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CodingAgentBench

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

polyglot
polyglot/python-two-sum

Per-axis scores

Pass
0.000
Tokens/correct
—
Wall
8.2s
Blast
0.000
Refusal
—
Integrity
1.000
Composite
0.569

Run identity

cell_id
free-20260527/goose/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/python-two-sum
sweep_id
free-20260527
container_image
codingagentbench/goose:v1.35.0
image_digest
sha256:b105cf72a2cb923875ba8896a68c835b29025d9e24e7fb39ca95856ec105a3a6
model_build_id
nvidia/llama-3.3-nemotron-super-49b-v1
exit_code
0

Timing

started_at
2026-06-16T17:41:25.368249Z
ended_at
2026-06-16T17:41:33.584333Z
duration
8.22 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-goose-polyglot_python-two-sum-_v8tu2_4/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-goose-polyglot_python-two-sum-_v8tu2_4/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-goose-polyglot_python-two-sum-_v8tu2_4/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 0.002s\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":8216.084,"container_active_ms":8210.198,"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":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":0.5690046432334596,"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":8216.084,"expected_refusal":false,"refusal_produced":false,"cost_efficiency":1,"latency_efficiency":0.7933642882230642,"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 / 8.22 s
span 9189af32bc5b4c2ea601e652ce5956d2task_setupprepare:polyglot/python-two-sum0 ms → 0 ms
workdir/home/andrew/.codingagentbench-scratch/codingagentbench-goose-polyglot_python-two-sum-_v8tu2_4/workdir
task_categorypolyglot
plugin_stack[]
behavior_modefactory

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/goose:v1.35.0·sha256:sha256:b105cf72a…
docker run — exact image used in this run
# pull the exact image used in this run
docker pull codingagentbench/goose:v1.35.0@sha256:sha256:b105cf72a2cb923875ba8896a68c835b29025d9e24e7fb39ca95856ec105a3a6

docker run --rm \
  -e CAB_ENDPOINT="$YOUR_ENDPOINT" \
  -e CAB_KEY="$YOUR_KEY" \
  codingagentbench/goose:v1.35.0@sha256:sha256:b105cf72a2cb923875ba8896a68c835b29025d9e24e7fb39ca95856ec105a3a6 \
  run-cell \
    --tui goose \
    --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 goose \
  --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 (6)

Span Kind Name Duration Attrs / Error
9189af32bc5b4c2ea601e652ce5956d2 task_setup prepare:polyglot/python-two-sum 0 ms {"workdir":"/home/andrew/.codingagentbench-scratch/codingagentbench-goose-polyglot_python-two-sum-_v8tu2_4/workdir","task_category":"polyglot","plugin_stack":[],"behavior_mode":"factory"}
09c920779a42492b9a51ed0c31d25bab ↳ dd054b49231e47448e56474648b9d884 tool_call applied_plugins 0 ms {"tui":"goose","count":0,"applied":[],"env_keys":[],"extra_args":[],"applied_count":0,"skipped_count":0}
196c68bfe0a14f3cb9fd240a3bc3df72 ↳ dd054b49231e47448e56474648b9d884 tool_call goose:extensions 0 ms {"extensions":[],"count":0}
e5be6931e3d84e8f8dd9021fb90eba57 ↳ dd054b49231e47448e56474648b9d884 container goose:run 8211 ms {"image":"codingagentbench/goose:v1.35.0","command":["run","--no-session","-t","Find two indices summing to target; broken hash-map walk returns the same index twice"],"exit_code":0,"timed_out":false}
dd054b49231e47448e56474648b9d884 adapter_run goose:polyglot/python-two-sum 8216 ms {"timeout_s":600,"plugin_stack":[],"exit_code":0}
651309f4ff4f45beb28de0fef6eeca44 cleanup cleanup:goose 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: goose × nvidia/llama-3.3-nemotron-super-49b-v1 57%