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Llama 4 Scout 17B 16E Instruct vs OpenVLA 7B

At a Glance

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OpenVLA 7BOpenVLA Research Team
Pricing and Limits
Context windowMaximum documented tokens10,000KNot reported
Model facts checkedAug 28, 2026View model evidence →Aug 29, 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

FieldLlama-4-Scout-17B-16E-InstructOpenVLA 7B
DeveloperMetaOpenVLA Research Team
FamilyLlama 4 Scout 17b 16e InstructOpenVLA
ModelLlama-4-Scout-17B-16E-InstructOpenVLA 7B
VersionLlama-4-Scout-17B-16E-Instruct7B
Lifecycleactiveactive
Released2025-04-052024-06-13
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image, Robot state
Output modalitiesTextRobot action
Context window10,000KUnknown
Total parameters108.6B7B
Active parameters17BUnknown
LicenseotherUnknown
Open weightsYesYes
API availableYesNo
Self-hostableYesYes
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)Unknown
Capabilitieschat, generation, toolscross-embodiment, fine-tuning, generalist-manipulation
Robotics model typeUnknownVision-language-action model
Action representationUnknownTokenized actions decoded to continuous robot controls
Control architectureUnknownFused SigLIP and DINOv2 visual encoder with Llama 2 7B backbone
Inference locationUnknownFlexible
Native control rate (Hz)UnknownUnknown
Supported embodimentsUnknownWidowX, Google Robot, Franka Panda
Training dataUnknown970,000 robot manipulation trajectories from Open X-Embodiment described by the authors.

Llama 4 Scout 17B 16E Instruct Capabilities

chatgenerationtools
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDmeta-llama/Llama-4-Scout-17B-16E-Instruct

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

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Primary Evidence

Sources and Freshness

meta-llama/Llama-4-Scout-17B-16E-Instruct developer model repositoryMeta · observed Aug 28, 2026OpenVLA: An Open-Source Vision-Language-Action ModelOpenVLA research team · observed Aug 29, 2026

Questions

Llama 4 Scout 17B 16E Instruct vs OpenVLA 7B FAQs

Is Llama 4 Scout 17B 16E Instruct or OpenVLA 7B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Llama 4 Scout 17B 16E Instruct and OpenVLA 7B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Llama 4 Scout 17B 16E Instruct or OpenVLA 7B?+

Only Llama 4 Scout 17B 16E Instruct has a directly sourced input price: $0.10 per million tokens. Only Llama 4 Scout 17B 16E Instruct has a directly sourced output price: $0.30 per million tokens.

Which has a larger context window, Llama 4 Scout 17B 16E Instruct or OpenVLA 7B?+

Neither model has a larger sourced context window in this comparison. Llama 4 Scout 17B 16E Instruct is 10,000K and OpenVLA 7B is —.

Which performs better in benchmarks, Llama 4 Scout 17B 16E Instruct or OpenVLA 7B?+

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

Can Llama 4 Scout 17B 16E Instruct or OpenVLA 7B be self-hosted?+

Both models have the same recorded self-hosting status: supported. Llama 4 Scout 17B 16E Instruct is open weight; OpenVLA 7B is open weight.

Can Llama 4 Scout 17B 16E Instruct and OpenVLA 7B understand images?+

Llama 4 Scout 17B 16E Instruct 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, Llama 4 Scout 17B 16E Instruct or OpenVLA 7B?+

Neither has a larger sourced maximum output. Llama 4 Scout 17B 16E Instruct is — and OpenVLA 7B is —.

Do Llama 4 Scout 17B 16E Instruct and OpenVLA 7B support reasoning and tool use?+

Llama 4 Scout 17B 16E Instruct: tool calling and image input. OpenVLA 7B: image input. Feature support does not establish relative quality.

Which is available from more inference providers, Llama 4 Scout 17B 16E Instruct or OpenVLA 7B?+

Llama 4 Scout 17B 16E Instruct has 4 sourced provider routes; OpenVLA 7B has 0, so Llama 4 Scout 17B 16E Instruct has broader tracked availability.

Which offers better value, Llama 4 Scout 17B 16E Instruct 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.

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