qwen-code × nvidia/llama-3.3-nemotron-super-49b-v1

polyglot

polyglot/python-two-sum

Per-axis scores

Pass

0.000

Tokens/correct

—

Wall

463.5s

Blast

1.000

Refusal

—

Integrity

1.000

Composite

0.406

Run identity

cell_id: free-20260527/qwen-code/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/python-two-sum
sweep_id: free-20260527
container_image: codingagentbench/qwen-code:v0.16.1
image_digest: sha256:597f01dba22092cfdcfc7a593f2c5a658a9e647bae60709f04aaba33622c961d
model_build_id: nvidia/llama-3.3-nemotron-super-49b-v1
exit_code: 0

Timing

started_at: 2026-06-16T21:29:18.182443Z
ended_at: 2026-06-16T21:37:01.717193Z
duration: 463.54 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":"test_two_sum (unittest.loader._FailedTest.test_two_sum) ... ERROR\n\n======================================================================\nERROR: test_two_sum (unittest.loader._FailedTest.test_two_sum)\n----------------------------------------------------------------------\nImportError: Failed to import test module: test_two_sum\nTraceback (most recent call last):\n File \"/home/andrew/.pyenv/versions/3.11.11/lib/python3.11/unittest/loader.py\", line 419, in _find_test_path\n module = self._get_module_from_name(name)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/home/andrew/.pyenv/versions/3.11.11/lib/python3.11/unittest/loader.py\", line 362, in _get_module_from_name\n __import__(name)\n File \"/home/andrew/.codingagentbench-scratch/codingagentbench-qwen-code-polyglot_python-two-sum-ypphwt_k/workdir/tests/test_two_sum.py\", line 1\n <UPDATED_CONTENT_ABOVE>\n ^\nSyntaxError: invalid syntax\n\n\n----------------------------------------------------------------------\nRan 1 test in 0.000s\n\nFAILED (errors=1)\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":463534.75,"container_active_ms":463521.337,"model_call_ms":0}`
blast_radius	blast_radius, added, removed, modified, unexpected_changes, expected_changes, total_changes, extra_git_dir	`{"blast_radius":1,"added":[],"removed":[],"modified":["tests/test_two_sum.py"],"unexpected_changes":["tests/test_two_sum.py"],"expected_changes":[],"total_changes":1,"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":0.40606739155666716,"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":1,"tokens_per_correct_task":0,"wall_clock_ms":463534.75,"expected_refusal":false,"refusal_produced":false,"cost_efficiency":1,"latency_efficiency":0.3737826103777811,"clean_blast":0,"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

speedt = 0 ms / 463.54 s

span ecadd9eabcac44cba7f3b4e36225cccatask_setupprepare:polyglot/python-two-sum0 ms → 13 ms

workdir/home/andrew/.codingagentbench-scratch/codingagentbench-qwen-code-polyglot_python-two-sum-ypphwt_k/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/qwen-code:v0.16.1·sha256:sha256:597f01dba…

docker run — exact image used in this run

# pull the exact image used in this run
docker pull codingagentbench/qwen-code:v0.16.1@sha256:sha256:597f01dba22092cfdcfc7a593f2c5a658a9e647bae60709f04aaba33622c961d

docker run --rm \
  -e CAB_ENDPOINT="$YOUR_ENDPOINT" \
  -e CAB_KEY="$YOUR_KEY" \
  codingagentbench/qwen-code:v0.16.1@sha256:sha256:597f01dba22092cfdcfc7a593f2c5a658a9e647bae60709f04aaba33622c961d \
  run-cell \
    --tui qwen-code \
    --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 qwen-code \
  --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
ecadd9eabcac44cba7f3b4e36225ccca	task_setup	prepare:polyglot/python-two-sum	13 ms	`{"workdir":"/home/andrew/.codingagentbench-scratch/codingagentbench-qwen-code-polyglot_python-two-sum-ypphwt_k/workdir","task_category":"polyglot","plugin_stack":[],"behavior_mode":"factory"}`
f262c1e923aa43df8aea04aa27e39f1c ↳ 8e1868f73c534d3994a6cd835ee94019	tool_call	applied_plugins	0 ms	`{"tui":"qwen-code","count":0,"applied":[],"env_keys":[],"extra_args":[],"applied_count":0,"skipped_count":0}`
227b684924db4fb4b676e5ddd4c1196c ↳ 8e1868f73c534d3994a6cd835ee94019	container	qwen-code:run	463522 ms	`{"image":"codingagentbench/qwen-code:v0.16.1","command":["-p","Find two indices summing to target; broken hash-map walk returns the same index twice","--yolo"],"model":"nvidia/llama-3.3-nemotron-super-49b-v1","exit_code":0,"timed_out":false}`
8e1868f73c534d3994a6cd835ee94019	adapter_run	qwen-code:polyglot/python-two-sum	463522 ms	`{"timeout_s":600,"plugin_stack":[],"exit_code":0}`
784fd23c3b074dfaa84d974fba3470de	cleanup	cleanup:qwen-code	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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