gemini-3-flash-previewGoogle
- endpoints
- 4
- regions
- 1
- best tok/s
- 290
- api
- chat
- released
- December 2025
capabilities 6/8
The same weights cost 2.0x more on google llc (gemini api) than on google llc (gemini api). That is what the endpoints table is for.
| # | flags | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 1 |  Google LLC (Gemini API) | Global | 1.0M | $0.25 | $1.50 | $0.05 | 6.73s | 290.0 | zdr | |
| 2 |  Google LLC (Vertex AI) | Global | 1.0M | $0.25 | $1.50 | $0.02 | 4.78s | 132.0 | - | zdr |
| 3 | Google LLC (Gemini API) | Global | 1.0M | $0.50 | $3.00 | $0.05 | 6.73s | 290.0 | zdr | |
| 4 | Google LLC (Vertex AI) | Global | 1.0M | $0.50 | $3.00 | $0.05 | 4.78s | 132.0 | - | zdr |
| provider | now | low | high | change |
|---|---|---|---|---|
| Google LLC (Vertex AI) | 4.78s | 1.42s | 2.38s | +65% |
| Google LLC (Gemini API) | 6.73s | 1.11s | 7.28s | -81% |
median wait before the first token lands. this is the number a user feels, and it moves with provider load through the day.
Lines are steps: each sample is one week of traffic held flat, not a slide from the week before. Click a name in the key to drop it from the plot. Measured through Sep 12.
| eval | Score as a share of 100 | /100 |
|---|---|---|
| Math Index | 97.0 | |
| AIME 2025 | 97.0 | |
| LiveCodeBench | 90.8 | |
| GPQA Diamond | 89.8 | |
| MMLU Pro | 89.0 | |
| τ²-Bench | 80.4 | |
| Terminal-Bench Hard | 38.6 | |
| Humanity's Last Exam | 36.6 | |
| Intelligence Index | 26.3 | |
| 9 evals | mean | 71.7 |
Scores from Artificial Analysis and public leaderboards, normalised to 100. Bar colour is the band, not the rank: green 80 and up, blue 55 and up, amber 30 and up. Benchmarks measure narrow skills, so test on your own workload before committing. Released 2025-12-17.
google/gemini-3-flash-preview:flexthis model has no managed policy yet, so call the provider endpoint directly. every id in the endpoints table works the same way
Base url is https://router.requesty.ai/v1 for every id here. One key reaches the whole catalog.
from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create( model="google/gemini-3-flash-preview:flex", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ],) print(response.choices[0].message.content)
Change the base url, use your Requesty key, set the model to any id in the call pane. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog, so switching later is a one-parameter change. Browse all models
Gemini 3 Flash Preview is designed to deliver strong agentic capabilities (near-Pro level) at substantial speed and value. Making it perfect for engaging multi-turn chats, and collaborating back and forth with your coding agent without getting out of flow. Compared to 2.5 Flash it delivers significant improvements across the board.
questions 6
Which providers serve gemini-3-flash-preview?
How much does gemini-3-flash-preview cost?
Is gemini-3-flash-preview open weights?
What is the context window of gemini-3-flash-preview?
Which provider is fastest for gemini-3-flash-preview?
How do I use gemini-3-flash-preview with the OpenAI SDK?
more from google 6
| model | context | from /M | providers |
|---|---|---|---|
| gemini-3.8-flash | 1.0M | $0.75 | 1 |
| gemini-3.7-flash | 1.0M | $0.75 | 1 |
| gemini-3.6-flash | 1.0M | $0.38 | 2 |
| gemini-3.5-flash-lite | 1.0M | $0.15 | 2 |
| gemini-3.1-flash-image | 131K | $0.25 | 2 |
| gemini-3-pro-image | 1.0M | $1.00 | 2 |
route gemini-3-flash-preview through one endpoint
One key for 2 providers on this model and 600+ others. No markup on provider prices, automatic failover, caching built in. Weekly aggregates in the measured pane come from production traffic routed through Requesty, one line per provider on a shared axis. Methodology