SpaceX Starship v3 and DeepMind Gemini Ultra serve fundamentally different purposes. Starship v3 is designed for space travel and cargo delivery, emphasizing reusability and high payload capacity. Gemini Ultra is an AI model focused on advanced reasoning and multimodal input processing, aimed at business applications and integration with Google products. The choice depends entirely on the specific application: space exploration or AI-driven solutions.
| Attribute | SpaceX Starship v3 | DeepMind Gemini Ultra |
|---|---|---|
| Name | SpaceX Starship v3 | DeepMind Gemini Ultra |
| Development Stage | The Starship v3 design has been completed, and SpaceX is actively working on research and production. Prototypes are under construction, with potential test flights as early as 2026. | Gemini Ultra 2 is the latest iteration. Gemini Ultra 2.1 planned for Q4 2025. |
| Target Payload Capacity (Metric Tons) | Starship v3 aims for a reusable payload capacity of at least 200 tons to low Earth orbit (LEO). It may also carry 400 tons in an expendable configuration. | Not available |
| Propulsion System Type | Starship v3 will be powered by Raptor 3 engines, burning liquid methane and liquid oxygen. The Super Heavy booster is expected to have 35 Raptor 3 engines, while the Starship upper stage will have nine. | Not available |
| Reusability (Stages) | Both stages (Super Heavy booster and Starship) are designed to be fully reusable, returning to the launch site for vertical landing. | Not available |
| Primary Mission Objective | Starship is intended to carry both crew and cargo to Earth orbit, the Moon, Mars, and beyond. Specific objectives include deploying large satellites, constructing a Moon base, and enabling interplanetary travel. | Supports a wide range of business applications, from enhancing productivity tools to powering complex decision-making processes. |
| AI Model Architecture | Not applicable to SpaceX Starship v3. | Gemini 2.5 uses a Sparse Mixture-of-Experts (MoE) architecture. |
| Training Data Volume and Diversity | Not applicable to SpaceX Starship v3. | Gemini 1.0 was trained to recognize and understand text, images, audio, and more simultaneously. |
| Multimodal Input Capabilities | Not applicable to SpaceX Starship v3. | Supports processing text, code, audio, and image inputs. Gemini 2.X series supports long context inputs of >1 million tokens and have native tool use support. |
| Reasoning and Problem-Solving Performance | Not applicable to SpaceX Starship v3. | Exceeds current state-of-the-art results on 30 of the 32 widely-used academic benchmarks. Gemini Ultra 2 reportedly outperforms GPT-5 in advanced reasoning tasks. |
| Energy Efficiency (Training and Inference) | Not applicable to SpaceX Starship v3. | Trained on Google's TPUs and will be supported by the new TPU v5p. Trained on Google's latest TPUv5 chips for speed and cost-effectiveness. |
| Accessibility and API Availability | Not applicable to SpaceX Starship v3. | Gemini Pro is accessible through the Gemini API in Google AI Studio or Google Cloud Vertex AI. Gemini Ultra 2 is being natively integrated across Google products. |
| Ethical Considerations and Safety Measures | Not applicable to SpaceX Starship v3. | Extensive trust and safety checks, including red-teaming by trusted external parties. Google DeepMind also brings a unique safety perspective due to its background in reinforcement learning and agents. |
| Price | Not available | Not available |
| Ratings | Not available | Overall performance exceeds current state-of-the-art results on 30 of the 32 widely-used academic benchmarks. Gemini Ultra is the first model to outperform human experts on MMLU with a score of 90.0%. |