OpenVLA 7B vs GLM 5.3
At a Glance
| Compare |  OpenVLA 7BOpenVLA Research Team |  GLM 5.3Z.ai |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #16 of 4670.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 46.9–80.3 |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #34 of 44$0.248 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #26 of 3850.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 38.2–54.9 |
| Pricing and Limits | ||
| Context windowMaximum documented tokens | Not reported | 1,000K |
| Model facts checked | Aug 29, 2026View model evidence → | Aug 29, 2026View model evidence → |
Available Benchmarks
Side-by-Side Facts
| Field | OpenVLA 7B | GLM-5.3 |
|---|---|---|
| Developer | OpenVLA Research Team | Z.ai |
| Family | OpenVLA | Glm 5 3 |
| Model | OpenVLA 7B | GLM-5.3 |
| Version | 7B | GLM-5.3 |
| Lifecycle | active | active |
| Released | 2024-06-13 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Robot state | Text |
| Output modalities | Robot action | Text |
| Context window | Unknown | 1,000K |
| Total parameters | 7B | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | Yes | No |
| API available | No | Yes |
| Self-hostable | Yes | No |
| Provider access | Unknown | Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard) |
| Capabilities | cross-embodiment, fine-tuning, generalist-manipulation | agents, chat, reasoning, structured_outputs, tools |
| Robotics model type | Vision-language-action model | Unknown |
| Action representation | Tokenized actions decoded to continuous robot controls | Unknown |
| Control architecture | Fused SigLIP and DINOv2 visual encoder with Llama 2 7B backbone | Unknown |
| Inference location | Flexible | Unknown |
| Native control rate (Hz) | Unknown | Unknown |
| Supported embodiments | WidowX, Google Robot, Franka Panda | Unknown |
| Training data | 970,000 robot manipulation trajectories from Open X-Embodiment described by the authors. | Unknown |
OpenVLA 7B Capabilities
GLM 5.3 Capabilities
Related Comparisons
| A | Pair | B | Context |
|---|---|---|---|
OpenVLA 7BOpenVLA Research Team | vs | GLM-5.2Z.ai | cross-developer peers |
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Claude Fable 5.1Anthropic | vs | OpenVLA 7BOpenVLA Research Team | cross-developer peers |
 Gemini 3.1 ProGoogle DeepMind | vs | OpenVLA 7BOpenVLA Research Team | cross-developer peers |
 DeepSeek-V4.1-FlashDeepSeek | vs | OpenVLA 7BOpenVLA Research Team | cross-developer peers |
OpenVLA 7BOpenVLA Research Team | vs | Grok 4.6xAI | cross-developer peers |
OpenVLA 7BOpenVLA Research Team | vs |  Qwen3.8-MaxQwen | cross-developer peers |
 Kimi-K3Moonshot AI | vs | OpenVLA 7BOpenVLA Research Team | cross-developer peers |
 MiniMax-M3MiniMax | vs | OpenVLA 7BOpenVLA Research Team | cross-developer peers |
OpenVLA 7BOpenVLA Research Team | vs |  Hy4 previewTencent | cross-developer peers |
Seed 2.1 ProByteDance Seed | vs | OpenVLA 7BOpenVLA Research Team | cross-developer peers |
 Mistral Large 3Mistral AI | vs | OpenVLA 7BOpenVLA Research Team | cross-developer peers |
Primary Evidence
Sources and Freshness
Questions
OpenVLA 7B vs GLM 5.3 FAQs
Is OpenVLA 7B or GLM 5.3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both OpenVLA 7B and GLM 5.3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, OpenVLA 7B or GLM 5.3?+
Only GLM 5.3 has a directly sourced input price: $1.20 per million tokens. Only GLM 5.3 has a directly sourced output price: $4.00 per million tokens.
Which has a larger context window, OpenVLA 7B or GLM 5.3?+
Neither model has a larger sourced context window in this comparison. OpenVLA 7B is — and GLM 5.3 is 1,000K.
Which performs better in benchmarks, OpenVLA 7B or GLM 5.3?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can OpenVLA 7B or GLM 5.3 be self-hosted?+
OpenVLA 7B is the only model in this pair currently marked as self-hostable. OpenVLA 7B is open weight; GLM 5.3 is not marked open weight.
Can OpenVLA 7B and GLM 5.3 understand images?+
OpenVLA 7B is documented with image input; GLM 5.3 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, OpenVLA 7B or GLM 5.3?+
Neither has a larger sourced maximum output. OpenVLA 7B is — and GLM 5.3 is 131K.
Do OpenVLA 7B and GLM 5.3 support reasoning and tool use?+
OpenVLA 7B: image input. GLM 5.3: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, OpenVLA 7B or GLM 5.3?+
OpenVLA 7B has 0 sourced provider routes; GLM 5.3 has 4, so GLM 5.3 has broader tracked availability.
Which offers better value, OpenVLA 7B or GLM 5.3?+
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.