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

polyglot

polyglot/java-null-safety

Per-axis scores

Pass

0.000

Tokens/correct

—

Wall

49.8s

Blast

0.000

Refusal

—

Integrity

1.000

Composite

0.534

Run identity

cell_id: free-20260527/goose/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/java-null-safety
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: 2026-06-16T17:41:02.392501Z
ended_at: 2026-06-16T17:41:52.181211Z
duration: 49.79 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":"ok normal\n","stderr_tail":"Exception in thread \"main\" java.lang.NullPointerException\n\tat UserGreeter.greet(UserGreeter.java:5)\n\tat Tests.main(Tests.java:18)\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":49788.71,"container_active_ms":49781.719000000005,"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/java-null-safety"}`
composite	composite, weights, components, note	{"composite":0.5344300238447709,"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":49788.71,"expected_refusal":false,"refusal_produced":false,"cost_efficiency":1,"latency_efficiency":0.562866825631806,"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 / 49.79 s

span 32a06f63e7b04671a2abb6ca3e024f29task_setupprepare:polyglot/java-null-safety0 ms → 2 ms

workdir/home/andrew/.codingagentbench-scratch/codingagentbench-goose-polyglot_java-null-safety-q8puwck3/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/java-null-safety

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/java-null-safety
# 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
32a06f63e7b04671a2abb6ca3e024f29	task_setup	prepare:polyglot/java-null-safety	2 ms	`{"workdir":"/home/andrew/.codingagentbench-scratch/codingagentbench-goose-polyglot_java-null-safety-q8puwck3/workdir","task_category":"polyglot","plugin_stack":[],"behavior_mode":"factory"}`
5d31f20592e04964b58e94da7c02d60a ↳ 1a07806f4e154a53beb978839e7e02ea	tool_call	applied_plugins	0 ms	`{"tui":"goose","count":0,"applied":[],"env_keys":[],"extra_args":[],"applied_count":0,"skipped_count":0}`
b5c649df20614fc0837ccbba9bae5217 ↳ 1a07806f4e154a53beb978839e7e02ea	tool_call	goose:extensions	0 ms	`{"extensions":[],"count":0}`
3a2c7134ea7c46358b507e786a62a358 ↳ 1a07806f4e154a53beb978839e7e02ea	container	goose:run	49782 ms	`{"image":"codingagentbench/goose:v1.35.0","command":["run","--no-session","-t","User class lookup crashes on null fields; rewrite to return empty string instead of NPE"],"exit_code":0,"timed_out":false}`
1a07806f4e154a53beb978839e7e02ea	adapter_run	goose:polyglot/java-null-safety	49787 ms	`{"timeout_s":600,"plugin_stack":[],"exit_code":0}`
a5a9c1389ceb4a30b65489cfad13035b	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 53%](https://codingagentbench.com/badge/goose/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/java-null-safety.svg)](https://codingagentbench.com/cell/goose/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/java-null-safety)

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