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

polyglot

polyglot/java-stream-collect

Per-axis scores

Pass

0.000

Tokens/correct

—

Wall

31.7s

Blast

0.000

Refusal

—

Integrity

1.000

Composite

0.543

Run identity

cell_id: free-20260527/qwen-code/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/java-stream-collect
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: 1

Timing

started_at: 2026-06-16T21:28:24.207614Z
ended_at: 2026-06-16T21:28:55.859735Z
duration: 31.65 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":"Exception in thread \"main\" java.lang.IllegalStateException: Duplicate key a (attempted merging values 1 and 1)\n\tat java.base/java.util.stream.Collectors.duplicateKeyException(Collectors.java:133)\n\tat java.base/java.util.stream.Collectors.lambda$uniqKeysMapAccumulator$1(Collectors.java:180)\n\tat java.base/java.util.stream.ReduceOps$3ReducingSink.accept(ReduceOps.java:169)\n\tat java.base/java.util.Spliterators$ArraySpliterator.forEachRemaining(Spliterators.java:948)\n\tat java.base/java.util.stream.AbstractPipeline.copyInto(AbstractPipeline.java:484)\n\tat java.base/java.util.stream.AbstractPipeline.wrapAndCopyInto(AbstractPipeline.java:474)\n\tat java.base/java.util.stream.ReduceOps$ReduceOp.evaluateSequential(ReduceOps.java:913)\n\tat java.base/java.util.stream.AbstractPipeline.evaluate(AbstractPipeline.java:234)\n\tat java.base/java.util.stream.ReferencePipeline.collect(ReferencePipeline.java:578)\n\tat WordCounter.countWords(WordCounter.java:8)\n\tat Tests.main(Tests.java:16)\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":31652.121000000003,"container_active_ms":31640.677,"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/java-stream-collect"}`
composite	composite, weights, components, note	{"composite":0.5426133379029635,"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":31652.121000000003,"expected_refusal":false,"refusal_produced":false,"cost_efficiency":1,"latency_efficiency":0.6174222526864238,"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

speedt = 0 ms / 31.65 s

span d764cc5a241e476d8b8bd3cec7565f12task_setupprepare:polyglot/java-stream-collect0 ms → 11 ms

workdir/home/andrew/.codingagentbench-scratch/codingagentbench-qwen-code-polyglot_java-stream-collect-dbdlcym0/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/java-stream-collect

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/java-stream-collect
# 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
d764cc5a241e476d8b8bd3cec7565f12	task_setup	prepare:polyglot/java-stream-collect	11 ms	`{"workdir":"/home/andrew/.codingagentbench-scratch/codingagentbench-qwen-code-polyglot_java-stream-collect-dbdlcym0/workdir","task_category":"polyglot","plugin_stack":[],"behavior_mode":"factory"}`
a40ff562dac54dfdb445149a07e10393 ↳ fbfd12cab8a54e85aa814f907a5bacd0	tool_call	applied_plugins	0 ms	`{"tui":"qwen-code","count":0,"applied":[],"env_keys":[],"extra_args":[],"applied_count":0,"skipped_count":0}`
e131d555dff64ffb82fd9e8f6046fea8 ↳ fbfd12cab8a54e85aa814f907a5bacd0	container	qwen-code:run	31641 ms	`{"image":"codingagentbench/qwen-code:v0.16.1","command":["-p","Wrong Collector loses duplicates; convert toMap-merge instead of groupingBy","--yolo"],"model":"nvidia/llama-3.3-nemotron-super-49b-v1","exit_code":1,"timed_out":false}`
fbfd12cab8a54e85aa814f907a5bacd0	adapter_run	qwen-code:polyglot/java-stream-collect	31641 ms	`{"timeout_s":600,"plugin_stack":[],"exit_code":1}`
b5528e88e2934507934eb51a0aa55aa7	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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