Gemini 2.5 Flash
google/gemini-2.5-flashThe high-volume multimodal default, 1M context and vision input at workhorse prices.
Model overview
Context window
1M
tokens
Input price
—
quoted on request
Output price
—
quoted on request
Weekly volume
—
tokens / week
Open weights
No
API only
Capabilities
5
of 11 tags
Description
Gemini 2.5 Flash is a language model from Google. Webparam does not stock this model yet and can source it on request — tell us what you need it for and we will come back with availability and a price. Google’s stated focus is frontier multimodality at planetary scale. The weights are not published, so it is API-only.
Capabilities
- Tool calling
- Calls functions you define and returns their arguments as structured data, the basis of agents.
- JSON mode
- Constrains the response to valid JSON matching a schema you supply.
- Streaming
- Emits tokens as they are generated, so answers appear progressively rather than all at once.
- Vision input
- Accepts images alongside text in the prompt.
- Long context
- Built for inputs well beyond the mainstream window, whole repositories, archives or corpora.
Strengths & weaknesses
Strengths
- 1M context at volume prices
- Fast
- Vision included
Weaknesses
- Depth trails Pro on hard tasks
- Audio input reserved for Pro
Pricing
| Rate | Price | Unit |
|---|---|---|
| Input | — quoted on request | — |
| Output | — quoted on request | — |
This model is not provisioned yet; the rate is quoted on request.
Context window
1Mtokens
covers prompt and response together, so a long input leaves less room for the answer.
Supported features
| Feature | Support |
|---|---|
| Tool calling | Supported |
| JSON mode | Supported |
| Streaming | Supported |
| Vision input | Supported |
| Audio input | Not supported |
| Long context | Supported |
| Open weights | Not supported |
| Reasoning | Not supported |
| Fine-tunable | Not supported |
| Batch | Not supported |
| Caching | Not supported |
Example use cases
Production default
Long-document volume work
Multimodal features
Related models
Comparison
Compare against anything →| Attribute | Gemini 2.5 Flash | GPT-5.1 Mini | Gemini 3 Pro |
|---|---|---|---|
| Context window | 1M | 400K | 1M |
| Input price | R0.00 | R0.00 | R0.00 |
| Output price | — not charged | — not charged | — not charged |
| Tool calling | Supported | Supported | Supported |
| JSON mode | Supported | Supported | Supported |
| Vision input | Supported | Supported | Supported |
| Open weights | Not supported | Not supported | Not supported |
| Prompt caching | Not supported | Supported | Not supported |
Best value in each row is highlighted. Blank cells are facts the supplier does not publish, not zeroes.
Provider information
View Google →Google · Mountain View, United States · est. 1998 (DeepMind model era from 2023)
Google DeepMind's Gemini line is natively multimodal (text, vision and audio in one system) backed by custom TPU infrastructure nobody else can match. Veo and Imagen lead generative media, and Gemini's long-context engineering set the 1M-token standard the industry chased.
Recent releases
Documentation
Frequently asked questions
Input is billed at R0.00 per 1M tokens, and there is no separate output charge. Every figure on this page is an illustrative placeholder.
No. Gemini 2.5 Flash is served through its provider's API only; the weights are not published, so self-hosting is not an option.
Prompt and response share one window: Gemini 2.5 Flash accepts up to 1M tokens in total, so a long input leaves less room for the answer. The median across language models is 256K. It carries the long-context tag, meaning it is built for inputs well beyond the mainstream window.
GPT-5.1 Mini is the closest neighbour in the catalogue, with 400K of context at R0.00 per 1M tokens in. Put both in a comparison before wiring a fallback chain, so the trade-off is a decision rather than a default.