SmolVLA 450M vs Qwen3.8 Max

At a Glance

Compare
SmolVLA 450MHugging Face LeRobot
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5UnrankedNot in the 46-model eligible cohort#10 of 4679.2 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 52.8–86.1
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#23 of 44$0.107 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.5UnrankedNot in the 38-model eligible cohort#6 of 3863.2 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 50.0–66.7
Pricing and Limits
Context windowMaximum documented tokensNot reported1,000K
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

FieldSmolVLA 450MQwen3.8-Max
DeveloperHugging Face LeRobotQwen
FamilySmolVLAQwen3 8 Max
ModelSmolVLA 450MQwen3.8-Max
Version450MQwen3.8-Max
Lifecycleactiveactive
Released2025-06-03Unknown
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Robot stateText, Image, Video
Output modalitiesRobot actionText
Context windowUnknown1,000K
Total parameters450M2.4T
Active parametersUnknownUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableNoYes
Self-hostableYesNo
Provider accessUnknownAlibaba Cloud Model Studio (Standard), Deepinfra (Standard), Fireworks Ai (Standard), Openrouter (Standard)
Capabilitiesasynchronous-inference, fine-tuning, low-cost-hardware, manipulationagents, chat, reasoning, structured_outputs, tools, vision
Robotics model typeVision-language-action modelUnknown
Action representationContinuous action chunks from a flow-matching action expertUnknown
Control architectureSmolVLM2 backbone with flow-matching action expertUnknown
Inference locationOn deviceUnknown
Native control rate (Hz)UnknownUnknown
Supported embodimentsSO-100, SO-101, LeKiwi, LIBERO FrankaUnknown
Training dataCompatibly licensed LeRobot community datasets totaling fewer than 30,000 episodes in the cited release.Unknown

SmolVLA 450M Capabilities

asynchronous-inferencefine-tuninglow-cost-hardwaremanipulation
Model typeVision-language-action model
InferenceOn device
Action representationContinuous action chunks from a flow-matching action expert
Supported embodiments4
Canonical IDlerobot/smolvla_base

Qwen3.8 Max Capabilities

agentschatreasoningstructured outputstoolsvision
Model typeUnknown
InferenceUnknown
Action representationUnknown
Supported embodimentsUnknown
Canonical IDqwen/qwen3.8-max

Primary Evidence

Sources and Freshness

Questions

SmolVLA 450M vs Qwen3.8 Max FAQs

Is SmolVLA 450M or Qwen3.8 Max better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both SmolVLA 450M and Qwen3.8 Max, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, SmolVLA 450M or Qwen3.8 Max?+

Only Qwen3.8 Max has a directly sourced input price: $1.65 per million tokens. Only Qwen3.8 Max has a directly sourced output price: $4.951 per million tokens.

Which has a larger context window, SmolVLA 450M or Qwen3.8 Max?+

Neither model has a larger sourced context window in this comparison. SmolVLA 450M is — and Qwen3.8 Max is 1,000K.

Which performs better in benchmarks, SmolVLA 450M or Qwen3.8 Max?+

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

Can SmolVLA 450M or Qwen3.8 Max be self-hosted?+

SmolVLA 450M is the only model in this pair currently marked as self-hostable. SmolVLA 450M is open weight; Qwen3.8 Max is not marked open weight.

Can SmolVLA 450M and Qwen3.8 Max understand images?+

SmolVLA 450M is documented with image input; Qwen3.8 Max is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, SmolVLA 450M or Qwen3.8 Max?+

Neither has a larger sourced maximum output. SmolVLA 450M is — and Qwen3.8 Max is 131K.

Do SmolVLA 450M and Qwen3.8 Max support reasoning and tool use?+

SmolVLA 450M: image input. Qwen3.8 Max: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, SmolVLA 450M or Qwen3.8 Max?+

SmolVLA 450M has 0 sourced provider routes; Qwen3.8 Max has 4, so Qwen3.8 Max has broader tracked availability.

Which offers better value, SmolVLA 450M or Qwen3.8 Max?+

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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