Physical AI lab

Can AI engineer
the physical world?

Long-horizon tasks (60–150 tool steps) on a real, delivered industrial oven: Siemens TIA Portal program, electrical drawings, acceptance protocols, the engineers' revision history.

CAD model of the conveyor oven used in the benchmark

Long-horizon hard bench

22 long tasks · 35–199 tool steps · pass = every item exact · rounds 1–2 · 1 run per task, 2 runs on borderline tasks · each task weighs the same · updated 2026-11-06

Pass rate

Tasks finished with every item exact · Higher is better

55%Opus 5.515/31 runs50%Argon14/31 runs45%Sol14/32 runs0%DeepSeek0/22 runsClaude Opus 5.5Score 97.8 · 15/31 fully correct6.8 min · $3.53 per task22 tasksGemini 4 ArgonScore 79.7 · 14/31 fully correct27.0 min · $1.94 per task22 tasksGPT-6.1 SolScore 91.3 · 14/32 fully correct3.5 min · $0.43 per task22 tasksDeepSeek V4.1 FlashScore 33.0 · 0/22 fully correct53.1 min · $0.65 per task22 tasks

Time per Task

Mean minutes per task · Lower is better

3.5Sol6.8Opus 5.527.0Argon53.1DeepSeekGPT-6.1 SolScore 91.3 · 14/32 fully correct3.5 min · $0.43 per task22 tasksClaude Opus 5.5Score 97.8 · 15/31 fully correct6.8 min · $3.53 per task22 tasksGemini 4 ArgonScore 79.7 · 14/31 fully correct27.0 min · $1.94 per task22 tasksDeepSeek V4.1 FlashScore 33.0 · 0/22 fully correct53.1 min · $0.65 per task22 tasks

Cost per Task

Mean USD per task · Lower is better

$0.43Sol$0.65DeepSeek$1.94Argon$3.53Opus 5.5GPT-6.1 SolScore 91.3 · 14/32 fully correct3.5 min · $0.43 per task22 tasksDeepSeek V4.1 FlashScore 33.0 · 0/22 fully correct53.1 min · $0.65 per task22 tasksGemini 4 ArgonScore 79.7 · 14/31 fully correct27.0 min · $1.94 per task22 tasksClaude Opus 5.5Score 97.8 · 15/31 fully correct6.8 min · $3.53 per task22 tasks

Pass rate vs. Cost per Task

Tasks fully correct · mean USD per task

Most attractive quadrant020406080100$0.1$0.2$0.5$1$2$5$10Cost per task (USD, log scale)Pass rate (%)Claude Opus 5.5Gemini 4 ArgonGPT-6.1 SolDeepSeek V4.1 FlashClaude Opus 5.5Pass rate 55% · score 98$3.53 per task15/31 fully correctGPT-6.1 SolPass rate 45% · score 91$0.43 per task14/32 fully correctGemini 4 ArgonPass rate 50% · score 80$1.94 per task14/31 fully correctDeepSeek V4.1 FlashPass rate 0% · score 33$0.65 per task0/22 fully correctMost attractive quadrant020406080100$0.1$0.2$0.5$1$2$5$10Cost per task (USD, log scale)Pass rate (%)Claude Opus 5.5Gemini 4 ArgonGPT-6.1 SolDeepSeek V4.1 FlashClaude Opus 5.5Pass rate 55% · score 98$3.53 per task15/31 fully correctGPT-6.1 SolPass rate 45% · score 91$0.43 per task14/32 fully correctGemini 4 ArgonPass rate 50% · score 80$1.94 per task14/31 fully correctDeepSeek V4.1 FlashPass rate 0% · score 33$0.65 per task0/22 fully correct
  • Claude Opus 5.5
  • GPT-6.1 Sol
  • Gemini 4 Argon
  • DeepSeek V4.1 Flash
  • Most attractive quadrant
  • Model Pareto frontier

Score by Domain

Mean score, 0–100 · Higher is better

PLC logicElectrical /EPLANAcceptance /FATMechanical /processCAD50100Claude Opus 5.5 · PLC logic: 99Claude Opus 5.5 · Electrical / EPLAN: 100Claude Opus 5.5 · Acceptance / FAT: 99Claude Opus 5.5 · Mechanical / process: 93Claude Opus 5.5 · CAD: 95Gemini 4 Argon · PLC logic: 77Gemini 4 Argon · Electrical / EPLAN: 50Gemini 4 Argon · Acceptance / FAT: 100Gemini 4 Argon · Mechanical / process: 48Gemini 4 Argon · CAD: 97GPT-6.1 Sol · PLC logic: 91GPT-6.1 Sol · Electrical / EPLAN: 99GPT-6.1 Sol · Acceptance / FAT: 98GPT-6.1 Sol · Mechanical / process: 94GPT-6.1 Sol · CAD: 94DeepSeek V4.1 Flash · PLC logic: 38DeepSeek V4.1 Flash · Electrical / EPLAN: 0DeepSeek V4.1 Flash · Acceptance / FAT: 36DeepSeek V4.1 Flash · Mechanical / process: 41DeepSeek V4.1 Flash · CAD: 0
  • Claude Opus 5.5
  • Gemini 4 Argon
  • GPT-6.1 Sol
  • DeepSeek V4.1 Flash

Results per Task

22 tasks · 4 models

TaskClaude Opus 5.5Gemini 4 ArgonGPT-6.1 SolDeepSeek V4.1 Flash
Clone a fan chain end to endClaude Opus 5.5 · 97Gemini 4 Argon · 46GPT-6.1 Sol · 46DeepSeek V4.1 Flash · 21
Eight-part site change packageClaude Opus 5.5 · 100Gemini 4 Argon · 100GPT-6.1 Sol · 36DeepSeek V4.1 Flash · 31
Cross-reference all 48 outputsClaude Opus 5.5 · 89Gemini 4 Argon · 100GPT-6.1 Sol · 89DeepSeek V4.1 Flash · 0
Plant job: symptoms, change, spec checkClaude Opus 5.5 · 100Gemini 4 Argon · 85GPT-6.1 Sol · 77DeepSeek V4.1 Flash · 5
IO tag → networks, HMI, alarmsClaude Opus 5.5 · 100Gemini 4 Argon · 99GPT-6.1 Sol · 100DeepSeek V4.1 Flash · 84
IO tag → networks, HMI, alarms (code)Claude Opus 5.5 · 100Gemini 4 Argon · 0GPT-6.1 Sol · 99DeepSeek V4.1 Flash · 0
Screen object → tags, writers, IOClaude Opus 5.5 · 97Gemini 4 Argon · 100GPT-6.1 Sol · 100DeepSeek V4.1 Flash · 90
Screen object → tags, writers, IO (code)Claude Opus 5.5 · 100Gemini 4 Argon · 100GPT-6.1 Sol · 100DeepSeek V4.1 Flash · 0
IO, safety chain and change impactClaude Opus 5.5 · 100Gemini 4 Argon · 50GPT-6.1 Sol · 99DeepSeek V4.1 Flash · 0
FAT protocol coverage auditClaude Opus 5.5 · 100Gemini 4 Argon · 100GPT-6.1 Sol · 100DeepSeek V4.1 Flash · 93
Predict the FAT resultClaude Opus 5.5 · 98Gemini 4 Argon · 100GPT-6.1 Sol · 98DeepSeek V4.1 Flash · 8
Write the burner FAT sectionClaude Opus 5.5 · 100Gemini 4 Argon · 100GPT-6.1 Sol · 95DeepSeek V4.1 Flash · 8
Process-limit audit vs manualsClaude Opus 5.5 · 87Gemini 4 Argon · 95GPT-6.1 Sol · 90DeepSeek V4.1 Flash · 81
Spare-parts integrity auditClaude Opus 5.5 · 98Gemini 4 Argon · 1GPT-6.1 Sol · 98DeepSeek V4.1 Flash · 1
Manufacturing release of the liftClaude Opus 5.5 · 100Gemini 4 Argon · 100GPT-6.1 Sol · 100DeepSeek V4.1 Flash · 0
Scissor mechanism reviewClaude Opus 5.5 · 90Gemini 4 Argon · 95GPT-6.1 Sol · 88DeepSeek V4.1 Flash · 0
Commission the conveyorClaude Opus 5.5 · 100Gemini 4 Argon · 100GPT-6.1 Sol · 100DeepSeek V4.1 Flash · 48
Commission the conveyor (rules unstated, code)Claude Opus 5.5 · 100Gemini 4 Argon · 97GPT-6.1 Sol · 97DeepSeek V4.1 Flash · 42
Commission the conveyor (rules unstated)Claude Opus 5.5 · 98Gemini 4 Argon · 50GPT-6.1 Sol · 100DeepSeek V4.1 Flash · 74
Commission the ovenClaude Opus 5.5 · 99Gemini 4 Argon · 100GPT-6.1 Sol · 100DeepSeek V4.1 Flash · 25
Commission the oven (rules unstated, code)Claude Opus 5.5 · 99Gemini 4 Argon · 89GPT-6.1 Sol · 100DeepSeek V4.1 Flash · 61
Commission the oven (rules unstated)Claude Opus 5.5 · 100Gemini 4 Argon · 49GPT-6.1 Sol · 97DeepSeek V4.1 Flash · 57
Pass rate55% · score 9850% · score 8045% · score 910% · score 33

Full score (100) Partial (1–99) ZeroEach task scores 0–100. Overall score = mean over the tasks a model ran. A dash = not run yet. One run per task; borderline tasks have two.

IO, safety chain and change impactElectrical dossier109 turns$12 cap229 files · 6.6 MBOpus 5.5ArgonSolDeepSeek

Brief

The workspace holds the engineering data of one industrial oven as text (read INDEX.txt first): the electrical schematic (one file per PDF page), the PLC tag tables, program blocks and hardware list (TIA Portal XML/CSV), the HMI export, the HMI alarm texts and the signed software acceptance protocols (the IO list). The documents were made by different people at different times and are not consistent with each other. You prepare the commissioning dossier for the site acceptance test, in three parts.

3 parts, graded item by item · IO reconciliation (108 channels) + safety-chain trace + change impact of 6 re-addressed signals

schematic page readingXML tag tablesrule application over 108 channelssafety-chain tracing across sheetsLAD/FBD network numberingPLC->HMI tag linksterminal diagramscross-document reconciliation

Workspace

  • acceptance_protocols/5 · 15 KBsoftware acceptance protocols (the signed IO list)
  • hmi/17 · 3.0 MBWinCC HMI screens and HMI tag tables (Openness export)screens/ 15tags/ 2
  • plc/102 · 3.4 MBPLC tag tables (TIA Portal Openness export, SimaticML) · hardware configuration · network nodes · program blocksblocks/ 81tag_tables/ 19
  • schematic_EN/102 · 241 KBelectrical schematic (EPLAN)
  • texts/2 · 9 KBHMI alarm texts EN / FR as delivered to the customer · HMI user texts EN / FR
  • INDEX.txt2 KBworkspace guide: what each folder holds

Grader

  • eleclib.py420 lines
  • grade_elec.py394 lines
  • Deterministic, item by item against reference answers; no LLM judge.

Budget

  • 109turns, stated in the prompt
  • $12per-run cost cap (ours)

Outcomes

Opus 5.5best 100$5.71/run
Argonbest 99$1.56/run
Solbest 100$0.51/run
DeepSeekbest 0$0.59/run
Earlier tasks (mostly solved)138 runs · 20 tasks · medium effort

Solved on content: these fail only on a tight turn budget, so they are not in the headline.

FamilyOpus 5.5ArgonSolDeepSeek
Handover records2 tasks3/4 · 750/4 · 24not runnot run

pass, every item exact fail stopped by our cost cap2/7 = runs that pass · 82 = mean score

#ModelScoreFiles onlyWith codeCost / taskTime / task
1Claude Opus 5.5Anthropic · medium effort878193$1.4996s
2Gemini 4 ArgonGoogle · medium effort838087$1.45224s

Claude Opus 5.568 runs

✓ 58solved correctly

✗ 10mistakes1 wrong answer · 9 ran out of turns

Mistake rate
15% 10 of 68 runs
Fixes its own errors
98% 122 of 125 tool errors

PLC 39/48CAD 7/8Docs 12/12

Gemini 4 Argon70 runs

✓ 52solved correctly

✗ 18mistakes7 wrong answers · 6 ran out of turns · 5 stopped early

Mistake rate
26% 18 of 70 runs
Fixes its own errors
92% 68 of 74 tool errors

PLC 43/52CAD 2/6Docs 7/12

Accuracy, time and cost

Accuracy

Mean score out of 100. Higher is better.

81Claude Opus 5.580Gemini 4 Argon

Time per task

Average wall time in seconds. Lower is better.

72sClaude Opus 5.5176sGemini 4 Argon

Cost per task

Average estimated cost in USD. Lower is better.

$1.19Gemini 4 Argon$1.60Claude Opus 5.5
22% vs 100%

Long ladder logic separates the models

With file tools only, Opus 5.5 often runs out of turns reading the oven logic. Argon reads in larger steps and finishes.

100%

A code tool closes the gap

Given a sandboxed Python tool, both models solve the hard tasks, about 24× cheaper than reading by hand.

Where it fails

A few failures we keep coming back to: what the model said, and what is real.

Real Siemens TIA Portal V19The oven project the PLC tasks use, opened in TIA Portal.
Tour, 38 s
Project tree: the oven PLC
Project tree: the oven PLC
Device view: CPU 1512SP F-1 PN
Device view: CPU 1512SP F-1 PN
HMI: the oven screen
HMI: the oven screen
FC_Oven compiles: 0 errors
FC_Oven compiles: 0 errors

Recreate the engineers' commits · Claude Opus 5.5

One realistic, terse change ticket in a chain of 6 real commits.

Opus 5.5
0 of 71 I/O lines right in the two acceptance annexes
Engineers' commit
71 I/O lines, re-addressed

Same chain, same files. Only the ticket wording differs.

Claude Opus 5.5

Asked to copy an alarm text exactly, it wrote its own. On all 4 drives.

It wrote
“Frequency converter error”
The file says
“Inverter error”

Everything else in the answer was right. One invented text makes it a fail.

All three models

A timing value hidden in the control program. Missed by every model: 0 of 9 runs.

Every model
No problem found
Real
The program stops the fans after 20 seconds. The manual says “after a few minutes”.

Across Opus 5.5, GPT-6.1 Sol and Gemini 4 Argon. No run found it.

AuditedFailures are audited against the source files; 18 of 22 Opus failures were genuine model mistakes, none were knowledge gaps.

For research labs.
Evaluate on real engineering work.

EvalEvaluation accessRun your model on the long-horizon bench.
Full envThe full environmentWindows + Siemens TIA VM, or Docker.
2.1 TB128 real projectsThe raw engineering archive behind the bench.
243Commits of engineer history per projectEach commit → a recreate-the-diff task.

The project

The lift, in real CAD

A hydraulic scissor lift that raises 1,000 kg by 1.3 m, designed by a real engineering office. This is its own 3D model and its own cutting files. Turn it, take it apart, and see where a model got the design wrong.

Load
1,000 kg
Lift height
1.3 m
Parts in the model
1,160
Laser-cut parts
56
3D model

Drag to turn · Scroll to zoom · Hover a part for its name · Red pins mark a model's mistakes

5.0 mmREJECTED

If Argon's number were used:

  1. Deck measured at 5.0 mm
  2. Spec says 4.0 mm, so inspection fails
  3. A lift that meets spec is held back

With Opus 5.5's 4.0 mm: passes, ships (2/3 runs).

Argon flagged deck_thickness = false in 3/3 runs · runs/gemini-4-argon/lift_model_vs_spec

Who fixed it better

Two traps in the lift's files. Opus 5.5 saw through both.

1 mm raised patchArgon5.0 mm ✗Opus 5.54.0 mm ✓

1Deck plate. Real plate: 4.0 mm. A tiny raised patch fools a bounding box.

✓ Opus 5.5 2/3 runs✗ Argon 0/3 runs

runs/*/lift_model_vs_spec/python_run1-3 · graders/cad_reference.json

Opus 5.5

7,594 mm² ✓

Took away 365 mm² as holes. Real holes: 365 mm².

Argon

5,471 mm² ✗ −28 %

Took away 2,488 mm² as holes. Real holes: 365 mm².

2Lower flange. Which loops are holes? Fill = metal the model counted. Real: 7,594 mm².

✓ Opus 5.5 right✗ Argon wrong loops

runs/claude-opus-5-5/lift_sheet_order/python_run1 · runs/gemini-4-argon/lift_sheet_order/python_run1 · TTN101.81.03.002.dxf · hover a flange for the numbers

Coming soon

Physical verification.
Scored on real machines.

Today every answer is checked against the original engineering files. Next, the same tasks run on real hardware: a controller on a test rig, parts cut from the model's own drawings.

  • PLC programs on a real controller hardware in the loop
  • CAD parts cut and assembled fit and tolerance
  • Robot tasks on a bench pick, place, assemble