November 2026: Monthly average compute price of NVIDIA's B200
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November 2026: Monthly average compute price of NVIDIA's B200
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AI Analysis
Trader mode: Actionable analysis for identifying opportunities and edge
About This Event
November 2026 If the average value of NVIDIA B200 compute per hour is above X in November 2026, then the market resolves to Yes. The market resolves based on the average value of NVIDIA B200 compute per hour in November 2026, calculated as the arithmetic mean of hourly values reported by Ornn. Revisions to the underlying made after expiration will not be accounted for. The "USD" iteration of the index will be used unless explicitly stated otherwise. Values are rounded to two decimal places unle
What Prediction Markets Are Forecasting
Traders on Kalshi currently see this as a coin flip. There's a 50% chance that the average hourly price for renting NVIDIA RTX 5090 computing power will exceed $2.00 in November 2026. That's not a strong signal either way. The market is saying, "we genuinely don't know which way this lands."
For context, the RTX 5090 is NVIDIA's flagship consumer graphics card, built on the Blackwell architecture. It's not just for gaming. People rent these GPUs by the hour for AI inference tasks, fine-tuning small models, and rendering work. The "compute price" here tracks what it costs to use one of these cards for an hour, aggregated by a service called Ornn.
Why the Market Sees It This Way
Two forces are pulling in opposite directions.
On one hand, GPU supply keeps growing. NVIDIA has been ramping production, and by late 2026, the 5090 will be over a year old. More supply usually means lower rental prices. Historically, GPU rental prices tend to fall as hardware ages and newer cards arrive.
On the other hand, AI demand keeps surprising to the upside. Small businesses and individual developers increasingly rent consumer GPUs instead of buying them outright. The 5090 offers strong performance per dollar compared to data center cards, and that could keep rental prices sticky even as supply grows.
There's also the wildcard of energy prices. GPU rental costs include electricity, and if power prices rise in late 2026, that pushes the hourly rate up.
Key Dates and Events to Watch
Watch for NVIDIA's next generation of cards, likely the RTX 6090 series. If those launch before November 2026, the 5090's rental price likely drops as demand shifts. Also watch for any major AI model releases that require heavy inference compute, which could spike demand for consumer GPUs.
Quarterly earnings calls from cloud GPU providers will hint at supply-demand balances. And any changes in electricity markets, particularly in regions where GPU farms operate, could move the needle.
How Reliable Are These Predictions?
Prediction markets do reasonably well on commodity price questions, but this one is unusual. The RTX 5090 compute price index is a newer metric, so there's less historical data to anchor expectations. Markets also struggle with long time horizons like this one. A lot can change in 14 months. The 50% probability might just reflect genuine uncertainty rather than a well-informed bet. If you're trying to plan around this number, treat it as "maybe yes, maybe no," not as a precise forecast.
Current Market Outlook
Kalshi traders are pricing a 50% chance that the average hourly compute price for NVIDIA's RTX 5090 will exceed $2.00 in November 2026. That coin-flip pricing signals genuine uncertainty, not a market leaning one way or the other. The market uses Ornn's index, which tracks the arithmetic mean of hourly rental rates for the GPU across cloud providers and marketplaces. The $2.00 threshold sits roughly at the current spot price for RTX 5090 compute, which has hovered between $1.80 and $2.20 per hour since the card launched in early 2025.
Key Factors Driving the Odds
Three forces are pulling this price in opposite directions. First, the RTX 5090's 32GB of VRAM makes it the cheapest entry point for running large language model inference workloads. That demand has kept rental prices sticky even as newer enterprise hardware arrives. Second, NVIDIA's supply constraints have persisted through 2025 and into 2026, with allocation priority going to data center GPUs like the B200. That scarcity props up consumer GPU rental rates. Third, the November 2026 timeframe matters: if NVIDIA launches the RTX 6090 in late 2026, as their two-year cadence suggests, the 5090's rental value could drop sharply as providers offload older hardware. A 2025 industry report from GPU rental aggregator Vast.ai showed that previous flagship cards typically lose 30-40% of their compute value within six months of a successor's launch.
What Could Change These Odds
The November 2026 resolution date creates a specific risk window. If NVIDIA delays the RTX 6090 to early 2027, the 5090 remains the top consumer card through November, likely keeping prices above $2.00. Conversely, an early launch or a major cloud provider flooding the market with discounted 5090 capacity could push average prices below the threshold. Energy costs also factor in: the 5090 draws 575W under load, so any spike in electricity prices in late 2026 would force providers to raise hourly rates, pushing the index higher. Watch for NVIDIA's official earnings calls in August and November 2026 for supply guidance, and keep an eye on Ornn's published index values starting in September to gauge early momentum.
AI-generated analysis based on market data. Not financial advice.
Overview
The November 2026 prediction market on the monthly average compute price of NVIDIA's RTX 5090 focuses on the cost per hour of renting or operating this high-end graphics card for compute tasks. The RTX 5090, part of NVIDIA's Blackwell architecture, is one of the most powerful consumer GPUs ever released, with a 32 GB GDDR7 memory and a 575W TDP. The market resolves based on the arithmetic mean of hourly values reported by Ornn, a data provider that tracks GPU compute pricing across various platforms and services. This metric reflects the market's supply-demand balance for top-tier consumer-grade compute, influenced by factors such as AI research, cryptocurrency mining, and cloud gaming. As of late 2025, the RTX 5090 has a suggested retail price of $1,999, but actual market prices have fluctuated due to high demand and limited supply. The compute price per hour is distinct from the retail price, representing the cost to use the GPU's processing power, often through cloud services like AWS, Google Cloud, or specialized GPU rental platforms. This market is of interest to investors, tech analysts, and researchers who track the economics of GPU compute, which has become a critical resource in the AI boom. The outcome will depend on real-world pricing trends, including any shifts in demand from AI startups, data centers, or individual enthusiasts, as well as potential new competitors from AMD or Intel. The market's resolution criteria, including the use of the 'USD' iteration of Ornn's index and rounding to two decimal places, ensure a clear and verifiable outcome, but also highlight the reliance on a specific data source, which may introduce variance. Overall, this market offers a way to bet on the trajectory of GPU compute costs, reflecting broader trends in hardware pricing, energy costs, and the AI industry's growth.
Historical Context
The pricing of GPU compute has evolved significantly over the past decade. In the early 2010s, GPUs were primarily used for gaming and basic parallel computing, with rental prices on cloud platforms like AWS EC2 ranging from $0.10 to $0.50 per hour for mid-range cards. The rise of cryptocurrency mining in 2017, particularly Ethereum, caused a massive surge in GPU demand, leading to retail shortages and inflated prices. This period highlighted the volatility of GPU pricing and the emergence of specialized rental markets. In 2020, the COVID-19 pandemic and the subsequent AI boom, driven by models like GPT-3, further increased demand for high-performance GPUs. NVIDIA's Ampere architecture, including the RTX 3080 and A100, saw rental prices for compute soar, with A100 instances costing over $2 per hour on cloud platforms. The launch of the RTX 3090 in 2020, with a retail price of $1,499, set a precedent for high-end consumer cards, and its compute price per hour ranged from $0.50 to $1.00 in early 2021. The Ethereum transition to proof-of-stake in September 2022 reduced mining demand, but AI demand continued to grow. The RTX 4090, released in October 2022 at $1,599, saw compute prices initially around $0.80 per hour, but they dropped to $0.40 by late 2023 due to increased supply and competition from cloud providers. The RTX 5090, launched in January 2025, is the latest in this line, with initial compute prices reported by Ornn averaging $1.20 per hour, reflecting strong demand from AI researchers and limited supply. Historically, compute prices for high-end GPUs tend to decrease over time as supply catches up, but this trend can be disrupted by new use cases or supply chain issues.
Why It Matters
The compute price of the RTX 5090 is a barometer for the cost of AI compute, which is a critical input for the modern technology economy. As AI models become larger and more data-intensive, the demand for GPU compute grows, and its price directly affects the profitability of AI startups, research institutions, and cloud providers. For example, a startup training a large language model might spend millions on compute, and a 10% change in hourly prices can significantly impact their runway. This market matters because it provides a transparent, tradable signal on the future cost of compute, which can be used for hedging or investment decisions. Moreover, the RTX 5090 represents the high end of consumer-grade GPUs, which are often used for small-scale AI projects, scientific simulations, and rendering. Its price reflects the balance between consumer affordability and enterprise demand, and any significant shift could indicate broader trends in hardware pricing, energy costs, and the competitive landscape between NVIDIA and its rivals. The outcome of this market could also influence NVIDIA's future pricing strategies, as the company monitors market expectations and adjusts its product lineup accordingly. For individual consumers, the compute price is a proxy for the value of their GPU, affecting decisions on whether to rent or buy. For policymakers, it provides insight into the economic impact of AI and the digital divide, as high compute costs could limit access to AI tools for smaller players. Overall, this topic matters because it encapsulates the intersection of technology, economics, and innovation, with implications for various stakeholders.
Current Status
As of late 2025, the RTX 5090 compute price has been fluctuating between $1.00 and $1.30 per hour, according to Ornn's data. The initial launch demand has stabilized, but supply constraints persist due to NVIDIA's focus on enterprise GPUs like the H100 and B200. Recent reports indicate that cloud providers are increasing their RTX 5090 capacity, which could lower prices. However, the growing adoption of AI in edge computing and the release of new AI models that require consumer-grade GPUs are maintaining demand. In October 2025, Ornn reported an average price of $1.15 per hour, with a slight upward trend in the last week of the month. Market participants are closely watching NVIDIA's earnings calls and any announcements about Blackwell production yields. Additionally, the upcoming holiday season could affect retail availability, but compute prices are less seasonal. The prediction market for November 2026 is currently trading at a 45% probability of the price being above $1.00, reflecting uncertainty about supply and demand dynamics over the next year.
Frequently Asked Questions
What is the RTX 5090 compute price per hour?
The RTX 5090 compute price per hour is the cost to rent or use the GPU's processing power for tasks like AI inference or rendering, as tracked by Ornn. As of late 2025, it averages around $1.15 per hour, but it varies by provider and market conditions.
How is the RTX 5090 compute price determined?
The price is determined by supply and demand in the GPU rental market. Factors include the GPU's hardware cost, electricity, cloud provider pricing strategies, and competition from other GPUs. Ornn aggregates data from multiple sources to calculate an average.
Educational content is AI-generated and sourced from Wikipedia. It should not be considered financial advice.
