Gemini 4 Argon
gemini-4-argon
Total Context
1M
Max Output
65.5K
Released
N/A
Input$4 / M tokens
Output$20 / M tokens
Gemini 2.5 Pro
gemini-2.5-proGemini 2.5 Pro is Google’s advanced Gemini 2.5 model for complex tasks, deep reasoning, and coding. Official Gemini 2.5 materials describe the generation as “thinking” before responding, with improved performance and accuracy on hard tasks. It remains a strong choice for users who need deliberate reasoning and multimodal understanding.
Context Window
1M tokens
Maximum Output
65.5K tokens
Release Date
Jun 17, 2025
Modalities
Gemini 2.5 Pro Pricing
| Input Price | Output Price | Cache Read |
|---|---|---|
| $1.25/M | $10/M | $0.125/M |
Gemini 2.5 Pro API Capabilities
Reasoning
Supported
Tool calling
Supported
Temperature parameter
Supported
Attachments
Supported
Knowledge Base
2025-01-01
Endpoint Protocols
Completions APIMessages APIgemini
Gemini 2.5 Pro Model Highlights
Gemini 2.5 Pro combines deep reasoning, advanced coding and million-token multimodal context for complex technical and analytical tasks.
Deep Technical Reasoning
Reasons through difficult problems in mathematics, science and engineering before producing a final answer.
Advanced Code Reasoning
Analyzes large codebases, understands dependencies and develops solutions for complex implementation or debugging problems.
Million-Token Multimodality
Processes up to 1,048,576 input tokens across text, images, video, audio and PDFs in a single context.
Gemini 2.5 Pro Use Cases
Gemini 2.5 Pro is suited to complex coding, scientific problem solving and analysis of large multimodal datasets or document collections.
Complex Codebase Analysis
Trace architecture and dependencies across a large repository, diagnose defects and propose coordinated modifications.
Scientific Problem Solving
Work through multi-stage mathematics or STEM problems, explain assumptions and derive a reasoned result.
Large Multimodal Corpus Review
Review extensive documents, recordings, images and video, extract relevant evidence and synthesize findings.
How to Use Gemini 2.5 Pro via the TokenHub API
import OpenAI from "openai"
const client = new OpenAI({
apiKey: process.env.TOKENHUB_API_KEY,
baseURL: "https://us-api.tokenhub.com/v1",
})
const result = await client.chat.completions.create({})
console.log(result.choices[0]?.message?.content)Gemini 2.5 Pro Benchmarks
Gemini 2.5 Pro
| Index score | ||
|---|---|---|
| Artificial Analysis Intelligence Index | Artificial Analysis broad capability aggregate | 27 |
| Artificial Analysis Coding Index | Artificial Analysis software task aggregate | 32 |
| Artificial Analysis Math Index | Artificial Analysis math reasoning aggregate | 87.7 |
| Knowledge & Reasoning | ||
| MMLU-Pro | Advanced multi-task knowledge | 86.2% |
| GPQA | Advanced science problem solving | 84.4% |
| HLE | Broad expert-level exam set | 21.1% |
| Coding & Engineering | ||
| LiveCodeBench | Live coding problems | 80.1% |
| SciCode | Scientific coding challenges | 42.8% |
| Terminal-Bench Hard | Hard terminal task execution | 26.5% |
| Math | ||
| MATH-500 | Advanced math problem solving | 96.7% |
| AIME | Competition math problems | 88.7% |
| AIME 2025 | Competition math problems | 87.7% |
| Instruction Following & Agent Tasks | ||
| IFBench | Prompt constraint adherence | 48.7% |
| AA-LCR | Long-context reasoning | 66% |
| τ²-Bench | Agent workflow tasks | 54.1% |
Metrics sourced from Artificial Analysis
Gemini 2.5 Pro Guides & Articles
Frequently asked questions about Gemini 2.5 Pro
Understand what Gemini 2.5 Pro is, its best uses, distinguishing strengths, practical tradeoffs, and safe TokenHub integration guidance.
What is Gemini 2.5 Pro, and where does it fit in Google’s model lineup?+
Gemini 2.5 Pro is Google’s established Gemini 2.5 Pro reasoning model for code, STEM, large datasets, and long documents. It remains a defined model generation, but newer models in the same family may be preferable for new evaluations.
Which workloads are the best fit for Gemini 2.5 Pro?+
Best-fit scenarios include complex multi-step reasoning, mathematics, science, and engineering problems, and analysis of long documents and datasets. Test representative inputs and define measurable acceptance criteria before production.
Why might a team select Gemini 2.5 Pro over a smaller or older model?+
Key strengths include strong reasoning on difficult problems, strong handling of long context, and support for varied multimodal inputs. This combination is especially useful for mathematics, science, and engineering problems.
What should be validated before relying on Gemini 2.5 Pro?+
Consider another model when the project can adopt a newer Gemini generation, very low latency is the main requirement, or the workflow cannot include human review for important decisions. Verify important factual, legal, financial, medical, or operational outputs with qualified human review.
What is the practical TokenHub setup guidance for Gemini 2.5 Pro?+
In TokenHub, select the exact model identifier displayed for Gemini 2.5 Pro, use the endpoint documented for your account, and authenticate with your TokenHub credentials. Confirm the TokenHub-exposed input types, tools, grounding options, and model lifecycle rather than assuming full Gemini API parity.
Ready to use Gemini 2.5 Pro?
Use one API key to access Gemini 2.5 Pro and more AI models through TokenHub.
Media and Discussions
Selected public videos and posts related to this model.
X (Twitter)
Google AI ·
Here’s what launched this week: — Gemini 3.5 Live Translate our latest audio model for live speech-to-speech translation — @NotebookLM got a major upgrade including agentic capabilities in chat, more advanced reasoning, and a suite of new output formats — Project Genie from
View originalGoogle AI ·
Tune in for the full story ↓ https://www.youtube.com/watch?v=8hfpLa5wPGo
View originalGoogle AI ·
Here’s this week’s shipping recap 👇 — Nano Banana 2 & Nano Banana Pro are now GA and available via the Gemini Enterprise Agent Platform, Gemini API, and in @GoogleAIStudio —Co-Scientist, our new multi-agent system for structured scientific thinking, generates and refines novel
View originalReddit
Recent updates to deep research offerings and the best deep research prompts?
Beginning-Willow-801 ·
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Deep research is one of my favorite parts of ChatGPT and Gemini. I am curious what prompts people are having the best success with specifically for epic deep research outputs? I created over 100 deep research reports with AI this week. With Deep Research it searches hundreds of websites on a custom topic from one prompt and it delivers a rich, structured report — complete with charts, tables, and citations. Some of my reports are 20–40 pages long (10,000–20,000+ words!). I often follow up by asking for an executive summary or slide deck. I often benchmark the same report between ChatGTP or Gemini to see which creates the better report. I am interested in differences betwee deep research prompts across platforms. I have been able to create some pretty good prompts for - Ultimate guides on topics like MCP protocol and vibe coding - Create a masterclass on any given topic taught in the tone of the best possible public figure - Competitive intelligence is one of the best use cases I have found 5 Major Deep Research Updates ChatGPT now lets you export Deep Research reports as PDFs This should’ve been there from the start — but it’s a game changer. Tables, charts, and formatting come through beautifully. No more copy/paste hell. Open AI issued an update a few weeks ago on how many reports you can get for free, plus and pro levels: April 24, 2025 update: We’re significantly increasing how often you can use deep research—Plus, Team, Enterprise, and Edu users now get 25 queries per month, Pro users get 250, and Free users get 5. This is made possible through a new lightweight version of deep research powered by a version of o4-mini, designed to be more cost-efficient while preserving high quality. Once you reach your limit for the full version, your queries will automatically switch to the lightweight version. 2. ChatGPT can now connect to your GitHub repo If you’re vibe coding, this is pretty awesome. You can ask for documentation, debugging, or code understanding — integrated directly into your workflow. 3. I believe Gemini 2.5 Pro now rivals ChatGPT for Deep Research (and considers 10X more websites) Google's massive context window makes it ideal for long, complex topics. Plus, you can export results to Google Docs instantly. Gemini documentation says on the paid $20 a month plan you can run 20 reports per day! I have noticed that Gemini scans a lot more web sites for deep research reports - benchmarking the same deep research prompt Gemini get to 10 TIMES as many sites in some cases (often looks at hundreds of sites). 3. Claude has entered the Deep Research arena Anthropic’s Claude gives unique insights from different sources for paid users. It’s not as comprehensive in every case as ChatGPT, but offers a refreshing perspective. 4. Perplexity and Grok are fast, smart, but shorter Great for 3–5 page summaries. Grok is especially fast. But for detailed or niche topics, I still lean on ChatGPT or Gemini. One final thing I have noticed, the context windows are larger for plus users in ChatGPT than free users. And Pro context windows are even larger. So Seep Research reports are more comprehensive the more you pay. I have tested this and have gotten more comprehensive reports on Pro than on Plus. ChatGPT has different context window sizes depending on the subscription tier. Free users have a 8,000 token limit, while Plus and Team users have a 32,000 token limit. Enterprise users have the largest context window at 128,000 tokens Longer reports are not always better but I have seen a notable difference. The HUGE context window in Gemini gives their deep research reports an advantage. Again, I would love to hear what deep research prompts and topics others are having success with.
2.5 pro become useless for writing- document analysis (gemini advanced user here)
Humble-Me-15 ·
Earlier the 2.5 pro was very good, was able to go through multiple attached documents, bring out data and did very good analysis and generate good content. Now it is completely useless, i got frustrated to use gemini 2.5 pro, free chatgpt is doing way better job. now thinking about canceling gemini advanced subscription and jump to chatgpt plus subscription. Need advice and suggestions.
View originalTrouble with using a custom mode for learning
derekdehart ·
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I was excited to see Cursor introduce custom modes (https://docs.cursor.com/chat/custom-modes), and the Learn mode example in the docs made me come back to Cursor after finding it a bit too eager to make code changes rather than help me work through a problem on my own. This seemed to work well for a while, but lately my custom Learn mode is ignoring my custom instructions and greedily making a bunch of changes for me, even when I’ve reminded it in the course of conversation that it shouldn’t behave that way. I’ve been using gemini-2.5-pro with these custom instructions in the custom Learn mode I created: I’ve given it access to all tools because I’m also using the mode to write task specifications and generate Cursor rules and was too lazy to switch to other modes to do so. Has anyone found success with a Learn mode that guides more than does?
YouTube
Google Gemini 2.5 Pro is Insane...
Matthew Berman
View originalGoogle Gemini 2.5 Pro — Everything You Need to Know
AI Plus
View originalGoogles NEW Gemini 2.5 Pro BEATS Everything! (Gemini 2.5 Pro)
TheAIGRID
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