Gemini 1.0 Ultra
Gemini 1.0 Ultra is worth evaluating for long context and vision when its provider route and context window match the workload.
Use it for
- Teams evaluating long context and vision
- Workloads that can use a 1m context window
- Buyers comparing 1 tracked provider route
Do not use it for
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- Gemini 1.0
- Released
- 2023-12-13
- Context
- 1m
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
Cheapest of 1 route · GCP Vertex AI
About
Google's Gemini 1.0 Ultra is a leading large language model designed for tackling highly complex tasks with advanced analytical capabilities. As the largest model in the Gemini 1.0 family, it excels in coding, mathematical reasoning, and multimodal reasoning. Its strength lies in its ability to seamlessly understand and process diverse data types, including text, code, audio, images, and video. Gemini Ultra surpasses human experts on the MMLU benchmark with a 90% score, although it has limitations in image generation and some multimodal tasks. The model features a 32,000-token context window, less than some competitors, and access is primarily through a paid subscription or via Google Cloud for developers.
Gemini 1.0 Ultra is a model in the Gemini 1.0 family. The structured metadata tracks a 1m-token context window. This page tracks provider routes through GCP Vertex AI, with the cheapest tracked route listed at $1 input and $3 output per 1M tokens. Headline tracked benchmarks include Massive Multi-discipline Multimodal Understanding 59.4.
Top use-case fit
Long context
Included by capability and metadata signals in the decision map.
Vision
Q/$ C1 relevant benchmark in the decision map.
Provider price ladder
Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| GCP Vertex AI | $1.00 | $3.00 | Serverless |
Capabilities
No model capability flags are currently sourced.
Benchmark peer barsfor Vision
Benchmark scores(1)
| Benchmark | Score | Version | Source |
|---|---|---|---|
| Massive Multi-discipline Multimodal Understanding | 59.4 | — | https://mmmu-benchmark.github.io/ |
Migration checks
No linked migration route is available for this model yet.