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DeepSeek V4.1 Flash vs GR00T N1.7 3B

At a Glance

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Intelligence, Cost, and Efficiency
CostLower is better · Published-token output estimate#5 of 44$0.022 per LiveBench caseUnrankedNot in the 44-model eligible cohort
Pricing and Limits
Context windowMaximum documented tokens1,049KNot reported
Model facts checkedSep 10, 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

FieldDeepSeek-V4.1-FlashGR00T N1.7 3B
DeveloperDeepSeekNVIDIA
FamilyDeepseek V4 1Isaac GR00T
ModelDeepSeek-V4.1-FlashGR00T N1.7 3B
VersionDeepSeek-V4.1-FlashN1.7
Lifecycleactiveactive
Released2026-09-102026-07-07
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image, Robot state
Output modalitiesTextRobot action
Context window1,049KUnknown
Total parameters763.2B3B
Active parametersUnknownUnknown
Licensemitapache-2.0
Open weightsYesYes
API availableYesNo
Self-hostableYesYes
Provider accessDeepSeek (Standard), Deepinfra (Standard), Together Ai (Standard)Unknown
Capabilitiesagents, chat, fim, generation, reasoning, responses, structured_outputs, tools, visioncross-embodiment, dexterous-manipulation, whole-body-control, fine-tuning
Architecture designCausal Encoder-Decoder (20 encoder + 20 decoder layers)Unknown
Backbone parameters552000000000 parametersUnknown
Active parameters during decode16000000000 parametersUnknown
Active parameters during prefill8000000000 parametersUnknown
Pre-training corpus45000000000000 tokensUnknown
Reasoning effort range1–100Unknown
Routed experts per MoE layer384 expertsUnknown
Routed experts per token6 expertsUnknown
Transformer layers40 layersUnknown
Robotics model typeUnknownVision-language-action model
Action representationUnknownPredictive chunks of relative joint motions
Control architectureUnknownVision-language backbone with action expert
Inference locationUnknownOn device
Native control rate (Hz)UnknownUnknown
Supported embodimentsUnknownUnitree G1, AgiBot Genie-1, Fourier GR-1, bimanual manipulation platforms
Training dataUnknownMixture of real teleoperation, synthetic robot data, and internet-scale video described by NVIDIA.

DeepSeek V4.1 Flash Capabilities

agentschatfimgenerationreasoningresponsesstructured outputstoolsvision
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDdeepseek-ai/DeepSeek-V4.1-Flash

GR00T N1.7 3B Capabilities

cross-embodimentdexterous-manipulationwhole-body-controlfine-tuning
Model typeVision-language-action model
InferenceOn device
Action representationPredictive chunks of relative joint motions
Supported embodiments4
Canonical IDnvidia/GR00T-N1.7-3B

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Primary Evidence

Sources and Freshness

deepseek-ai/DeepSeek-V4.1-Flash developer model repositoryDeepSeek · observed Sep 10, 2026NVIDIA Isaac GR00T N1.7 official repositoryNVIDIA · observed Aug 29, 2026

Questions

DeepSeek V4.1 Flash vs GR00T N1.7 3B FAQs

Is DeepSeek V4.1 Flash or GR00T N1.7 3B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V4.1 Flash and GR00T N1.7 3B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, DeepSeek V4.1 Flash or GR00T N1.7 3B?+

Only DeepSeek V4.1 Flash has a directly sourced input price: $0.15 per million tokens. Only DeepSeek V4.1 Flash has a directly sourced output price: $0.60 per million tokens.

Which has a larger context window, DeepSeek V4.1 Flash or GR00T N1.7 3B?+

Neither model has a larger sourced context window in this comparison. DeepSeek V4.1 Flash is 1,049K and GR00T N1.7 3B is —.

Which performs better in benchmarks, DeepSeek V4.1 Flash or GR00T N1.7 3B?+

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

Can DeepSeek V4.1 Flash or GR00T N1.7 3B be self-hosted?+

Both models have the same recorded self-hosting status: supported. DeepSeek V4.1 Flash is open weight; GR00T N1.7 3B is open weight.

Can DeepSeek V4.1 Flash and GR00T N1.7 3B understand images?+

DeepSeek V4.1 Flash is documented with image input; GR00T N1.7 3B is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, DeepSeek V4.1 Flash or GR00T N1.7 3B?+

Neither has a larger sourced maximum output. DeepSeek V4.1 Flash is 393K and GR00T N1.7 3B is —.

Do DeepSeek V4.1 Flash and GR00T N1.7 3B support reasoning and tool use?+

DeepSeek V4.1 Flash: reasoning, tool calling, and image input. GR00T N1.7 3B: image input. Feature support does not establish relative quality.

Which is available from more inference providers, DeepSeek V4.1 Flash or GR00T N1.7 3B?+

DeepSeek V4.1 Flash has 3 sourced provider routes; GR00T N1.7 3B has 0, so DeepSeek V4.1 Flash has broader tracked availability.

Which offers better value, DeepSeek V4.1 Flash or GR00T N1.7 3B?+

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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