Dexmal logo

Dexmal

StartupChina

Chinese robotics company (原力灵机) that develops the DM0 and DM0.5 VLA models and the open-source Dexbotic VLA toolbox.

Overview

Dexmal (原力灵机) is a Chinese robotics company that publishes the open-source Dexbotic VLA toolbox and the DM0 (February 2026, with StepFun) and DM0.5 (July 2026) vision-language-action models. DM0.5 uses a Gemma3 4B vision-language backbone with a 680M action expert, and its weights are published on Hugging Face. Dexmal researchers also co-authored MemoryVLA with Tsinghua University.

Sources: github.com (19 Oct 2026) · arxiv.org (16 Feb 2026) · huggingface.co (19 Oct 2026) · huggingface.co (19 Oct 2026) · arxiv.org (26 Aug 2025)

Type
Startup
Website
dexmal.com

Funding history

Private company

No funding rounds have been disclosed in sources we could verify.

Ranking

#22 of 104 model companies · score 67.9 / 100 · updated 19 Oct 2026

  • Published benchmarks 35%88%
  • Open weights 20%67%
  • Adoption 20%73%
  • Released models 15%60%
  • Disclosed funding 10%0%

Each bar shows an input from 0 to 100% before weighting. 2 of 3 listed models have open weights. Most-starred official repository: dexmal/dexbotic (3.3k stars, 19 Oct 2026).

How we rank model companies

The score (0–100) measures public, checkable evidence about a company's robot models. It does not measure private capability. A company that publishes no benchmark results and no weights can still have strong models. Every input is computed from the data on each company page, and every number there links to its source.

InputWeightHow it is measured
Published benchmarks35%For each scored benchmark, the company's best result divided by the best result any company has published, averaged over the benchmarks it reports. No published results scores 0. Results come only from the model's own paper, model card or the official benchmark leaderboard. Scored: LIBERO (4-suite average success, %); SimplerEnv Google Robot, visual matching (%); SimplerEnv Google Robot, variant aggregation (%); SimplerEnv WidowX / Bridge (%); CALVIN ABC→D (average length, 0–5); RoboArena (pairwise rating).
Open weights20%Share of the company's listed models whose weights the public can download.
Adoption20%GitHub stars on the company's most-starred official model repository, on a log scale relative to the most-starred repository in the list. Hugging Face downloads are shown on company pages but not scored, because gated repositories report zero.
Released models15%Number of publicly announced, named models, capped at 5.
Disclosed funding10%The sum of the funding rounds listed on the company's profile that were disclosed in USD, on a log scale from $10M to the largest sum in the list. Rounds reported only in other currencies are listed but not converted or counted. This input applies only to private startups and robot makers. For big-tech divisions, research labs and listed companies it is n/a, and its weight is shared across the other inputs in proportion.

Sources. arXiv papers and official model cards for benchmarks and parameters; official leaderboards (RoboArena); the GitHub and Hugging Face APIs for stars and downloads; company announcements and established press for funding. Missing values are shown as n/a, never estimated.

Updated 19 Oct 2026. Benchmark protocols differ between papers, for example in fine-tuning and number of trials, so small gaps between close scores are not meaningful.

Submit or correct data →

Open-weights models (2)

Dexmal logo

DM0.5

Open weightsVLA

Successor to Dexmal's DM0 (2.4B) vision-language-action model, extended for open-ended instructions, long-horizon tasks and multi-embodiment control; weights and training code released in the OpenDM repository.

Released
9 Jul 2026
Parameters
n/a
License
Apache-2.0 (code); Gemma license (weights)
Embodiments
single-arm, bimanual
GitHub stars
2.3k as of 19 Oct 2026
HF downloads (all time)
1.7k as of 19 Oct 2026
Published benchmark results for DM0.5
BenchmarkResultSource
LIBEROLIBERO success rate (%)99%github.comOpenDM README Benchmark Results table (reported as LIBERO SR; per-suite breakdown not shown in README). As of 19 Oct 2026
Dexmal logo

MemoryVLA

Open weightsVLA

CogACT-style 7B VLA with a perceptual-cognitive memory bank that retrieves and consolidates past tokens for long-horizon manipulation; co-developed with Tsinghua University.

Released
26 Aug 2025
Parameters
7B
License
MIT
Embodiments
single-arm
GitHub stars
363 as of 19 Oct 2026
HF downloads (all time)
607 as of 19 Oct 2026
Published benchmark results for MemoryVLA
BenchmarkResultSource
SimplerEnv WidowXSimplerEnv WidowX (Bridge) average (%)71.9%arxiv.orgTable 1, SimplerEnv-Bridge. As of 26 Aug 2025
SimplerEnv Google VMSimplerEnv Google Robot visual matching average (%)77.7%arxiv.orgTable 2, SimplerEnv-Fractal visual matching. As of 26 Aug 2025
SimplerEnv Google VASimplerEnv Google Robot variant aggregation average (%)67.7%arxiv.orgTable 2, SimplerEnv-Fractal variant aggregation. As of 26 Aug 2025
LIBEROAverage success rate across LIBERO-Spatial/Object/Goal/Long (%)96.7%arxiv.orgTable 3; mean of the four suites (98.4/98.4/96.4/93.4) computed here; the paper's 5-suite average incl. LIBERO-90 is 96.5. As of 26 Aug 2025

Closed or unreleased-weights models (1)

Dexmal logo

DM0

Weights: n/aVLA

Dexmal's first in-house VLA model, released through the Dexbotic toolbox and the predecessor of DM0.5.

Released
10 Feb 2026
Parameters
n/a
License
n/a
Embodiments
single-arm, bimanual
GitHub stars
3.3k as of 19 Oct 2026
HF downloads (all time)
n/a

No benchmark results on a shared public benchmark have been published for this model.