Sliced Inference

Runtimelabs

ModelClick SuccessLoose MatchLatency$/step
RuntimeLabs SVLMself-hosted 4B
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J. Alvarez
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M. Chen
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T. Nakamura
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P. Dubois
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Escalations
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R. Fontaine
K. Whitfield
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September 2026›
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RuntimeLabs SVLM · live log
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gpt-6-astraOpenAI, hosted API
0/22  Ready
cirrus-support.internal/tickets
▦
▤
📊
♪
⚙
J. Alvarez
Sep 12
M. Chen
Sep 12
R. Osei
Sep 11
T. Nakamura
Sep 11
P. Dubois
Sep 10
✉
💬
🕑
⚑
Loading folders…
Order arrived with wrong lens coating
+
Ticket Dispose
×
📁 Customer Service ×
🔍   ×
Searching…
L1
Return Order Update
Searching…
L2
Refund Issues Warranty Claim Delivery Dispute
Searching…
L3
Approved Rejected
L4
Customer ServiceReturnWarranty ClaimApproved
Select Queue *
 
Searching…
Escalations
Delight
Warranty Desk
Assign To *
 
Searching…
R. Fontaine
K. Whitfield
M. Adeyemi
S. Kowalski
Disposition Type
 
Searching…
Pending
Resolved
Escalated
Remarks *
Reviewed and approved per policy.
Is Callback Required
Callback At
14 Sep 2026, 10:00 AM
September 2026›
121314 15161718
OK
SUBMIT
✕
queued 0.00s
flow result —
gpt-6-astra · live log
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Where & why gpt-6-astra fails

Knows the neighborhood, not the address
Mean IoU 0.53 (astra) vs 0.88 (ours) · 81.3% lenient collapses to 44.6% at IoU≥0.5. It lands near the element and stops there.
88–100%
Static click
12–17%
Loads / autocompletes
Fails on dynamic UI, not small UI
open_disposition 12% success, assign-to-random 17% · plain clicks 88–100%. It can't know what a screenshot hasn't shown it yet.
✕ ✓
Doesn't know when to wait
Racing the folder-tree load is the real product's own #1 dispose failure. A one-shot screenshot can't show "still loading."
acc. tokens
More reasoning tokens ≠ more precision
Kimi: 2,028 tok/call, worst score. Ours: ~30 tok, best. Chain-of-thought doesn't recalibrate a coordinate.
gpt-6-astra
Remarks
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RuntimeLabs SVLM
Approved
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Sometimes it doesn't understand the field itself
Action precision: 100% ours vs 82.6% astra — roughly 1 in 6 answers gets click-vs-fill wrong, a level below "where."

1 GPU · 100 in parallel · 1,000 in RAM

GPUs
1
Serving in parallel
100
Slices staged in RAM
1,000
GPU footprint
~24 GB