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CodingAgentBench

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

polyglot
polyglot/go-slice-dedup

Per-axis scores

Pass
0.000
Tokens/correct
—
Wall
5.6s
Blast
0.000
Refusal
—
Integrity
1.000
Composite
0.576

Run identity

cell_id
expansion-20260616/codex/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/go-slice-dedup
sweep_id
expansion-20260616
container_image
codingagentbench/codex:v0.140.0
image_digest
sha256:52116224fbc698acc448343890c4542efcc101a950ef8c8de1eca3e051f228bc
model_build_id
nvidia/llama-3.3-nemotron-super-49b-v1
exit_code
0

Timing

started_at
2026-06-17T00:53:47.111940Z
ended_at
2026-06-17T00:53:52.720633Z
duration
5.61 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":"--- FAIL: TestDedup_FirstSeenOrder (0.00s)\n dedup_test.go:12: got [1 2 3 4 5 6 9] want [3 1 4 5 9 2 6]\n--- FAIL: TestDedup_NoMutation (0.00s)\n dedup_test.go:21: input mutated: got [1 1 3 4 5] want [3 1 4 1 5]\n--- FAIL: TestDedup_AlreadyUnique (0.00s)\n dedup_test.go:44: got [1 2 5 9] want [5 1 9 2]\nFAIL\nFAIL\tcodingagentbench/goslicededup\t0.002s\nFAIL\n","stderr_tail":"","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":5608.692999999999,"container_active_ms":5595.764,"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/go-slice-dedup"}
composite composite, weights, components, note {"composite":0.5756948264654612,"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":5608.692999999999,"expected_refusal":false,"refusal_produced":false,"cost_efficiency":1,"latency_efficiency":0.837965509769742,"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 / 5.61 s
span 0f0849e5ef0542e2ad740648daf05a45task_setupprepare:polyglot/go-slice-dedup0 ms → 13 ms
workdir/home/andrew/.codingagentbench-scratch/codingagentbench-codex-polyglot_go-slice-dedup-77pdpvok/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/codex:v0.140.0·sha256:sha256:52116224f…
docker run — exact image used in this run
# pull the exact image used in this run
docker pull codingagentbench/codex:v0.140.0@sha256:sha256:52116224fbc698acc448343890c4542efcc101a950ef8c8de1eca3e051f228bc

docker run --rm \
  -e CAB_ENDPOINT="$YOUR_ENDPOINT" \
  -e CAB_KEY="$YOUR_KEY" \
  codingagentbench/codex:v0.140.0@sha256:sha256:52116224fbc698acc448343890c4542efcc101a950ef8c8de1eca3e051f228bc \
  run-cell \
    --tui codex \
    --model nvidia/llama-3.3-nemotron-super-49b-v1 \
    --task polyglot/go-slice-dedup

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 codex \
  --model nvidia/llama-3.3-nemotron-super-49b-v1 \
  --endpoint "$YOUR_ENDPOINT" \
  --key "$YOUR_KEY" \
  --task polyglot/go-slice-dedup
# 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
0f0849e5ef0542e2ad740648daf05a45 task_setup prepare:polyglot/go-slice-dedup 13 ms {"workdir":"/home/andrew/.codingagentbench-scratch/codingagentbench-codex-polyglot_go-slice-dedup-77pdpvok/workdir","task_category":"polyglot","plugin_stack":[],"behavior_mode":"factory"}
204f0dfffdeb4940830ca58340d47b6f ↳ d6e2d262ee0448d198be46e08a74f963 tool_call applied_plugins 0 ms {"tui":"codex","count":0,"applied":[],"env_keys":[],"extra_args":[],"applied_count":0,"skipped_count":0}
4073cc7797d640d3ae282adae6c810aa ↳ d6e2d262ee0448d198be46e08a74f963 container codex:launch 5596 ms {"image":"codingagentbench/codex:v0.140.0","argv":["exec","--dangerously-bypass-approvals-and-sandbox","--skip-git-repo-check","--ephemeral","--ignore-user-config","-m","nvidia/llama-3.3-nemotron-super-49b-v1","-c","model_providers.nim={ name = 'nim', base_url = 'http://172.17.0.1:31415/v1', wire_api = 'responses', env_key = 'OPENAI_API_KEY' }","-c","model_provider=\"nim\"","--disable","multi_agent","--disable","browser_use","--disable","browser_use_external","--disable","computer_use","--disable","apps","Dedup a slice preserving first-seen order; current impl mutates input and produces wrong order"],"timeout_s":600,"exit_code":0,"duration_s":3.3403138520079665,"timed_out":false}
d6e2d262ee0448d198be46e08a74f963 adapter_run codex:polyglot/go-slice-dedup 5596 ms {"timeout_s":600,"plugin_stack":[],"exit_code":0}
60e5153f0ff2497abd7581b65d639d96 cleanup cleanup:codex 0 ms {}

Model calls (0)

# Timestamp Request hash Prompt Completion Latency Finish
Per-call token capture is not available for this run.

Other CLIs on this task

Other models with this CLI

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README / Markdown
[![CodingAgentBench: codex × nvidia/llama-3.3-nemotron-super-49b-v1 58%](https://codingagentbench.com/badge/codex/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/go-slice-dedup.svg)](https://codingagentbench.com/cell/codex/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/go-slice-dedup)
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CodingAgentBench: codex × nvidia/llama-3.3-nemotron-super-49b-v1 58%