Gemini 1.0 Models by Google DeepMind
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Google's Gemini 1.0 is a family of large language models (LLMs) that excels in capability and versatility 126. The Gemini family comprises three distinct models tailored to different tasks and hardware requirements: Gemini Ultra, aimed at tackling highly complex tasks; Gemini Pro, a flexible all-round model; and Gemini Nano, optimized for efficiency and on-device usage 16. These models are multimodal, capable of processing diverse data types such as text, code, audio, images, and video 1411. Known for achieving state-of-the-art performance, Gemini 1.0 models have been rigorously tested, at times surpassing human expert performance 14. Focused on safety and responsibility, these models undergo comprehensive safety evaluations before deployment 1.
Current Variants
Use-when guidance is derived from seed capabilities, context, release, and replacement fields.
Use when the workload needs 12k context, structured outputs, and multimodal inputs.
Use when the workload needs 32k context and structured outputs.
Use when the workload needs 33k context, structured outputs, and multimodal inputs.
| Model | Use when | Released | Signals | Status |
|---|---|---|---|---|
| Gemini 1.0 Pro Vision | Use when the workload needs 12k context, structured outputs, and multimodal inputs. | 2024-04 | 12k contextstructured outputsmultimodal inputs | Current |
| Gemini 1.0 Ultra | Use when the workload needs 1m context. | 2023-12 | 1m context | Current |
| Gemini 1.0 Pro | Use when the workload needs 32k context and structured outputs. | 2023-12 | 32k contextstructured outputs | Current |
| Gemini 1.0 Nano | Use when the workload needs 32k context. | 2023-12 | 32k context | Current |
| Gemini 1.0 Pro on Google Vertex AI | Use when the workload needs 33k context, structured outputs, and multimodal inputs. | 2023-12 | 33k contextstructured outputsmultimodal inputs | Current |
Release Timeline
2 release groupsSpecifications(5 models)
| Model | Released | Context | Vision | Multimodal | Structured Outputs |
|---|---|---|---|---|---|
| Gemini 1.0 Pro Vision | 2024-04 | 12k | Yes | No | Yes |
| Gemini 1.0 Ultra | 2023-12 | 1m | No | No | No |
| Gemini 1.0 Pro | 2023-12 | 32k | No | No | Yes |
| Gemini 1.0 Nano | 2023-12 | 32k | No | No | No |
| Gemini 1.0 Pro on Google Vertex AI | 2023-12 | 33k | Yes | Yes | Yes |
Available From(1 provider)
Pricing
| Model | Provider | Input / 1M | Output / 1M | Type |
|---|---|---|---|---|
| Gemini 1.0 Pro on Google Vertex AI | GCP Vertex AI | $0.125 | $0.375 | Serverless |
| Gemini 1.0 Pro | GCP Vertex AI | $0.5 | $1.5 | Serverless |
| Gemini 1.0 Pro Vision | GCP Vertex AI | $0.5 | $1.5 | Serverless |
| Gemini 1.0 Ultra | GCP Vertex AI | $1 | $3 | Serverless |
Frequently Asked Questions
- What is Gemini 1.0 used for?
- Gemini 1.0 is used for vision and multimodal work, structured outputs, and coding. The family description and listed model capabilities point to those workloads as the best fit.
- How does Gemini 1.0 compare to Gemma 4?
- Gemini 1.0 by Google DeepMind is strongest where you need vision and multimodal work, while Gemma 4 by Google DeepMind is the closest related family to check for multimodal. Gemini 1.0 has 5 listed variants and reaches up to 1m context, while Gemma 4 reaches up to 256k context, so compare the specs and pricing tables before choosing a production model.
- Which Gemini 1.0 model should I use?
- For the lowest listed input price, start with Gemini 1.0 Pro on Google Vertex AI through GCP Vertex AI at $0.125/1M input tokens. For the most capable/latest local choice, evaluate Gemini 1.0 Pro on Google Vertex AI with 33k context and structured outputs and multimodal inputs.
