MiniMax M2.5 vs pi 0.7

At a Glance

Compare
pi 0.7Physical Intelligence
Pricing and Limits
Context windowMaximum documented tokens197KNot 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

FieldMiniMax-M2.5pi 0.7
DeveloperMiniMaxPhysical Intelligence
FamilyMinimax M2 5pi
ModelMiniMax-M2.5pi 0.7
VersionMiniMax-M2.50.7
Lifecycleactiveactive
Released2026-02-122026-04-16
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image, Robot state
Output modalitiesTextRobot action
Context window197KUnknown
Total parameters228.7BUnknown
Active parametersUnknownUnknown
LicenseotherUnknown
Open weightsYesNo
API availableYesUnknown
Self-hostableYesUnknown
Provider accessHugging Face (Standard), Openrouter (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.

MiniMax M2.5 Capabilities

chatgenerationtools
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDMiniMaxAI/MiniMax-M2.5

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

Primary Evidence

Sources and Freshness

Questions

MiniMax M2.5 vs pi 0.7 FAQs

Is MiniMax M2.5 or pi 0.7 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both MiniMax M2.5 and pi 0.7, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, MiniMax M2.5 or pi 0.7?+

Only MiniMax M2.5 has a directly sourced input price: $0.27 per million tokens. Only MiniMax M2.5 has a directly sourced output price: $1.08 per million tokens.

Which has a larger context window, MiniMax M2.5 or pi 0.7?+

Neither model has a larger sourced context window in this comparison. MiniMax M2.5 is 197K and pi 0.7 is —.

Which performs better in benchmarks, MiniMax M2.5 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 MiniMax M2.5 or pi 0.7 be self-hosted?+

MiniMax M2.5 is the only model in this pair currently marked as self-hostable. MiniMax M2.5 is open weight; pi 0.7 is not marked open weight.

Can MiniMax M2.5 and pi 0.7 understand images?+

MiniMax M2.5 is not 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, MiniMax M2.5 or pi 0.7?+

Neither has a larger sourced maximum output. MiniMax M2.5 is — and pi 0.7 is —.

Do MiniMax M2.5 and pi 0.7 support reasoning and tool use?+

MiniMax M2.5: tool calling. pi 0.7: image input. Feature support does not establish relative quality.

Which is available from more inference providers, MiniMax M2.5 or pi 0.7?+

MiniMax M2.5 has 2 sourced provider routes; pi 0.7 has 0, so MiniMax M2.5 has broader tracked availability.

Which offers better value, MiniMax M2.5 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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