DeepSeek V4 Pro 0813 vs OpenVLA 7B

At a Glance

Compare
OpenVLA 7BOpenVLA Research Team
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5#20 of 4665.0 score · 3/3 sources · completeUnrankedNot in the 46-model eligible cohort
CostLower is better · Published-token output estimate#20 of 44$0.094 per LiveBench caseUnrankedNot in the 44-model eligible cohort
EfficiencyHigher is better · MM Efficiency v1.5#14 of 3857.4 score · 3/3 sources · completeUnrankedNot in the 38-model eligible cohort
Pricing and Limits
Context windowMaximum documented tokens1,049KNot reported
Model facts checkedSep 3, 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-Pro-0813OpenVLA 7B
DeveloperDeepSeekOpenVLA Research Team
FamilyDeepseek V4 ProOpenVLA
ModelDeepSeek-V4-Pro-0813OpenVLA 7B
VersionDeepSeek-V4-Pro-08137B
Lifecycleactiveactive
Released2026-08-132024-06-13
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image, Robot state
Output modalitiesTextRobot action
Context window1,049KUnknown
Total parameters1.6T7B
Active parameters49BUnknown
LicensemitUnknown
Open weightsYesYes
API availableYesNo
Self-hostableYesYes
Provider accessDeepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard)Unknown
Capabilitiesagents, chat, coding, generation, reasoning, 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.

DeepSeek V4 Pro 0813 Capabilities

agentschatcodinggenerationreasoningtools
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDdeepseek-ai/DeepSeek-V4-Pro-0813

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

Primary Evidence

Sources and Freshness

Questions

DeepSeek V4 Pro 0813 vs OpenVLA 7B FAQs

Is DeepSeek V4 Pro 0813 or OpenVLA 7B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V4 Pro 0813 and OpenVLA 7B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, DeepSeek V4 Pro 0813 or OpenVLA 7B?+

Only DeepSeek V4 Pro 0813 has a directly sourced input price: $1.30 per million tokens. Only DeepSeek V4 Pro 0813 has a directly sourced output price: $2.60 per million tokens.

Which has a larger context window, DeepSeek V4 Pro 0813 or OpenVLA 7B?+

Neither model has a larger sourced context window in this comparison. DeepSeek V4 Pro 0813 is 1,049K and OpenVLA 7B is —.

Which performs better in benchmarks, DeepSeek V4 Pro 0813 or OpenVLA 7B?+

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

Can DeepSeek V4 Pro 0813 or OpenVLA 7B be self-hosted?+

Both models have the same recorded self-hosting status: supported. DeepSeek V4 Pro 0813 is open weight; OpenVLA 7B is open weight.

Can DeepSeek V4 Pro 0813 and OpenVLA 7B understand images?+

DeepSeek V4 Pro 0813 is not documented with image input; OpenVLA 7B is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, DeepSeek V4 Pro 0813 or OpenVLA 7B?+

Neither has a larger sourced maximum output. DeepSeek V4 Pro 0813 is — and OpenVLA 7B is —.

Do DeepSeek V4 Pro 0813 and OpenVLA 7B support reasoning and tool use?+

DeepSeek V4 Pro 0813: reasoning and tool calling. OpenVLA 7B: image input. Feature support does not establish relative quality.

Which is available from more inference providers, DeepSeek V4 Pro 0813 or OpenVLA 7B?+

DeepSeek V4 Pro 0813 has 3 sourced provider routes; OpenVLA 7B has 0, so DeepSeek V4 Pro 0813 has broader tracked availability.

Which offers better value, DeepSeek V4 Pro 0813 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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