Google: Gemini 2.5 Pro Preview 06-05
google/gemini-2.5-pro-preview
Access Gemini 2.5 Pro Preview 06-05 from Google using Puter.js AI API.
Get Started// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "google/gemini-2.5-pro-preview"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "google/gemini-2.5-pro-preview"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://api.puter.com/puterai/openai/v1/",
api_key="YOUR_PUTER_AUTH_TOKEN",
)
response = client.chat.completions.create(
model="google/gemini-2.5-pro-preview",
messages=[
{"role": "user", "content": "Explain quantum computing in simple terms"}
],
)
print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
-d '{
"model": "google/gemini-2.5-pro-preview",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Gemini 2.5 Pro Preview is the preview version of Google's most advanced reasoning model with state-of-the-art coding and complex task performance. It features Deep Think mode, 1M token context, and advanced multimodal capabilities.
Context Window 1M
tokens
Max Output 66K
tokens
Input Cost $1.25
per million tokens
Output Cost $10
per million tokens
Release Date Jun 5, 2025
Output Speed 127
tokens / sec
Latency 19.60s
time to first token
Model Playground
Try Gemini 2.5 Pro Preview 06-05 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How Gemini 2.5 Pro Preview 06-05 performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 84.4% |
| Humanity's Last Exam Cross-domain reasoning | 21.1% |
| LiveCodeBench Recent coding problems | 80.1% |
| SciCode Scientific programming | 42.8% |
| MATH-500 Competition math | 96.7% |
| AIME 2024 Advanced math exam | 88.7% |
| AIME 2025 Advanced math exam | 87.7% |
| IFBench Instruction following | 48.7% |
| LCR Long-context reasoning | 66.0% |
| Terminal-Bench Hard Agentic terminal tasks | 26.5% |
| τ²-Bench Tool use / agents | 54.1% |
Scores sourced from Artificial Analysis.
Find other Google models →
Gemini 3.5 Flash
Gemini 3.5 Flash is Google DeepMind's frontier-speed model that combines Flash-tier latency and cost with near-Pro-level reasoning, announced at Google I/O 2026. It processes output 4x faster than comparable frontier models while outperforming Gemini 3.1 Pro on coding and agentic benchmarks — 76.2% on Terminal-Bench 2.1, 83.6% on MCP Atlas, and 84.2% on CharXiv Reasoning. It's purpose-built for agentic workflows: orchestrating multi-step tool use, long-context document analysis, and iterative code generation. With a 1M token context window and full multimodal input support (text, image, audio, video, PDF), it handles complex real-world tasks at scale. At $1.50 per million input tokens and $9.00 per million output tokens, it's the best choice for developers who need frontier intelligence without frontier latency or cost.
ChatGemma 4 26B A4B
Gemma 4 26B A4B is a Mixture-of-Experts (MoE) open model from Google DeepMind, built from the same research as Gemini 3. It has 26B total parameters but activates only 3.8B per forward pass, delivering near-31B-dense quality at a fraction of the compute cost. The model supports a 256K token context window, multimodal image and text input, built-in step-by-step reasoning (thinking mode), and native function calling for agentic workflows. It currently ranks #6 among open models on the Arena AI text leaderboard with an estimated LMArena score of 1441 — competitive with models many times its active size. It excels at reasoning, coding, long-context tasks, and structured tool use. It's a strong pick for developers who need high throughput and low latency without sacrificing capability.
ChatGemma 4 31B
Gemma 4 31B is a dense multimodal model from Google DeepMind, built on the same research foundation as Gemini 3. It is the most capable model in the Gemma 4 family, accepting text, image, and video input with a 256K-token context window. It delivers strong benchmark results: 89.2% on AIME 2026, 85.2% on MMLU Pro, 80.0% on LiveCodeBench v6, and 84.3% on GPQA Diamond. On the Arena AI text leaderboard, it ranks as the #3 open model globally, outperforming many models with far higher parameter counts. Gemma 4 31B features native function calling trained into the model, configurable chain-of-thought reasoning, and structured JSON output — making it especially well-suited for agentic workflows, coding tasks, and multi-turn tool use. It supports over 140 languages and serves as a strong foundation for fine-tuning.
Frequently Asked Questions
You can access Gemini 2.5 Pro Preview 06-05 by Google through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Gemini 2.5 Pro Preview 06-05 to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $1.25 |
| Output | $10 |
Gemini 2.5 Pro Preview 06-05 was created by Google and released on Jun 5, 2025.
Gemini 2.5 Pro Preview 06-05 supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,097 pages of text.
Gemini 2.5 Pro Preview 06-05 can generate up to 66K tokens in a single response.
Gemini 2.5 Pro Preview 06-05 scores 34.6 on the Artificial Analysis Intelligence Index, outperforming 76% of tracked models. On coding, it scores 32.0 (outperforms 73% of models). On math, it scores 87.7 (outperforms 85% of models).
Yes — the Gemini 2.5 Pro Preview 06-05 API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Get started with Puter.js
Add Gemini 2.5 Pro Preview 06-05 to your app without worrying about API keys or setup.
Read the Docs View Tutorials