DeepSeek R1 vs SmolVLA 450M
At a Glance
| Compare |  DeepSeek R1DeepSeek |  SmolVLA 450MHugging Face LeRobot |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 164K | Not reported |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 29, 2026View model evidence → |
Available Benchmarks
Side-by-Side Facts
| Field | DeepSeek-R1 | SmolVLA 450M |
|---|---|---|
| Developer | DeepSeek | Hugging Face LeRobot |
| Family | Deepseek R1 | SmolVLA |
| Model | DeepSeek-R1 | SmolVLA 450M |
| Version | DeepSeek-R1 | 450M |
| Lifecycle | active | active |
| Released | 2025-01-20 | 2025-06-03 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image, Robot state |
| Output modalities | Text | Robot action |
| Context window | 164K | Unknown |
| Total parameters | 684.5B | 450M |
| Active parameters | 37B | Unknown |
| License | mit | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Yes | No |
| Self-hostable | Yes | Yes |
| Provider access | Hugging Face (Standard), Openrouter (Standard) | Unknown |
| Capabilities | chat, generation, reasoning | asynchronous-inference, fine-tuning, low-cost-hardware, manipulation |
| Robotics model type | Unknown | Vision-language-action model |
| Action representation | Unknown | Continuous action chunks from a flow-matching action expert |
| Control architecture | Unknown | SmolVLM2 backbone with flow-matching action expert |
| Inference location | Unknown | On device |
| Native control rate (Hz) | Unknown | Unknown |
| Supported embodiments | Unknown | SO-100, SO-101, LeKiwi, LIBERO Franka |
| Training data | Unknown | Compatibly licensed LeRobot community datasets totaling fewer than 30,000 episodes in the cited release. |
DeepSeek R1 Capabilities
SmolVLA 450M Capabilities
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Primary Evidence
Sources and Freshness
Questions
DeepSeek R1 vs SmolVLA 450M FAQs
Is DeepSeek R1 or SmolVLA 450M better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek R1 and SmolVLA 450M, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, DeepSeek R1 or SmolVLA 450M?+
Only DeepSeek R1 has a directly sourced input price: $0.70 per million tokens. Only DeepSeek R1 has a directly sourced output price: $2.50 per million tokens.
Which has a larger context window, DeepSeek R1 or SmolVLA 450M?+
Neither model has a larger sourced context window in this comparison. DeepSeek R1 is 164K and SmolVLA 450M is —.
Which performs better in benchmarks, DeepSeek R1 or SmolVLA 450M?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can DeepSeek R1 or SmolVLA 450M be self-hosted?+
Both models have the same recorded self-hosting status: supported. DeepSeek R1 is open weight; SmolVLA 450M is open weight.
Can DeepSeek R1 and SmolVLA 450M understand images?+
DeepSeek R1 is not documented with image input; SmolVLA 450M is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, DeepSeek R1 or SmolVLA 450M?+
Neither has a larger sourced maximum output. DeepSeek R1 is 33K and SmolVLA 450M is —.
Do DeepSeek R1 and SmolVLA 450M support reasoning and tool use?+
DeepSeek R1: reasoning. SmolVLA 450M: image input. Feature support does not establish relative quality.
Which is available from more inference providers, DeepSeek R1 or SmolVLA 450M?+
DeepSeek R1 has 2 sourced provider routes; SmolVLA 450M has 0, so DeepSeek R1 has broader tracked availability.
Which offers better value, DeepSeek R1 or SmolVLA 450M?+
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.