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CodingAgentBench

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

polyglot
polyglot/python-two-sum

Per-axis scores

Pass
0.000
Tokens/correct
—
Wall
6.7s
Blast
0.000
Refusal
—
Integrity
1.000
Composite
0.573

Run identity

cell_id
expansion-20260616/copilot/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/python-two-sum
sweep_id
expansion-20260616
container_image
codingagentbench/copilot:v1.0.63
image_digest
sha256:6ad0221187dc5c6de50c8aeec50b0eb8eab269c1a681c79efaaa068741a20607
model_build_id
nvidia/llama-3.3-nemotron-super-49b-v1
exit_code
0

Timing

started_at
2026-06-17T02:29:44.270620Z
ended_at
2026-06-17T02:29:51.018547Z
duration
6.75 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":", 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-copilot-polyglot_python-two-sum-vn1bqe8n/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-copilot-polyglot_python-two-sum-vn1bqe8n/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-copilot-polyglot_python-two-sum-vn1bqe8n/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":6747.927,"container_active_ms":6734.105,"model_call_ms":0}
blast_radius blast_radius, added, removed, modified, unexpected_changes, expected_changes, total_changes, extra_git_dir {"blast_radius":0,"added":[],"removed":[],"modified":[],"unexpected_changes":[],"expected_changes":[],"total_changes":0,"extra_git_dir":true}
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":0.5725529185485524,"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,"tokens_per_correct_task":0,"wall_clock_ms":6747.927,"expected_refusal":false,"refusal_produced":false,"cost_efficiency":1,"latency_efficiency":0.8170194569903492,"clean_blast":1,"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 / 6.75 s
span 46b64bda2e0449d7af65e26af68fa2b8task_setupprepare:polyglot/python-two-sum0 ms → 14 ms
workdir/home/andrew/.codingagentbench-scratch/codingagentbench-copilot-polyglot_python-two-sum-vn1bqe8n/workdir
task_categorypolyglot
plugin_stack[]
behavior_modefactory

Terminal playback

replay of the run — opencode cells show genuine step timing; others show a span summary

Run it yourself

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

Imagecodingagentbench/copilot:v1.0.63·sha256:sha256:6ad022118…
docker run — exact image used in this run
# pull the exact image used in this run
docker pull codingagentbench/copilot:v1.0.63@sha256:sha256:6ad0221187dc5c6de50c8aeec50b0eb8eab269c1a681c79efaaa068741a20607

docker run --rm \
  -e CAB_ENDPOINT="$YOUR_ENDPOINT" \
  -e CAB_KEY="$YOUR_KEY" \
  codingagentbench/copilot:v1.0.63@sha256:sha256:6ad0221187dc5c6de50c8aeec50b0eb8eab269c1a681c79efaaa068741a20607 \
  run-cell \
    --tui copilot \
    --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 copilot \
  --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
46b64bda2e0449d7af65e26af68fa2b8 task_setup prepare:polyglot/python-two-sum 14 ms {"workdir":"/home/andrew/.codingagentbench-scratch/codingagentbench-copilot-polyglot_python-two-sum-vn1bqe8n/workdir","task_category":"polyglot","plugin_stack":[],"behavior_mode":"factory"}
d218cc57a7d749049d07daf4a0c71ca6 ↳ 7b4c2c598fc242b38022babd23ca5530 tool_call applied_plugins 0 ms {"tui":"copilot","count":0,"applied":[],"env_keys":[],"extra_args":[],"applied_count":0,"skipped_count":0}
3c622ed3e95243d5a0682b373d7fce81 ↳ 7b4c2c598fc242b38022babd23ca5530 container copilot:launch 6734 ms {"image":"codingagentbench/copilot:v1.0.63","argv":["-p","Find two indices summing to target; broken hash-map walk returns the same index twice","--allow-all"],"timeout_s":600,"exit_code":0,"duration_s":6.718968995992327,"timed_out":false}
7b4c2c598fc242b38022babd23ca5530 adapter_run copilot:polyglot/python-two-sum 6734 ms {"timeout_s":600,"plugin_stack":[],"exit_code":0}
88b35b82279a4fabbe48c396efe1b0bf cleanup cleanup:copilot 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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Other models with this CLI

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CodingAgentBench: copilot × nvidia/llama-3.3-nemotron-super-49b-v1 57%