MolmoAct 2 vs pi 0.7
At a Glance
| Compare | MolmoAct 2Ai2 | pi 0.7Physical Intelligence |
|---|---|---|
| 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
pi 0.7Physical Intelligence source ↗Side-by-Side Facts
| Field | MolmoAct 2 | pi 0.7 |
|---|---|---|
| Developer | Ai2 | Physical Intelligence |
| Family | MolmoAct 2 | pi |
| Model | MolmoAct 2 | pi 0.7 |
| Version | 2 | 0.7 |
| Lifecycle | active | active |
| Released | 2026-05-05 | 2026-04-16 |
| 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 | Unknown |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | No | Unknown |
| Self-hostable | Yes | Unknown |
| Provider access | Unknown | Unknown |
| Capabilities | action-reasoning, bimanual-manipulation, depth-reasoning, fine-tuning | cross-embodiment, dexterous-manipulation, language-steering, visual-subgoals |
| Robotics model type | Action reasoning model | Vision-language-action model |
| Action representation | Flow-matching continuous action expert | Continuous robot actions conditioned by multimodal prompts |
| Control architecture | Molmo 2-ER backbone with KV-cache bridge and action expert | High-level policy, world model, and action expert |
| Inference location | Flexible | Unknown |
| Native control rate (Hz) | Unknown | Unknown |
| Supported embodiments | SO-100, SO-101, Franka, WidowX, bimanual YAM | mobile manipulators, bimanual UR5e, multiple fixed manipulators |
| Training data | Open bimanual YAM, SO-100/SO-101, DROID, BC-Z, Fractal, Bridge, and prior MolmoAct data described by Ai2. | Robot demonstrations, autonomous data, egocentric human data, and multimodal web data described by the publisher. |
MolmoAct 2 Capabilities
pi 0.7 Capabilities
Primary Evidence
Sources and Freshness
Questions
MolmoAct 2 vs pi 0.7 FAQs
Is MolmoAct 2 or pi 0.7 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both MolmoAct 2 and pi 0.7, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, MolmoAct 2 or pi 0.7?+
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 pi 0.7?+
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 pi 0.7?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can MolmoAct 2 or pi 0.7 be self-hosted?+
MolmoAct 2's sourced self-hosting status is supported; pi 0.7's is unknown. An unknown status does not establish support or lack of support. MolmoAct 2 is open weight; pi 0.7 is not marked open weight.
Can MolmoAct 2 and pi 0.7 understand images?+
MolmoAct 2 is documented with image input; pi 0.7 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, MolmoAct 2 or pi 0.7?+
Neither model has a sourced maximum output in this comparison, so a larger limit cannot be determined.
Do MolmoAct 2 and pi 0.7 support reasoning and tool use?+
MolmoAct 2: reasoning and image input. pi 0.7: image input. Feature support does not establish relative quality.
Which is available from more inference providers, MolmoAct 2 or pi 0.7?+
MolmoAct 2 has 0 sourced provider routes; pi 0.7 has 0, a tie.
Which offers better value, MolmoAct 2 or pi 0.7?+
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.