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CodingAgentBench

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

polyglot
polyglot/python-two-sum

Per-axis scores

Pass
0.000
Tokens/correct
—
Wall
32.6s
Blast
0.000
Refusal
—
Integrity
1.000
Composite
0.542

Run identity

cell_id
free-20260527/opencode/nvidia/llama-3.3-nemotron-super-49b-v1/polyglot/python-two-sum
sweep_id
free-20260527
container_image
codingagentbench/opencode:v1.15.10
image_digest
sha256:e56bdb69fb83ea2f8c81c06257f190fd4b5e91077e83d5536f722ff1b9c70275
model_build_id
nvidia/llama-3.3-nemotron-super-49b-v1
exit_code
0

Timing

started_at
2026-06-16T18:06:41.760710Z
ended_at
2026-06-16T18:07:14.382708Z
duration
32.62 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":"n 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-opencode-polyglot_python-two-sum-dwmcl_i5/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-opencode-polyglot_python-two-sum-dwmcl_i5/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-opencode-polyglot_python-two-sum-dwmcl_i5/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":32621.998,"container_active_ms":30737.135,"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":0.5420452187468027,"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":32621.998,"expected_refusal":false,"refusal_produced":false,"cost_efficiency":1,"latency_efficiency":0.613634791645351,"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 / 32.62 s
span 665c1175c19a426c8e9a098411a3b786task_setupprepare:polyglot/python-two-sum0 ms → 1 ms
workdir/home/andrew/.codingagentbench-scratch/codingagentbench-opencode-polyglot_python-two-sum-dwmcl_i5/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/opencode:v1.15.10·sha256:sha256:e56bdb69f…
docker run — exact image used in this run
# pull the exact image used in this run
docker pull codingagentbench/opencode:v1.15.10@sha256:sha256:e56bdb69fb83ea2f8c81c06257f190fd4b5e91077e83d5536f722ff1b9c70275

docker run --rm \
  -e CAB_ENDPOINT="$YOUR_ENDPOINT" \
  -e CAB_KEY="$YOUR_KEY" \
  codingagentbench/opencode:v1.15.10@sha256:sha256:e56bdb69fb83ea2f8c81c06257f190fd4b5e91077e83d5536f722ff1b9c70275 \
  run-cell \
    --tui opencode \
    --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.

opencode — BYO endpoint wiring
# Write .opencode/config.json in the task workdir:
# {
#   "providers": {
#     "codingagentbench": {
#       "type": "openai",
#       "options": {
#         "baseURL": "$YOUR_ENDPOINT",
#         "apiKey": "$YOUR_KEY"
#       },
#       "models": [{ "id": "$YOUR_MODEL_ID", "name": "$YOUR_MODEL_ID" }]
#     }
#   }
# }

opencode run \
  --format json \
  --dangerously-skip-permissions \
  -m codingagentbench/$YOUR_MODEL_ID

# 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 opencode \
  --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
665c1175c19a426c8e9a098411a3b786 task_setup prepare:polyglot/python-two-sum 1 ms {"workdir":"/home/andrew/.codingagentbench-scratch/codingagentbench-opencode-polyglot_python-two-sum-dwmcl_i5/workdir","task_category":"polyglot","plugin_stack":[],"behavior_mode":"factory"}
b96a14032338419ab28c292e13cbd12e ↳ d900a5c03973413b83c1ca0a30b26fef tool_call applied_plugins 1 ms {"tui":"opencode","count":0,"applied":[],"env_keys":[],"extra_args":[],"applied_count":0,"skipped_count":0}
97ed895fccb74c348ee2b8a316d50dc0 ↳ d900a5c03973413b83c1ca0a30b26fef container opencode-run:polyglot/python-two-sum 30737 ms {"image":"codingagentbench/opencode:v1.15.10","model":"nvidia/llama-3.3-nemotron-super-49b-v1","base_url":"http://172.17.0.1:31415/v1","exit_code":0,"duration_s":12.049,"timed_out":false,"image_digest":"sha256:e56bdb69fb83ea2f8c81c06257f190fd4b5e91077e83d5536f722ff1b9c70275"}
d900a5c03973413b83c1ca0a30b26fef adapter_run opencode:polyglot/python-two-sum 32621 ms {"timeout_s":600,"plugin_stack":[],"exit_code":0}
e25a5f4805514379808f746d211c57e9 cleanup cleanup:opencode 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: opencode × nvidia/llama-3.3-nemotron-super-49b-v1 54%