBench/qwen35-9b-test-impl-split-coop.diffing-stats-gemma-2-9b-it-SimPO-L20-mu1.0e-01-lr1e-04-CrosscoderLossdiffing-stats-gemma-2-9b-it-L20-mu4.0e-02-lr1e-04-CrosscoderLoss