MolmoAct 2 vs SOMA X v0.3.0

At a Glance

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Pricing and Limits
Context windowMaximum documented tokensNot reportedNot reported
Model facts checkedAug 29, 2026View model evidence →Sep 2, 2026View model evidence →

Available Benchmarks

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldMolmoAct 2SOMA-X v0.3.0
DeveloperAi2NVIDIA
FamilyMolmoAct 2Soma X
ModelMolmoAct 2SOMA-X v0.3.0
Version2SOMA-X v0.3.0
Lifecycleactiveactive
Released2026-05-052026-09-02
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Robot stateModel-specific input
Output modalitiesRobot action3D
Context windowUnknownUnknown
Total parameters5BUnknown
Active parametersUnknownUnknown
Licenseapache-2.0apache-2.0
Open weightsYesYes
API availableNoNo
Self-hostableYesYes
Provider accessUnknownUnknown
Capabilitiesaction-reasoning, bimanual-manipulation, depth-reasoning, fine-tuninganimation, hand-modeling, human-body-modeling, motion-retargeting, pose-inversion, simulation
Robotics model typeAction reasoning modelUnknown
Action representationFlow-matching continuous action expertUnknown
Control architectureMolmo 2-ER backbone with KV-cache bridge and action expertUnknown
Inference locationFlexibleUnknown
Native control rate (Hz)UnknownUnknown
Supported embodimentsSO-100, SO-101, Franka, WidowX, bimanual YAMUnknown
Training dataOpen bimanual YAM, SO-100/SO-101, DROID, BC-Z, Fractal, Bridge, and prior MolmoAct data described by Ai2.Unknown

MolmoAct 2 Capabilities

action-reasoningbimanual-manipulationdepth-reasoningfine-tuning
Model typeAction reasoning model
InferenceFlexible
Action representationFlow-matching continuous action expert
Supported embodiments5
Canonical IDallenai/MolmoAct2

SOMA X v0.3.0 Capabilities

animationhand-modelinghuman-body-modelingmotion-retargetingpose-inversionsimulation
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDnvidia/SOMA-X-v0.3.0

Primary Evidence

Sources and Freshness

Questions

MolmoAct 2 vs SOMA X v0.3.0 FAQs

Is MolmoAct 2 or SOMA X v0.3.0 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both MolmoAct 2 and SOMA X v0.3.0, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, MolmoAct 2 or SOMA X v0.3.0?+

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 SOMA X v0.3.0?+

Neither model has a larger sourced context window in this comparison. MolmoAct 2 is — and SOMA X v0.3.0 is —.

Which performs better in benchmarks, MolmoAct 2 or SOMA X v0.3.0?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can MolmoAct 2 or SOMA X v0.3.0 be self-hosted?+

Both models have the same recorded self-hosting status: supported. MolmoAct 2 is open weight; SOMA X v0.3.0 is open weight.

Can MolmoAct 2 and SOMA X v0.3.0 understand images?+

MolmoAct 2 is documented with image input; SOMA X v0.3.0 is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, MolmoAct 2 or SOMA X v0.3.0?+

Neither has a larger sourced maximum output. MolmoAct 2 is — and SOMA X v0.3.0 is —.

Do MolmoAct 2 and SOMA X v0.3.0 support reasoning and tool use?+

MolmoAct 2: reasoning and image input. SOMA X v0.3.0: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, MolmoAct 2 or SOMA X v0.3.0?+

MolmoAct 2 has 0 sourced provider routes; SOMA X v0.3.0 has 0, a tie.

Which offers better value, MolmoAct 2 or SOMA X v0.3.0?+

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.

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