Credits are our main unit of measurement for using the TESS platform – more complex or time-consuming tasks will require more credits. TESS is the first and only platform that keeps full transparency on pricing, openly showing all the cost details.
1 credit is worth $0.00297
TESS default markup per usage = 20%
This means that when you use an agent and spend 1,000 credits (which is $2.97), the real average breakdown of costs looks like this:
$2.38 goes directly to the original model providers for API usage;
$0.59 goes to TESS for accessing the models with all the benefits our platform offers
Credit consumption mainly depends on three factors:
LLM token usage: Used for strategic planning, decision making, and content generation.
Virtual machine operations: Used in cloud environments that let you manage files, automate browser tasks, and run code.
External API integrations: Used when we access third-party services we’ve integrated, including sources for financial info and specialized professional databases.
The exact amount of credits for each task depends on how complex it is and how long it takes to finish.
Credits are only deducted while the task is being processed — once it’s done, both storage and access to results don’t use any more credits. So you don’t have to delete completed tasks from your account.
When tasks fail due to technical issues caused by our infrastructure, we give back all the credits used in that process. Our commitment is to keep making the system run better and better to slowly reduce credit usage per task.
Credits are used in this order: event credits, daily credits, monthly credits, extra credits, and free credits.
Monthly credits come from your subscription and renew automatically on the same day every month, based on your subscription date.
Free credits and extra credits never expire.
Event credits can be earned by joining events and expire when the event ends.
Here are some cases and how much they might use per generation:
Initial Prompt
I’d like to create a gluten-free natural cookies ecommerce with at least 3
sweet options, 3 savory ones, and different pages for the user to browse from
Home, About Us, Products Page and Contact. The site needs to be responsive
for mobile and use the brand colors purple, light gray and blue.
Access here the final site
Initial Prompt
I want to make a PPT to explain Tess AI's API to users who don't have much API experience. Create a PPT with about 10-15 slides, using a clean and easy-to-understand visual style (e.g., light colors, intuitive icons). The PPT should cover the following topics, using the content from the website https://docs.tess.im/api/get-started/overview#available-endpoints and the JSON with the API collection:
1. What is an API (in a simple way)? (1 slide) - Explain the concept of an API using real-world analogies, avoiding technical jargon.
2. What is Tess AI's API and what is it for? (1 slide) - Describe the main features of Tess AI's API and its benefits for the user.
3. How do you access Tess AI's API? (1-2 slides) - Explain the basic steps to start using the API, including getting access keys (if needed) and the general structure of the requests.
4. Examples of using Tess AI's API (3-6 slides) - Show practical, simple examples of how to use the API for specific tasks, like [mention specific examples from the website if possible, like getting information or doing actions]. Include request and response examples (simplified).
5. Where to find more info? (1 slide) - Provide the link to the complete API documentation (https://docs.tess.im/api/get-started/overview#available-endpoints) and other support sources.
The goal is to make an intro and accessible material for users who don't know anything about APIs yet.
Used Settings
Template: Quiet Space
Mode: AI generation
AI: MiniMax Image 01
Download here the final PPT
Initial Prompt
I'd like to create a presentation about the cryptocurrency market in 2025 and projections for 2026. The presentation should include:
1. A detailed analysis of the current state of the cryptocurrency market (trends, main players, emerging technologies).
2. Forecasts for the market in 2025, considering factors like regulation, institutional adoption, and tech advancements.
3. Projections for 2026, based on the trends identified in 2025.
4. Charts and tables to illustrate the data and projections.
5. Identification of opportunities and risks for investors in the crypto market in 2025 and 2026.
6. A short executive summary with the main conclusions and recommendations.
The desired format for the presentation is pptx and the target audience is beginner investors with technical knowledge
Settings Used
Template: Future Vision
Mode: Mixed strategy
AI: Seedream 4
Download here the final PPT
Initial Prompt
Deep research the background of NVIDIA's CEO, Jensen Huang, focusing on his education, early career, and key milestones leading to his role as CEO. Based on this research, develop a comprehensive interview outline designed to explore his leadership philosophy, strategic vision for NVIDIA, and perspectives on the future of AI and computing.
Final Answer
Here is a comprehensive research summary and interview outline for Jensen Huang, CEO of NVIDIA, focusing on his background and designed to explore his leadership philosophy, strategic vision, and perspectives on AI and computing.
---
## Jensen Huang: Background Research
### Education
- Bachelor of Science in Electrical Engineering (BSEE) from Oregon State University (1984).
- Master of Science in Electrical Engineering (MSEE) from Stanford University (1992).
- Sources: NVIDIA Board Bio, Stanford Engineering Heroes, Oregon State University.
### Early Career
- Began as a microprocessor designer at Advanced Micro Devices (AMD).
- Later joined LSI Logic, where he held several engineering and leadership roles, including director of CoreWare.
- Sources: NVIDIA Bio, Wikipedia.
### Key Milestones Leading to CEO Role
- Co-founded NVIDIA in 1993 with Chris Malachowsky and Curtis Priem.
- Became President and CEO from day one and has held the position since.
- Led NVIDIA through major industry shifts: from graphics cards for gaming to high-performance computing, AI, and data centers.
- Pioneered CUDA (2006), enabling GPUs for general-purpose computing and AI.
- Oversaw NVIDIA’s expansion into AI, autonomous vehicles, and enterprise solutions.
- Sources: [NVIDIA Corporate Timeline](https://www.nvidia.com/en-us/about-nvidia/corporate-timeline/), [NVIDIA Blog](https://blogs.nvidia.com/blog/nvidia-dennys-trillion/), [Wikipedia](https://en.wikipedia.org/wiki/Jensen_Huang).
---
## Interview Outline: Jensen Huang
### Section A: Early Life and Education
- How did your experiences at Oregon State and Stanford shape your approach to engineering and leadership?
- Were there any formative moments or mentors during your education that influenced your career trajectory?
### Section B: Early Career and Founding of NVIDIA
- What lessons did you take from your time at AMD and LSI Logic that informed your vision for NVIDIA?
- Can you share the story of NVIDIA’s founding and the initial vision you had for the company?
- What were the biggest challenges in the early days, and how did you overcome them?
### Section C: Leadership Philosophy
- How would you describe your leadership style, and how has it evolved over the years?
- You’ve spoken about the importance of “productive struggle” and learning from pain. How do you foster resilience and innovation within your teams?
- With a flat organizational structure and many direct reports, how do you maintain agility and communication at scale?
### Section D: Strategic Vision for NVIDIA
- What is your framework for deciding when to invest in new technologies or platforms (e.g., CUDA, AI, RTX)?
- How do you balance NVIDIA’s core strengths with the need to expand into new markets like AI, data centers, and autonomous vehicles?
- What are the key factors that have enabled NVIDIA to repeatedly redefine its addressable market?
### Section E: Perspectives on the Future of AI and Computing
- As AI training and deployment scale, what technical bottlenecks do you see as most critical, and how is NVIDIA addressing them?
- How do you envision the concept of “AI factories” transforming enterprise IT and national compute strategies in the next 3–5 years?
- What breakthroughs are needed to bring real-time, multimodal AI inference to the edge (PCs, vehicles, robotics)?
- How should the industry balance rapid AI advancement with safety and robustness?
### Section F: Talent, Culture, and Execution
- What qualities do you look for in leaders and team members at NVIDIA?
- How do you measure and sustain innovation throughput across hardware, systems, and software during periods of hypergrowth?
- How do you ensure NVIDIA’s culture remains strong as the company scales globally?
### Section G: Personal Reflections and Legacy
- Looking back, which decision are you most proud of that was non-consensus at the time?
- How do your philanthropic efforts in engineering education reflect your vision for the next generation of innovators?
- What legacy do you hope to leave at NVIDIA and in the broader technology industry?
### Optional Lightning Round
- One principle you’d change in the tech industry if you could.
- A belief you held at NVIDIA’s founding that you no longer hold.
- The most underestimated trend in accelerated computing today.
---
### Supporting Materials
- For detailed references, screenshots, and supporting documents, see:
- Stanford Engineering Heroes Screenshot
- More supporting files and screenshots
If you need the full research notes or want to explore any section in more detail, let me know!
