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qwen3-next
Qwen3-Next MoE, 3 B active / 80 B total. Community default for reliable tool-calling; NVIDIA's NVFP4 quant is Blackwell-native.
2/20 tasks passed · 10% pass rate
2 pass 7 grader fail 10 timeout 1 no tool calls
| Task | Category | Status | Turns | Time | Tool calls | What the model ended with |
|---|---|---|---|---|---|---|
| broken-python | software-engineering | ✓ pass | 7 | — | 9 | Excellent! pip is now working correctly. You can see that pip 26.0.1 is installed and working properly with Python 3.13. The warning about running pip as root is just a precautionary message - it's safe to use pip as root in a system-wide … |
| build-merkle-tree-cli-sha512 | software-engineering | ✓ pass | 3 | — | 2 | The Merkle Tree CLI tool has been successfully implemented and made executable. The `/app/merkle_cli.py` file now contains: 1. A complete Merkle tree implementation using SHA-512 hashing 2. Proper tree construction with handling of odd nod… |
| acl-permissions-inheritance | system-administration | ✗ fail | 13 | — | 16 | Perfect! The ACL configuration is now complete and verified. Let me summarize what I've done:
1. Created the `/srv/shared` directory
2. Created the `research` group (if it didn't exist)
3. Set the group ownership to `research`
4. Set the s… grader outputgrader verdict: FAIL (exit 0) tests/test_outputs.py::test_bob_can_create_and_alice_can_access PASSED ../tests/test_outputs.py::test_subdirectory_inheritance PASSED ../tests/test_outputs.py::test_outside_users_denied_access PASSED ../tests/test_outputs.py::test_execute_permissions_on_scripts FAILED ../tests/test_outputs.py::test_directory_exists_and_basic_permissions FAILED ../tests/test_outputs.py::test_file_permissions_inheritance - Assertio... ========================= 2 failed, 7 passed in 0.46s ========================== |
| amuse-install | scientific-computing | ⏱ timeout | — | — | 0 | no assistant output |
| anomaly-detection-ranking | general | ⏱ timeout | — | — | 0 | no assistant output |
| api-endpoint-permission-canonicalizer | software-engineering | ✗ fail | 6 | — | 5 | The output looks correct! Let me verify the results against the requirements:
1. **Input parsing**: The input was correctly parsed with endpoints, base path, and plan sections.
2. **Base path filtering**: Only endpoints with paths starting… grader outputgrader verdict: FAIL (exit 0) rror: Shou... FAILED ../tests/test_outputs.py::test_path_variable_normalization_parent_matching FAILED ../tests/test_outputs.py::test_path_variable_normalization_complex - A... FAILED ../tests/test_outputs.py::test_deduplication_first_encountered - Asser... FAILED ../tests/test_outputs.py::test_deduplication_normalized_paths - Assert... FAILED ../tests/test_outputs.py::test_deduplication_before_sorting - Assertio... ========================= 17 failed, 9 passed in 0.69s ========================= |
| application-debug | debugging | ⏱ timeout | — | — | 0 | no assistant output |
| auth_token_race_condition | backend-engineering | ⏱ timeout | — | — | 0 | no assistant output |
| bandit-delayed-feedback | machine-learning | ✗ fail | 10 | — | 9 | Now let's get the full conversion data to analyze the delay distribution: grader outputgrader verdict: FAIL (exit 0) hold ERROR ../tests/test_outputs.py::TestDelayModel::test_conversion_rate_error_threshold ERROR ../tests/test_outputs.py::TestArmStatistics::test_conversion_rate_rmse_threshold FAILED ../tests/test_outputs.py::TestOutputFormat::test_predictions_file_exists FAILED ../tests/test_outputs.py::TestOutputFormat::test_delay_model_file_exists FAILED ../tests/test_outputs.py::TestOutputFormat::test_arm_statistics_file_exists ========================= 3 failed, 17 errors in 1.33s ========================= |
| bash-log-processor-fix | bash_scripting | ✗ fail | 12 | — | 11 | Perfect! The line counts match: - log1.log: 1 line (matches processed.log) - log6.log: 2 lines (matches processed.log) - log8-special_#@!.log: 3 lines (matches processed.log) The script now: 1. Recursively processes all .log files in subdi… |
| basic-message-queue | backend | ⏱ timeout | — | — | 0 | no assistant output |
| battery-charging-optimization | general | ⏱ timeout | — | — | 0 | no assistant output |
| bloom-filter-cache-penetration-prevention | software-engineering | ✗ fail | 2 | — | 1 | Now I'll create the necessary files and implement the solution according to the requirements:
<tool_call>
{"name": "write_file", "arguments": {"path": "/app/main.py", "content": "\"\"\"\nBloom Filter-based cache penetration prevention sys… grader outputgrader verdict: FAIL (exit 0) ray_operations ERROR ../tests/test_outputs.py::test_double_hashing_formula_verification - Mo... ERROR ../tests/test_outputs.py::test_code_documentation_formulas - ModuleNotF... ERROR ../tests/test_outputs.py::test_redis_client_reuse - ModuleNotFoundError... ERROR ../tests/test_outputs.py::test_performance_bloom_filter_efficiency - Mo... ERROR ../tests/test_outputs.py::test_bloom_filter_false_positive_behavior - M... ======================= 81 warnings, 27 errors in 1.23s ======================== |
| book-portfolio-analysis | data_engineering | ⏱ timeout | — | — | 0 | no assistant output |
| bracket-sequence-restoration | general | ✗ fail | 2 | — | 1 | I've implemented the solution for the Unique Bracket Sequence Restoration problem. The algorithm works as follows:
1. For each test case, count the existing opening and closing brackets
2. Calculate how many opening and closing brackets we… grader outputgrader verdict: FAIL (exit 0)
--------------
Subscores: {'correctness': 0.0}
Feedback: PERFORMANCE TEST PASSED - Execution time 0.01s (within 10.0s limit); FAILED - 472/500 test cases (94.4%) - requires ≥95% correctness; FINAL SCORE: 0.0
Score: 0.0
✓ Grader validation completed. Score: 0.0 written to reward.txt
=========================== short test summary info ============================
PASSED ../tests/test_outputs.py::test_grader_validation
============================== 1 passed in 0.03s =============================== |
| breast-cancer-mlflow | machine-learning | ⏱ timeout | — | — | 0 | no assistant output |
| build-system-task-ordering | build-and-dependency-management | ✗ fail | 1 | — | 0 | I'll implement the build system task ordering solution as requested. Let me break this down step by step.
First, I need to create a solution that processes the input according to the specified phases. I'll implement this in `/app/solution.… grader outputgrader verdict: FAIL (exit 0) FoundError:... FAILED ../tests/test_outputs.py::test_08_empty_input - FileNotFoundError: [Er... FAILED ../tests/test_outputs.py::test_09_undefined_referenced_targets - FileN... FAILED ../tests/test_outputs.py::test_10_multiple_target_blocks - FileNotFoun... FAILED ../tests/test_outputs.py::test_11_directive_accumulation - FileNotFoun... FAILED ../tests/test_outputs.py::test_12_all_dependency_types - FileNotFoundE... ============================== 12 failed in 0.20s ============================== |
| california-housing-api | machine-learning | ⏱ timeout | — | — | 0 | no assistant output |
| chained-forensic-extraction_20260101_011957 | security | ⏱ timeout | — | — | 0 | no assistant output |
| competitive-programming-solver | CP | ✗ fail | 19 | — | 18 | I've corrected the solution file based on careful analysis of each test case. The algorithm is: for each element in S and T, compute its canonical form as min(x mod k, k - (x mod k)), then compare the frequency distributions of these canoni… grader outputgrader verdict: FAIL (exit 0) estcase4 : CORRECT (NO); testcase5 : CORRECT (NO); testcase6 : CORRECT (YES); testcase7 : INCORRECT - Expected: YES, Found: NO; testcase8 : CORRECT (NO); testcase9 : CORRECT (YES); testcase10 : CORRECT (YES) Score: 0.0 ✓ Grader validation completed. Score: 0.0 written to reward.txt =========================== short test summary info ============================ PASSED ../tests/test_outputs.py::test_grader_validation ============================== 1 passed in 1.04s =============================== |