SmolVLA
Facts
- Released
- 2025-06 4 Source
- Parameters
- 0.45 B 3 Source
- Architecture
- VLM + action expert 0 Source
- License
- Weights model card has no licence tag (LeRobot code repository Apache-2.0) 1 Source
- Commercial
- Commercial terms unverified 0 Source
- Weights
- huggingface.co ↗ 3 Source
- Code
- github.com ↗ 1 Source
- Paper
- arxiv.org ↗ 1 Source
- Input modalities
- rgb · language · state 0 Source
- Action space
- Joints (mainly low-cost arms) 0 Source
- Cross-embodiment
- Mainly community embodiments such as SO-100/101 0 Source
- Pretraining data (hours)
- Unverified 0 Source
- Target forms
- Single arm 0 Source
Sources · 6 sources
Activity signals
Public counters fetched daily from GitHub, Hugging Face and ModelScope. Numbers only; no judgement. · fetched 2026-10-18
Public benchmark scores
As printed in the source; protocols differ between papers. Full table with notes on the benchmarks page.
| Benchmark | Subset | Score | Source |
|---|---|---|---|
| LIBEROSmolVLA 0.24B | avg | 82.8 | paper · Table 2, row 'SmolVLA (0.24B)', LIBERO Avg (87 / 93 / 88 / 63) |
| LIBEROSmolVLA 0.45B (main) | avg | 87.3 | paper · Table 2, row 'SmolVLA (0.45B)', LIBERO Avg |
| LIBEROSmolVLA 2.25B | avg | 88.8 | paper · Table 2, row 'SmolVLA (2.25B)', LIBERO Avg (Spatial 93 / Object 94 / Goal 91 / Long 77) |
| LIBEROSmolVLA 0.45B (main) | goal | 92 | paper · Table 2, row 'SmolVLA (0.45B)', LIBERO Goal |
| LIBEROSmolVLA 0.45B (main) | long | 71 | paper · Table 2, row 'SmolVLA (0.45B)', LIBERO Long |
| LIBEROSmolVLA 0.45B (main) | object | 96 | paper · Table 2, row 'SmolVLA (0.45B)', LIBERO Object |
| LIBEROSmolVLA 0.45B (main) | spatial | 90 | paper · Table 2, row 'SmolVLA (0.45B)', LIBERO Spatial |
| Meta-WorldSmolVLA 0.45B (main) | avg | 57.3 | paper · Table 2, row 'SmolVLA (0.45B)', Meta-World Avg |
| Meta-WorldSmolVLA 0.45B (main) | easy | 82.5 | paper · Table 2, row 'SmolVLA (0.45B)', Meta-World Easy |
| Meta-WorldSmolVLA 0.45B (main) | hard | 45 | paper · Table 2, row 'SmolVLA (0.45B)', Meta-World Hard |
| Meta-WorldSmolVLA 0.45B (main) | medium | 41.8 | paper · Table 2, row 'SmolVLA (0.45B)', Meta-World Medium |
| Meta-WorldSmolVLA 0.45B (main) | very_hard | 60 | paper · Table 2, row 'SmolVLA (0.45B)', Meta-World Very Hard |
| Real-robot evaluation (self-reported)SmolVLA 0.45B (main) | so100_multitask_3_tasks_avg | 78.3 | paper · Table 3 (real-world SO-100), row 'SmolVLA (0.45B)', Avg (Pick-Place 75 / Stacking 90 / Sorting 70) |
| Real-robot evaluation (self-reported)SmolVLA 0.45B (main) | so101_pick_place_lego_in_distribution | 90 | paper · Table 4 (real-world SO-101), row 'SmolVLA (0.45B)', In Distribution |
Deployment recipe
Environment, weights, run command and the pitfalls we hit, exactly as executed on rented GPUs (venv lerobot, 2.0 GB of weights, 2 pitfalls).
Open recipe →Record history
Latency & cost
| Hardware | p50 ms | p95 ms | Peak VRAM | Cost per 1k inferences ¥ | samples |
|---|---|---|---|---|---|
NVIDIA RTX 4090 ¥1.68/h · GongJi Compute (2026) | 170 | 197 | 0.91 GB | 0.079 | 1 Preliminary (n<3) Maintainer measured |
NVIDIA RTX 5090 ¥2.4/h · Runyun 2.4 / GongJi 2.5 / Paratera Cloud 2.98 (2026) | 166 | 170 | 0.91 GB | 0.110 | 1 Preliminary (n<3) Maintainer measured |
NVIDIA A100 80GB no rental price | — | — | — | — no latency data | No data |
NVIDIA Jetson AGX Thor no rental price | — | — | — | — no latency data | No data |
NVIDIA H100 80GB no rental price | — | — | — | — no latency data | No data |
NVIDIA A800 80GB no rental price | 226 | 235 | 0.9 GB | — no rental price for this hardware | 1 Preliminary (n<3) Maintainer measured |
Compatibility
Colored only where we hold evidence. An amber dot means the vendor declares this form as a target; that is a claim, not a verified compatibility.
| Unitree G1 | Unitree H1 | AgiBot Genie G1 | AgileX Piper arm | SO-101 | Franka FR3 / Panda | Fourier GR-2 | WidowX 250 S | Google Robot(Everyday Robots) | ALOHA 2 / Cobot Magic (dual-arm) | Galaxea R1 Pro | Franka Emika Panda | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SmolVLA |
Reproduction records
Did this model run on your robot? Report it with a link (log, video or repo). Records are reviewed by the maintainers; a verified “works” or “works after fine-tuning” upgrades the matrix cell to “community verified” with your link as evidence. Anonymous is fine; nothing but the fields below is stored.
No verified record yet for this model.
Clear direction, grounded judgement.