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Llama 4 Maverick 17B 128E Instruct vs pi 0.7

At a Glance

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pi 0.7Physical Intelligence
Pricing and Limits
Context windowMaximum documented tokens1,000KNot 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-Maverick-17B-128E-Instructpi 0.7
DeveloperMetaPhysical Intelligence
FamilyLlama 4 Maverick 17b 128e Instructpi
ModelLlama-4-Maverick-17B-128E-Instructpi 0.7
VersionLlama-4-Maverick-17B-128E-Instruct0.7
Lifecycleactiveactive
Released2025-04-052026-04-16
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image, Robot state
Output modalitiesTextRobot action
Context window1,000KUnknown
Total parameters401.6BUnknown
Active parameters17BUnknown
LicenseotherUnknown
Open weightsYesNo
API availableYesUnknown
Self-hostableYesUnknown
Provider accessOpenrouter (Standard)Unknown
Capabilitieschat, generation, toolscross-embodiment, dexterous-manipulation, language-steering, visual-subgoals
Robotics model typeUnknownVision-language-action model
Action representationUnknownContinuous robot actions conditioned by multimodal prompts
Control architectureUnknownHigh-level policy, world model, and action expert
Inference locationUnknownUnknown
Native control rate (Hz)UnknownUnknown
Supported embodimentsUnknownmobile manipulators, bimanual UR5e, multiple fixed manipulators
Training dataUnknownRobot demonstrations, autonomous data, egocentric human data, and multimodal web data described by the publisher.

Llama 4 Maverick 17B 128E Instruct Capabilities

chatgenerationtools
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDmeta-llama/Llama-4-Maverick-17B-128E-Instruct

pi 0.7 Capabilities

cross-embodimentdexterous-manipulationlanguage-steeringvisual-subgoals
Model typeVision-language-action model
InferenceUnknown
Action representationContinuous robot actions conditioned by multimodal prompts
Supported embodiments3
Canonical IDphysical-intelligence/pi-0.7

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Primary Evidence

Sources and Freshness

meta-llama/Llama-4-Maverick-17B-128E-Instruct developer model repositoryMeta · observed Aug 28, 2026pi 0.7: a Steerable Model with Emergent CapabilitiesPhysical Intelligence · observed Aug 29, 2026

Questions

Llama 4 Maverick 17B 128E Instruct vs pi 0.7 FAQs

Is Llama 4 Maverick 17B 128E Instruct or pi 0.7 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Llama 4 Maverick 17B 128E Instruct and pi 0.7, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Llama 4 Maverick 17B 128E Instruct or pi 0.7?+

Only Llama 4 Maverick 17B 128E Instruct has a directly sourced input price: $0.1875 per million tokens. Only Llama 4 Maverick 17B 128E Instruct has a directly sourced output price: $0.6525 per million tokens.

Which has a larger context window, Llama 4 Maverick 17B 128E Instruct or pi 0.7?+

Neither model has a larger sourced context window in this comparison. Llama 4 Maverick 17B 128E Instruct is 1,000K and pi 0.7 is —.

Which performs better in benchmarks, Llama 4 Maverick 17B 128E Instruct 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 Llama 4 Maverick 17B 128E Instruct or pi 0.7 be self-hosted?+

Llama 4 Maverick 17B 128E Instruct is the only model in this pair currently marked as self-hostable. Llama 4 Maverick 17B 128E Instruct is open weight; pi 0.7 is not marked open weight.

Can Llama 4 Maverick 17B 128E Instruct and pi 0.7 understand images?+

Llama 4 Maverick 17B 128E Instruct 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, Llama 4 Maverick 17B 128E Instruct or pi 0.7?+

Neither has a larger sourced maximum output. Llama 4 Maverick 17B 128E Instruct is — and pi 0.7 is —.

Do Llama 4 Maverick 17B 128E Instruct and pi 0.7 support reasoning and tool use?+

Llama 4 Maverick 17B 128E Instruct: tool calling and image input. pi 0.7: image input. Feature support does not establish relative quality.

Which is available from more inference providers, Llama 4 Maverick 17B 128E Instruct or pi 0.7?+

Llama 4 Maverick 17B 128E Instruct has 1 sourced provider route; pi 0.7 has 0, so Llama 4 Maverick 17B 128E Instruct has broader tracked availability.

Which offers better value, Llama 4 Maverick 17B 128E Instruct 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.

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