Helix 02 vs GPT-4.1 Mini

At a Glance

Compare
Helix 02Figure
Pricing and Limits
Context windowMaximum documented tokensNot reported1,048K
Model facts checkedAug 29, 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

FieldHelix 02GPT-4.1 Mini
DeveloperFigureOpenAI
FamilyHelixGpt 4 1
ModelHelix 02GPT-4.1 Mini
Version02GPT-4.1 Mini
Lifecycleactiveactive
Released2026-01-05Unknown
Knowledge cutoffUnknown2024-06-01
Input modalitiesText, Image, Robot stateText, Image
Output modalitiesRobot actionText
Context windowUnknown1,048K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableNoYes
Self-hostableNoNo
Provider accessUnknownOpenai (Standard), Openrouter (Standard)
Capabilitiesdexterous-manipulation, long-horizon-control, tactile-control, whole-body-controlchat, generation, tools
Robotics model typeVision-language-action modelUnknown
Action representationFull-body joint targetsUnknown
Control architectureSemantic reasoning, visuomotor policy, and kHz whole-body controllerUnknown
Inference locationOn deviceUnknown
Native control rate (Hz)UnknownUnknown
Supported embodimentsFigure 03Unknown
Training dataFigure reports more than 1,000 hours of human motion data plus sim-to-real reinforcement learning for its whole-body controller.Unknown

Helix 02 Capabilities

dexterous-manipulationlong-horizon-controltactile-controlwhole-body-control
Model typeVision-language-action model
InferenceOn device
Action representationFull-body joint targets
Supported embodiments1
Canonical IDfigure/helix-02

GPT-4.1 Mini Capabilities

chatgenerationtools
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDopenai/gpt-4.1-mini

Primary Evidence

Sources and Freshness

Questions

Helix 02 vs GPT-4.1 Mini FAQs

Is Helix 02 or GPT-4.1 Mini better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Helix 02 and GPT-4.1 Mini, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Helix 02 or GPT-4.1 Mini?+

Only GPT-4.1 Mini has a directly sourced input price: $0.20 per million tokens. Only GPT-4.1 Mini has a directly sourced output price: $0.80 per million tokens.

Which has a larger context window, Helix 02 or GPT-4.1 Mini?+

Neither model has a larger sourced context window in this comparison. Helix 02 is — and GPT-4.1 Mini is 1,048K.

Which performs better in benchmarks, Helix 02 or GPT-4.1 Mini?+

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

Can Helix 02 or GPT-4.1 Mini be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. Helix 02 is not marked open weight; GPT-4.1 Mini is not marked open weight.

Can Helix 02 and GPT-4.1 Mini understand images?+

Helix 02 is documented with image input; GPT-4.1 Mini is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Helix 02 or GPT-4.1 Mini?+

Neither has a larger sourced maximum output. Helix 02 is — and GPT-4.1 Mini is 33K.

Do Helix 02 and GPT-4.1 Mini support reasoning and tool use?+

Helix 02: image input. GPT-4.1 Mini: tool calling and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Helix 02 or GPT-4.1 Mini?+

Helix 02 has 0 sourced provider routes; GPT-4.1 Mini has 2, so GPT-4.1 Mini has broader tracked availability.

Which offers better value, Helix 02 or GPT-4.1 Mini?+

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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