MolmoAct 2Ai2 source ↗MolmoAct 2 vs OpenVLA 7B
At a Glance
| Compare |  MolmoAct 2Ai2 |  OpenVLA 7BOpenVLA Research Team |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | Not reported | Not reported |
| Model facts checked | Aug 29, 2026View model evidence → | Aug 29, 2026View model evidence → |
Available Benchmarks
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.
MolmoAct 2Ai2 source ↗
OpenVLA 7BOpenVLA research team source ↗Side-by-Side Facts
| Field | MolmoAct 2 | OpenVLA 7B |
|---|---|---|
| Developer | Ai2 | OpenVLA Research Team |
| Family | MolmoAct 2 | OpenVLA |
| Model | MolmoAct 2 | OpenVLA 7B |
| Version | 2 | 7B |
| Lifecycle | active | active |
| Released | 2026-05-05 | 2024-06-13 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Robot state | Text, Image, Robot state |
| Output modalities | Robot action | Robot action |
| Context window | Unknown | Unknown |
| Total parameters | 5B | 7B |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | Yes |
| API available | No | No |
| Self-hostable | Yes | Yes |
| Provider access | Unknown | Unknown |
| Capabilities | action-reasoning, bimanual-manipulation, depth-reasoning, fine-tuning | cross-embodiment, fine-tuning, generalist-manipulation |
| Robotics model type | Action reasoning model | Vision-language-action model |
| Action representation | Flow-matching continuous action expert | Tokenized actions decoded to continuous robot controls |
| Control architecture | Molmo 2-ER backbone with KV-cache bridge and action expert | Fused SigLIP and DINOv2 visual encoder with Llama 2 7B backbone |
| Inference location | Flexible | Flexible |
| Native control rate (Hz) | Unknown | Unknown |
| Supported embodiments | SO-100, SO-101, Franka, WidowX, bimanual YAM | WidowX, Google Robot, Franka Panda |
| Training data | Open bimanual YAM, SO-100/SO-101, DROID, BC-Z, Fractal, Bridge, and prior MolmoAct data described by Ai2. | 970,000 robot manipulation trajectories from Open X-Embodiment described by the authors. |
MolmoAct 2 Capabilities
Model typeAction reasoning model
InferenceFlexible
Action representationFlow-matching continuous action expert
Supported embodiments5
Canonical IDallenai/MolmoAct2
OpenVLA 7B Capabilities
Model typeVision-language-action model
InferenceFlexible
Action representationTokenized actions decoded to continuous robot controls
Supported embodiments3
Canonical IDopenvla/openvla-7b
Related Comparisons
All robotics comparisons →| A | Pair | B | Context |
|---|---|---|---|
MolmoAct 2Ai2 | vs |  Helix 02Figure | cross-developer peersrobotics |
MolmoAct 2Ai2 | vs |  Gemini Robotics 2Google DeepMind | cross-developer peersrobotics |
MolmoAct 2Ai2 | vs |  SmolVLA 450MHugging Face LeRobot | cross-developer peersrobotics |
MolmoAct 2Ai2 | vs |  GR00T N1.7 3BNVIDIA | cross-developer peersrobotics |
MolmoAct 2Ai2 | vs |  pi 0.7Physical Intelligence | cross-developer peersrobotics |
Primary Evidence
Sources and Freshness
Questions
MolmoAct 2 vs OpenVLA 7B FAQs
Is MolmoAct 2 or OpenVLA 7B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both MolmoAct 2 and OpenVLA 7B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, MolmoAct 2 or OpenVLA 7B?+
Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.
Which has a larger context window, MolmoAct 2 or OpenVLA 7B?+
Neither model has a sourced context window in this comparison, so a larger limit cannot be determined.
Which performs better in benchmarks, MolmoAct 2 or OpenVLA 7B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can MolmoAct 2 or OpenVLA 7B be self-hosted?+
Both models have the same sourced self-hosting status: supported. MolmoAct 2 is open weight; OpenVLA 7B is open weight.
Can MolmoAct 2 and OpenVLA 7B understand images?+
MolmoAct 2 is documented with image input; OpenVLA 7B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, MolmoAct 2 or OpenVLA 7B?+
Neither model has a sourced maximum output in this comparison, so a larger limit cannot be determined.
Do MolmoAct 2 and OpenVLA 7B support reasoning and tool use?+
MolmoAct 2: reasoning and image input. OpenVLA 7B: image input. Feature support does not establish relative quality.
Which is available from more inference providers, MolmoAct 2 or OpenVLA 7B?+
MolmoAct 2 has 0 sourced provider routes; OpenVLA 7B has 0, a tie.
Which offers better value, MolmoAct 2 or OpenVLA 7B?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.