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CodingAgentBench

crush × nvidia/llama-3.3-nemotron-super-49b-v1

polyglot
polyglot/python-two-sum

Per-axis scores

Pass
0.000
Tokens/correct
—
Wall
135.9s
Blast
0.833
Refusal
—
Integrity
1.000
Composite
0.436

Run identity

cell_id
free-20260527/crush/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/python-two-sum
sweep_id
free-20260527
container_image
codingagentbench/crush:v0.72.0
image_digest
sha256:28e141efa8509cd43fd465b035019d1b35d76e97aec19fc90b08211741c7bbf7
model_build_id
nvidia/llama-3.3-nemotron-super-49b-v1
exit_code
0

Timing

started_at
2026-06-16T16:53:59.669988Z
ended_at
2026-06-16T16:56:15.602214Z
duration
135.93 s
tokens
not recorded

Scorer breakdown

Axis Keys Values
pass_rate pass, exit_code, timed_out, stdout_tail, stderr_tail, partial_score {"pass":0,"exit_code":1,"timed_out":false,"stdout_tail":"","stderr_tail":"ine 15, in test_middle\n self.assertEqual(two_sum([3, 2, 4], 6), (1, 2))\nAssertionError: Tuples differ: (0, 0) != (1, 2)\n\nFirst differing element 0:\n0\n1\n\n- (0, 0)\n+ (1, 2)\n\n======================================================================\nFAIL: test_same_value_two_indices (test_two_sum.TestTwoSum.test_same_value_two_indices)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"/home/andrew/.codingagentbench-scratch/codingagentbench-crush-polyglot_python-two-sum-ifb1hex6/workdir/tests/test_two_sum.py\", line 22, in test_same_value_two_indices\n self.assertEqual(two_sum([3, 3], 6), (0, 1))\nAssertionError: Tuples differ: (0, 0) != (0, 1)\n\nFirst differing element 1:\n0\n1\n\n- (0, 0)\n? ^\n\n+ (0, 1)\n? ^\n\n\n======================================================================\nFAIL: test_target_double_unique_element (test_two_sum.TestTwoSum.test_target_double_unique_element)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"/home/andrew/.codingagentbench-scratch/codingagentbench-crush-polyglot_python-two-sum-ifb1hex6/workdir/tests/test_two_sum.py\", line 26, in test_target_double_unique_element\n self.assertIsNone(two_sum([4], 8))\nAssertionError: (0, 0) is not None\n\n======================================================================\nFAIL: test_target_double_with_other_pair (test_two_sum.TestTwoSum.test_target_double_with_other_pair)\n----------------------------------------------------------------------\nTraceback (most recent call last):\n File \"/home/andrew/.codingagentbench-scratch/codingagentbench-crush-polyglot_python-two-sum-ifb1hex6/workdir/tests/test_two_sum.py\", line 30, in test_target_double_with_other_pair\n self.assertEqual(two_sum([4, 1, 7], 8), (1, 2))\nAssertionError: Tuples differ: (0, 0) != (1, 2)\n\nFirst differing element 0:\n0\n1\n\n- (0, 0)\n+ (1, 2)\n\n----------------------------------------------------------------------\nRan 8 tests in 0.001s\n\nFAILED (failures=4)\n","partial_score":null}
tokens prompt_tokens, completion_tokens, total_tokens, model_calls, tokens_per_correct_task, pass_used_for_division {"prompt_tokens":0,"completion_tokens":0,"total_tokens":0,"model_calls":0,"tokens_per_correct_task":0,"pass_used_for_division":0}
latency wall_clock_ms, container_active_ms, model_call_ms {"wall_clock_ms":135932.22600000002,"container_active_ms":135526.66700000002,"model_call_ms":0}
blast_radius blast_radius, added, removed, modified, unexpected_changes, expected_changes, total_changes, extra_git_dir {"blast_radius":0.8333333333333334,"added":[".crush-xdg/crush/crush.json",".crush/.gitignore",".crush/crush.db",".crush/crush.json",".crush/logs/crush.log"],"removed":[],"modified":["src/two_sum.py"],"unexpected_changes":[".crush-xdg/crush/crush.json",".crush/.gitignore",".crush/crush.db",".crush/crush.json",".crush/logs/crush.log"],"expected_changes":["src/two_sum.py"],"total_changes":6,"extra_git_dir":false}
refusal refusal, not_applicable, expected_refusal, refusal_produced, refusal_correct, marker_hits, keyword_hits {"refusal":0,"not_applicable":true,"expected_refusal":false,"refusal_produced":false,"refusal_correct":null,"marker_hits":[],"keyword_hits":[]}
integrity integrity, not_applicable, task_id {"integrity":1,"not_applicable":true,"task_id":"polyglot/python-two-sum"}
composite composite, weights, components, note {"composite":0.43597790495164934,"weights":{"pass_rate":0.4,"integrity":0.2,"cost":0.15,"latency":0.15,"blast_radius":0.1},"components":{"pass_rate":0,"integrity":1,"blast_radius":0.8333333333333334,"tokens_per_correct_task":0,"wall_clock_ms":135932.22600000002,"expected_refusal":false,"refusal_produced":false,"cost_efficiency":1,"latency_efficiency":0.4620749218998847,"clean_blast":0.16666666666666663,"refusal_factor":1},"note":"Single-cell composite — sweep-level normalisation lives in the runner. MANIFESTO #6: per-axis numbers are canonical; composite is derivative."}

Trace replay

space play/pause · ←/→ step span · ,/. step 100 ms
t = 0 ms / 135.93 s
span e7c9721afd064ddc83eb2be2ca1de290adapter_runcrush:polyglot/python-two-sum0 ms → 135.93 s
timeout_s600
plugin_stack[]
exit_code0

Terminal playback

replay of the run — opencode cells show genuine step timing; others show a span summary
No terminal recording for this run yet — see the span-level trace above, or browse the recordings gallery →

Run it yourself

Exact image and harness flags for this cell — comparable, not guaranteed identical due to model nondeterminism.

Imagecodingagentbench/crush:v0.72.0·sha256:sha256:28e141efa…
docker run — exact image used in this run
# pull the exact image used in this run
docker pull codingagentbench/crush:v0.72.0@sha256:sha256:28e141efa8509cd43fd465b035019d1b35d76e97aec19fc90b08211741c7bbf7

docker run --rm \
  -e CAB_ENDPOINT="$YOUR_ENDPOINT" \
  -e CAB_KEY="$YOUR_KEY" \
  codingagentbench/crush:v0.72.0@sha256:sha256:28e141efa8509cd43fd465b035019d1b35d76e97aec19fc90b08211741c7bbf7 \
  run-cell \
    --tui crush \
    --model nvidia/llama-3.3-nemotron-super-49b-v1 \
    --task polyglot/python-two-sum

Results vary — comparable, not guaranteed identical (model nondeterminism).

Explore with your own model

Substitute your endpoint, key, and model ID. Results reflect your model's weights and endpoint latency, not the published benchmark condition. Endpoint must speak OpenAI-compatible /v1/chat/completions.

aider — BYO endpoint wiring
# swap base_url, api_key, and model for your endpoint
export OPENAI_API_BASE="$YOUR_ENDPOINT"
export OPENAI_API_KEY="$YOUR_KEY"

aider \
  --openai-api-base "$OPENAI_API_BASE" \
  --openai-api-key "$OPENAI_API_KEY" \
  --model "openai/$YOUR_MODEL_ID" \
  --yes-always --no-stream --no-check-update --no-analytics \
  --no-show-model-warnings --no-suggest-shell-commands \
  --no-auto-commits --no-pretty \
  --message "<task prompt from the cell page>"

# Published cell used model: nvidia/llama-3.3-nemotron-super-49b-v1
Zero-install preview — npx CLI (provisional, not for citation)
npx @codingagentbench/cli check
npx @codingagentbench/cli check \
  --tui crush \
  --model nvidia/llama-3.3-nemotron-super-49b-v1 \
  --endpoint "$YOUR_ENDPOINT" \
  --key "$YOUR_KEY" \
  --task polyglot/python-two-sum
# provisional score — not for citation

Provisional score — not for citation. Use the Docker or Harness CLI path for citable results.

Trace spans (5)

Span Kind Name Duration Attrs / Error
f7bb31013cc44b1da8f241060b578503 task_setup prepare:polyglot/python-two-sum 0 ms {"workdir":"/home/andrew/.codingagentbench-scratch/codingagentbench-crush-polyglot_python-two-sum-ifb1hex6/workdir","task_category":"polyglot","plugin_stack":[],"behavior_mode":"factory"}
821b89c970804119b821735c037156a4 ↳ e7c9721afd064ddc83eb2be2ca1de290 tool_call applied_plugins 0 ms {"tui":"crush","count":0,"applied":[],"env_keys":[],"extra_args":[],"applied_count":0,"skipped_count":0}
855a44723c724ed7832398b215c84fc1 ↳ e7c9721afd064ddc83eb2be2ca1de290 container crush-run:polyglot/python-two-sum 135527 ms {"image":"codingagentbench/crush:v0.72.0","model":"nvidia/llama-3.3-nemotron-super-49b-v1","base_url":"http://172.17.0.1:31415/v1","exit_code":0,"duration_s":135.12,"timed_out":false,"image_digest":"sha256:28e141efa8509cd43fd465b035019d1b35d76e97aec19fc90b08211741c7bbf7"}
e7c9721afd064ddc83eb2be2ca1de290 adapter_run crush:polyglot/python-two-sum 135932 ms {"timeout_s":600,"plugin_stack":[],"exit_code":0}
af85881e57864ec2a0a86480beb1030b cleanup cleanup:crush 0 ms {}

Model calls (0)

# Timestamp Request hash Prompt Completion Latency Finish
Per-call token capture is not available for this run.

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CodingAgentBench: crush × nvidia/llama-3.3-nemotron-super-49b-v1 44%