sfcompute vs Tensorlake
Sandbox Benchmark Comparison · Updated October 30, 2026
vs
sfcompute was faster in both shared sandbox benchmarks.
Head to head
Burst TTI
Median time to interactive over time
sfcomputeTensorlake
Median total workload time over time
sfcomputeTensorlake
Cost per DAX run
sfcompute
Per GiB-hour (parkable)$0.0085per run
41.72s median at $0.7315/hr
Rollout sandboxes at $0.04572/GiB-hr while active (16 GiB); parked/idle drops to ~$0.000139/GiB-hr. Interactive cpu-8 node is $0.4824/hr with a 15-min minimum.
Source pricing pageTensorlake
Active CPU + allocated RAM$0.017per run
78.16s median at $0.8000/hr
$0.07/core-hr active CPU + $0.015/GB-hr RAM (on-demand rates; Pro is ~40% lower).
Source pricing pageWork at sfcompute or Tensorlake? See where you stand every day, with full run logs, not just on benchmark Friday.Get stealth benchmarks →
Methodology
- One workload, every provider. The same script, payload, and model hit every provider, addressed the way its own API expects. Nobody gets a tuned or special path.
- Repeated on a schedule. Every suite runs many iterations per provider, automated on a recurring schedule, so results reflect steady state rather than one lucky request.
- Raw results published. Every run is committed as JSON to the public benchmarks repo, next to the code that produced it. Nothing is cherry-picked or held back.
- How this comparison is built. Each benchmark compares the two providers' medians; results within 5% count as roughly even. A comparison is published only when both providers completed at least 50% of runs in 2 or more shared benchmarks run in the last 30 days. If a provider’s latest run of a benchmark failed, its most recent successful run from that window is used instead.
Frequently asked questions
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sfcompute was faster in both shared sandbox benchmarks. In Burst TTI (October 30, 2026), sfcompute had a median time to interactive of 322ms versus 1.03s for Tensorlake, 3.19x faster. In DAX (October 9, 2026), sfcompute had a median total workload time of 41.72s versus 78.16s for Tensorlake, 1.87x faster.
More comparisons
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