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OpenVLA 7B vs Jev

At a Glance

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OpenVLA 7BOpenVLA Research Team
JevTypeSafe
Pricing and Limits
Context windowMaximum documented tokensNot reported64K
Model facts checkedAug 29, 2026View model evidence →Sep 17, 2026View model evidence →
Different Model RolesThese models do not share a sourced market category. Their primary-source facts remain comparable below, while performance claims require matched 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

FieldOpenVLA 7BJev
DeveloperOpenVLA Research TeamTypeSafe
FamilyOpenVLAJev
ModelOpenVLA 7BJev
Version7BJev
Lifecycleactiveactive
Released2024-06-132026-09-15
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Robot stateText, Model-specific input
Output modalitiesRobot actionModel-specific input
Context windowUnknown64K
Total parameters7BUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsYesNo
API availableNoYes
Self-hostableYesNo
Provider accessUnknownTypeSafe (Standard)
Capabilitiescross-embodiment, fine-tuning, generalist-manipulationcalibrated-confidence, parallel-evaluation, structured_outputs, typed-decisions
Maximum Choice cardinalityUnknown255 options
Default request rate limitUnknown1200 requests per minute
State plus longest question limitUnknown32000 tokens
Combined state and questions limitUnknown64000 tokens
Default token rate limitUnknown250000 tokens per second
Robotics model typeVision-language-action modelUnknown
Action representationTokenized actions decoded to continuous robot controlsUnknown
Control architectureFused SigLIP and DINOv2 visual encoder with Llama 2 7B backboneUnknown
Inference locationFlexibleUnknown
Native control rate (Hz)UnknownUnknown
Supported embodimentsWidowX, Google Robot, Franka PandaUnknown
Training data970,000 robot manipulation trajectories from Open X-Embodiment described by the authors.Unknown

OpenVLA 7B Capabilities

cross-embodimentfine-tuninggeneralist-manipulation
Model typeVision-language-action model
InferenceFlexible
Action representationTokenized actions decoded to continuous robot controls
Supported embodiments3
Canonical IDopenvla/openvla-7b

Jev Capabilities

calibrated-confidenceparallel-evaluationstructured outputstyped-decisions
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDtypesafe/jev

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Primary Evidence

Sources and Freshness

OpenVLA: An Open-Source Vision-Language-Action ModelOpenVLA research team · observed Aug 29, 2026Models | TypeSafe AITypeSafe · observed Sep 17, 2026

Questions

OpenVLA 7B vs Jev FAQs

Is OpenVLA 7B or Jev better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both OpenVLA 7B and Jev, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, OpenVLA 7B or Jev?+

Only Jev has a directly sourced input price: $0.042 per million tokens. Only Jev has a directly sourced output price: $0.000 per million tokens.

Which has a larger context window, OpenVLA 7B or Jev?+

Neither model has a larger sourced context window in this comparison. OpenVLA 7B is — and Jev is 64K.

Which performs better in benchmarks, OpenVLA 7B or Jev?+

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

Can OpenVLA 7B or Jev be self-hosted?+

OpenVLA 7B is the only model in this pair currently marked as self-hostable. OpenVLA 7B is open weight; Jev is not marked open weight.

Can OpenVLA 7B and Jev understand images?+

OpenVLA 7B is documented with image input; Jev is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, OpenVLA 7B or Jev?+

Neither has a larger sourced maximum output. OpenVLA 7B is — and Jev is —.

Do OpenVLA 7B and Jev support reasoning and tool use?+

OpenVLA 7B: image input. Jev: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, OpenVLA 7B or Jev?+

OpenVLA 7B has 0 sourced provider routes; Jev has 1, so Jev has broader tracked availability.

Which offers better value, OpenVLA 7B or Jev?+

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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