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RSI Bench
nano-gpt-data-curation

gpt-5.6-sol

nano-gpt-data-curation — graded by the task's verifier against a measured baseline.

backend
modal
variant
codex azure_ai/gpt-5.6-sol
metric
held-out multi-domain perplexity
actions
285
duration
1h 22m
recorded
2026-08-04

run iddclm-nano-curation__NqS7udZ

Everything gpt-5.6-sol did on this task, in order.

download JSON ↗
codexgpt-5.6-sol294 turns9 narration285 reasoning285 action285 observation1 final
#51
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "33",
  "yield_time_ms": 30000,
  "max_tokens": 10000
}
wait result
Script completed
Wall time 16.4 seconds
Output:
{"chunk_id":"cc9793","wall_time_seconds":30.00180107,"session_id":15357,"original_token_count":0,"output":""}
#52
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"nvidia-smi --query-compute-apps=pid,used_memory --format=csv,noheader && ps -o pid,etime,pcpu,pmem,args -C python | tail -20 && cat .timer/remaining_secs\",workdir:\"/workspace\",yield_time_ms:10000,max_output_tokens:5000}); text(r);\n"
}
exec result
Script completed
Wall time 0.1 seconds
Output:
{"chunk_id":"6a612d","wall_time_seconds":0.000078667,"exit_code":0,"original_token_count":28,"output":"1, 28890 MiB\n  PID     ELAPSED %CPU %MEM COMMAND\n 1432       02:49  122  0.4 python work/neural_score.py\n4629\n"}
#53
narration

The random controls show that “clean web only” is not enough: it improves over raw crawl alone but loses to a mixed selection, indicating that register coverage matters more than a single quality boundary. I’m therefore scoring every document with a small reference LM trained only on the disclosed four-way dev distribution, then I’ll combine that affinity with boilerplate/repetition filters and explicit domain quotas.

#54
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.write_stdin({session_id:15357,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}
exec result
Script running with cell ID 35
Wall time 11.0 seconds
Output:
#55
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "35",
  "yield_time_ms": 30000,
  "max_tokens": 10000
}
wait result
Script completed
Wall time 16.6 seconds
Output:
{"chunk_id":"b83583","wall_time_seconds":30.00088674,"session_id":15357,"original_token_count":0,"output":""}
#56
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.write_stdin({session_id:15357,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}
exec result
Script running with cell ID 36
Wall time 11.0 seconds
Output:
#57
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "36",
  "yield_time_ms": 30000,
  "max_tokens": 10000
}
wait result
Script completed
Wall time 16.3 seconds
Output:
{"chunk_id":"208e71","wall_time_seconds":30.001729913,"session_id":15357,"original_token_count":0,"output":""}
#58
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"ps -o pid,etime,pcpu,pmem,args -C python; nvidia-smi --query-gpu=utilization.gpu,memory.used --format=csv,noheader\",workdir:\"/workspace\",yield_time_ms:10000,max_output_tokens:1000}); text(r);\n"
}
exec result
Script completed
Wall time 0.1 seconds
Output:
{"chunk_id":"199a8d","wall_time_seconds":0.000043366,"exit_code":0,"original_token_count":27,"output":"  PID     ELAPSED %CPU %MEM COMMAND\n 1432       04:02  122  0.4 python work/neural_score.py\n0 %, 28899 MiB\n"}
#59
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.write_stdin({session_id:15357,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}
exec result
Script running with cell ID 38
Wall time 11.0 seconds
Output:
#60
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "38",
  "yield_time_ms": 30000,
  "max_tokens": 10000
}
wait result
Script completed
Wall time 16.5 seconds
Output:
{"chunk_id":"799844","wall_time_seconds":30.000839357,"session_id":15357,"original_token_count":0,"output":""}
#61
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"ps -o pid,etime,pcpu,pmem,rss,args -C python; nvidia-smi --query-gpu=utilization.gpu,memory.used --format=csv,noheader; ls -lh work/neural_scores.npz 2>/dev/null || true\",workdir:\"/workspace\",yield_time_ms:10000,max_output_tokens:1000}); text(r);\n"
}
exec result
Script completed
Wall time 0.1 seconds
Output:
{"chunk_id":"50027d","wall_time_seconds":0.000035357,"exit_code":0,"original_token_count":31,"output":"  PID     ELAPSED %CPU %MEM   RSS COMMAND\n 1432       04:46  120  0.4 5326064 python work/neural_score.py\n0 %, 28899 MiB\n"}
#62
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const patch = \"*** Begin Patch\\n*** Add File: /workspace/work/train_diag.py\\n+import argparse,math,time,json,numpy as np,torch\\n+from model import GPT,GPTConfig\\n+ap=argparse.ArgumentParser();ap.add_argument('--train_npy',required=True);ap.add_argument('--out_json',required=True);ap.add_argument('--max_iters',type=int,default=3000);ap.add_argument('--seed',type=int,default=1337)\\n+a=ap.parse_args();torch.manual_seed(a.seed);np.random.seed(a.seed)\\n+tr=torch.from_numpy(np.load(a.train_npy).astype(np.int64));ho=torch.from_numpy(np.load('data/multi_dev.npy').astype(np.int64));rng=np.random.default_rng(a.seed)\\n+m=GPT(GPTConfig(block_size=256,vocab_size=50257,n_layer=6,n_head=6,n_embd=384,dropout=0,bias=False)).cuda();o=m.configure_optimizers(.1,6e-4,(.9,.95),'cuda')\\n+def batch(src):\\n+ ix=rng.integers(0,len(src)-257,size=32);return torch.stack([src[i:i+256] for i in ix]).cuda(),torch.stack([src[i+1:i+257] for i in ix]).cuda()\\n+t=time.time();m.train()\\n+for it in range(a.max_iters):\\n+ lr=6e-4*(it+1)/151 if it<150 else 6e-5+.5*(1+math.cos(math.pi*(it-150)/max(1,a.max_iters-150)))*5.4e-4\\n+ for g in o.param_groups:g['lr']=lr\\n+ x,y=batch(tr)\\n+ with torch.autocast('cuda',dtype=torch.bfloat16):_,loss=m(x,y)\\n+ o.zero_grad(set_to_none=True);loss.backward();torch.nn.utils.clip_grad_norm_(m.parameters(),1);o.step()\\n+m.eval();losses=[]\\n+with torch.no_grad():\\n+ for d in range(4):\\n+  vals=[]; seg=ho[d*250000:(d+1)*250000]; nw=(len(seg)-1)//256\\n+  for j in range(0,nw,32):\\n+   starts=list(range(j,min(j+32,nw)));x=torch.stack([seg[k*256:k*256+256] for k in starts]).cuda();y=torch.stack([seg[k*256+1:k*256+257] for k in starts]).cuda()\\n+   with torch.autocast('cuda',dtype=torch.bfloat16):_,l=m(x,y)\\n+   vals.extend([float(l)]*len(starts))\\n+  losses.append(float(np.mean(vals)))\\n+out={'losses':losses,'ppls':[math.exp(x) for x in losses],'mean_loss':float(np.mean(losses)),'ppl':math.exp(float(np.mean(losses))),'train_s':time.time()-t}\\n+json.dump(out,open(a.out_json,'w'));print(out)\\n*** End Patch\";\nconst a = await tools.apply_patch(patch); text(a);\n"
}
exec result
Script completed
Wall time 0.0 seconds
Output:
{}
#63
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.write_stdin({session_id:15357,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}
exec result
Script running with cell ID 41
Wall time 11.0 seconds
Output:
#64
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "41",
  "yield_time_ms": 30000,
  "max_tokens": 10000
}
wait result
Script completed
Wall time 15.8 seconds
Output:
{"chunk_id":"ec02f1","wall_time_seconds":30.002140503,"session_id":15357,"original_token_count":0,"output":""}
#65
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.write_stdin({session_id:15357,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}
exec result
Script running with cell ID 42
Wall time 11.0 seconds
Output:
#66
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "42",
  "yield_time_ms": 30000,
  "max_tokens": 10000
}
wait result
Script completed
Wall time 8.4 seconds
Output:
{"chunk_id":"ffb568","wall_time_seconds":30.002009194,"session_id":15357,"original_token_count":0,"output":""}
#67
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"ps -o pid,etime,pcpu,pmem,rss,args -C python; nvidia-smi --query-gpu=utilization.gpu,memory.used --format=csv,noheader; cat .timer/remaining_secs\",workdir:\"/workspace\",yield_time_ms:10000,max_output_tokens:1000}); text(r);\n"
}
exec result
Script completed
Wall time 0.1 seconds
Output:
{"chunk_id":"740652","wall_time_seconds":0.000139764,"exit_code":0,"original_token_count":32,"output":"  PID     ELAPSED %CPU %MEM   RSS COMMAND\n 1432       06:06  119  0.4 5323260 python work/neural_score.py\n0 %, 28899 MiB\n4429\n"}
#68
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.write_stdin({session_id:15357,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}
exec result
Script running with cell ID 44
Wall time 11.0 seconds
Output:
#69
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "44",
  "yield_time_ms": 30000,
  "max_tokens": 10000
}
wait result
Script completed
Wall time 14.6 seconds
Output:
{"chunk_id":"98b476","wall_time_seconds":30.001261187,"session_id":15357,"original_token_count":0,"output":""}
#70
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.write_stdin({session_id:15357,chars:\"\",yield_time_ms:30000,max_output_tokens:10000}); text(r);\n"
}
exec result
Script running with cell ID 45
Wall time 11.0 seconds
Output:
#71
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "45",
  "yield_time_ms": 30000,
  "max_tokens": 10000
}
wait result
Script completed
Wall time 15.9 seconds
Output:
{"chunk_id":"61dc1b","wall_time_seconds":30.001902297,"session_id":15357,"original_token_count":0,"output":""}
#72
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"nvidia-smi dmon -s pucvmet -d 1 -c 5\",workdir:\"/workspace\",yield_time_ms:10000,max_output_tokens:2000}); text(r);\n"
}
exec result
Script completed
Wall time 4.5 seconds
Output:
{"chunk_id":"966599","wall_time_seconds":4.340562689,"exit_code":0,"original_token_count":270,"output":"# gpu    pwr  gtemp  mtemp     sm    mem    enc    dec    jpg    ofa   mclk   pclk  pviol  tviol     fb   bar1   ccpm  sbecc  dbecc    pci  rxpci  txpci \n# Idx      W      C      C      %      %      %      %      %      %    MHz    MHz      %   bool     MB     MB     MB   errs   errs   errs   MB/s   MB/s \n    0    138     44     52      1      0      0      0      0      0   2619   1980      0      0      4      4      0      0      0      0      1      4 \n    0    130     44     50      0      0      0      0      0      0   2619   1980      0      0      4      4      0      0      0      0      0      2 \n    0    101     43     50      0      0      0      0      0      0   2619    795      0      0      4      4      0      0      0      0      3      0 \n    0     76     42     50      0      0      0      0      0      0   2619    495      0      0      4      4      0      0      0      0      0      0 \n    0     75     42     50      0      0      0      0      0      0   2619    345      0      0      4      4      0      0      0      0      0      1 \n"}
#73
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.write_stdin({session_id:15357,chars:\"\",yield_time_ms:1000,max_output_tokens:10000}); text(r);\n"
}
exec result
Script completed
Wall time 0.0 seconds
Output:
{"chunk_id":"0417db","wall_time_seconds":0.000004646,"exit_code":0,"original_token_count":76,"output":"train 0 10.865493774414062\ntrain 300 5.42300271987915\ntrain 600 4.685652256011963\ntrain 900 4.036515712738037\ntrain 1200 3.7150909900665283\ntrain 1500 3.4014289379119873\nquantiles [ 0.          5.77004538  6.36182761  6.67190886  7.24575925  8.09722328\n  9.35249281 10.23939037 11.70716834 18.75856781]\n"}
#74
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolexec
args
{
  "input": "const r = await tools.exec_command({cmd:\"python - <<'PY'\\nimport json,re,numpy as np\\nz=np.load('work/neural_scores.npz'); loss=z['loss']; tl=z['toklen']; ds=np.load('work/domain_scores.npy');\\ntexts=[]\\nfor line in open('data/pool.jsonl'):\\n r=json.loads(line);texts.append(r['text'])\\nvalid=np.array([800<=len(s)<=30000 and sum(c.isalpha() for c in s)/len(s)>.58 for s in texts]) & (tl>=128)\\nsets=[('all',np.where(valid)[0])]+[(f'd{d}',np.where(valid & (ds.argmax(1)==d))[0]) for d in range(4)]\\nfor name,ids in sets:\\n print('\\\\n###',name,'n',len(ids))\\n for i in ids[np.argsort(loss[ids])[:25]]:\\n  print(f'{i} loss={loss[i]:.3f} D={ds[i].argmax()} len={len(texts[i])} :: '+re.sub(r'\\\\s+',' ',texts[i][:240]))\\nPY\",workdir:\"/workspace\",yield_time_ms:30000,max_output_tokens:30000}); text(r);\n"
}
exec result
Script running with cell ID 48
Wall time 11.0 seconds
Output:
#75
reasoning (redacted)

encrypted chain-of-thought — recorded, not exposed

toolwait
args
{
  "cell_id": "48",
  "yield_time_ms": 30000,
  "max_tokens": 30000
}
wait result
Script completed
Wall time 11.9 seconds
Output:
{"chunk_id":"13ba43","wall_time_seconds":30.002301314,"session_id":10946,"original_token_count":0,"output":""}