A100 vs H100 GPU Rack Comparison: Power and Cooling Requirements for AI Data Centers

AI data center rack populated with NVIDIA H100 GPUs has very high power and cooling demands

A typical AI data center rack populated with NVIDIA H100 GPUs has very high power and cooling demands due to the density and performance of these accelerators. Below is a detailed breakdown:

---

Power and Cooling Requirements for an H100 Rack

1. Power Consumption per H100 GPU

| Specification | Value |

| --------------------------------• | -------------------------------• |

| Power draw (per H100 SXM module) | \~700 W (typical, sustained) |

| Power draw (per H100 PCIe module) | \~350–400 W |

---

2. Typical Rack Configuration

A standard high-density AI rack may contain:

8 to 10 H100 SXM GPUs per server

3 to 4 servers per rack

Total GPUs per rack: 24 to 40

Total rack power draw: \~20 to 30 kW, depending on configuration

For SXM form factor (more common in AI training setups), power density is higher.

| Component | Count | Power Total |

| -------------------------• | ---------------------------------• | -------------• |

| H100 GPUs | 32 (e.g., 4x HGX servers × 8 GPUs) | 22.4 kW |

| CPUs, NVSwitch, SSDs, etc. | N/A | 2.5–5 kW |

| Total Rack Power | — | \~25–30 kW |

---

3. Cooling Requirements

To remove 30 kW of heat:

1 kW = 3,412 BTU/hr

Therefore:

30 kW × 3,412 = 102,360 BTU/hr

Thus, typical cooling demand is \~100,000 to 120,000 BTU/hr per rack.

Cooling Methods Used:

| Method | Notes |

| ----------------------------------• | --------------------------------------------------------------------------• |

| Liquid Cooling (Direct-to-Chip) | Required for SXM-based H100s due to high thermal density |

| Rear Door Heat Exchangers | Supplement cooling in high-density environments |

| Immersion Cooling | Used in ultra-dense AI clusters or for efficiency in large-scale deployment |

---

Summary Table

| Metric | Value |

| ------------------------------• | ------------------------------• |

| Power (kW) per rack | 25–30 kW |

| Cooling (BTU/hr) per rack | \~100,000 to 120,000 BTU/hr |

| Cooling (tons of refrigeration) | \~8.3 to 10 tons |

| Preferred cooling method | Liquid cooling |

A100 vs H100 Data Center Rack Power and Cooling Requirements

A100 vs H100 Data Center Rack Power and Cooling Requirements

| Parameter | A100 Rack (SXM) | H100 Rack (SXM) |

| -------------------------------------• | ---------------------------------------• | -------------------------------------• |

| GPU Power (per unit) | \~400 W (A100 SXM) | \~700 W (H100 SXM) |

| GPUs per server | 8 | 8 |

| Servers per rack | 3–4 | 3–4 |

| Total GPUs per rack | 24–32 | 24–32 |

| GPU Power Total (rack) | 9.6–12.8 kW | 16.8–22.4 kW |

| Additional System Power (CPU, etc) | 2–4 kW | 2.5–5 kW |

| Total Rack Power Consumption | 12–16 kW | 22–30 kW |

| Cooling Requirement (BTU/hr) | 40,944–54,592 BTU/hr | 75,064–102,360 BTU/hr |

| Cooling (Tons of Refrigeration) | \~3.4–4.6 tons | \~6.3–8.5 tons |

| Cooling Method | Air or liquid (large clusters) | Liquid or immersion required |

| Typical Rack Density (U) | 42U standard, may require custom airflow | 42U with high-flow or liquid manifolds |

---

Key Observations

H100 racks require nearly double the power and cooling compared to A100 racks due to higher TDP (thermal design power).

H100 SXM modules are typically not air-cooled—direct-to-chip liquid cooling is the standard.

A100 can still be found in air-cooled PCIe variants, allowing for slightly more flexible deployments.

As AI model sizes and compute intensity grow, data centers upgrading from A100 to H100 will need major cooling infrastructure upgrades, including:

Higher-rated power feeds per rack (30–40 kW)

Chilled water loop integration

Liquid-to-air or liquid-to-liquid cooling manifolds

A100 vs H100 GPU Rack Comparison: Power and Cooling Requirements for AI Data Centers

A100 vs H100 GPU Rack Comparison: Power and Cooling Requirements for AI Data Centers

---

Meta Description

Compare the power and cooling requirements of NVIDIA A100 and H100 GPU racks for AI data centers. Understand how each affects infrastructure planning and thermal management.

---

Teaser

Upgrading to NVIDIA H100 GPUs? Learn how their power and cooling demands compare to A100-based racks and what it means for your data center design.

---

Article: Comparing A100 and H100 GPU Rack Requirements for AI Infrastructure

Overview

As AI workloads grow more complex, data centers are rapidly shifting from NVIDIA A100 GPUs to the more powerful H100 architecture. However, this performance leap brings a significant increase in power consumption and cooling requirements per rack. This article provides a side-by-side comparison of A100 and H100 GPU-based racks to help guide infrastructure decisions.

---

Power Requirements per Rack

The A100 SXM GPU typically draws around 400 watts per unit, while the H100 SXM GPU can draw up to 700 watts. When configured in standard high-density AI training racks, the total rack power demand increases dramatically when moving from A100 to H100.

| Parameter | A100 Rack | H100 Rack |

| -----------------------• | --------------• | --------------• |

| GPUs per rack | 24 to 32 | 24 to 32 |

| Rack power (GPU only) | 9.6 to 12.8 kW | 16.8 to 22.4 kW |

| Additional system power | 2 to 4 kW | 2.5 to 5 kW |

| Total power per rack | 12 to 16 kW | 22 to 30 kW |

This nearly doubles the electrical demand for H100 racks compared to A100.

---

Cooling Requirements

Higher power consumption translates directly into increased heat output, which must be removed to maintain system reliability.

1 kW = 3,412 BTU/hr

Therefore:

A100 racks require \~40,000 to 55,000 BTU/hr

H100 racks require \~75,000 to 102,000 BTU/hr

| Metric | A100 Rack | H100 Rack |

| --------------• | ---------------• | ----------------• |

| BTU/hr | 40,944 to 54,592 | 75,064 to 102,360 |

| Tons of cooling | 3.4 to 4.6 tons | 6.3 to 8.5 tons |

---

Cooling Strategies

| Feature | A100 Rack | H100 Rack |

| -------------• | ------------• | ---------------------------• |

| Cooling method | Air or liquid | Liquid or immersion required |

| Rack density | 42U standard | 42U standard |

| Thermal risk | Moderate | High without liquid cooling |

Due to the heat density of H100 racks, data centers must adopt direct-to-chip liquid cooling or immersion cooling systems to prevent thermal throttling and ensure uptime.

---

Infrastructure Implications

For operators planning a migration from A100 to H100, this shift involves:

Upgrading electrical feeds per rack (up to 40 kW per rack)

Redesigning cooling systems, including hot aisle containment or chilled water loops

Adjusting rack spacing and airflow design

Failure to accommodate these needs may result in thermal failure, reduced GPU performance, or infrastructure overload.

---

Conclusion

NVIDIA H100 racks offer massive performance gains for AI workloads, but they double the energy and cooling requirements compared to A100 racks. Data centers must plan for these elevated demands by investing in next-generation cooling and power delivery systems. Accurate assessment and proactive infrastructure scaling are essential to future-proof AI facilities.

A100 vs H100 Data Center Rack Power and Cooling Requirements

A100 vs H100 Data Center Rack Power and Cooling Requirements

| Parameter | A100 Rack (SXM) | H100 Rack (SXM) |

| -------------------------------------• | ---------------------------------------• | -------------------------------------• |

| GPU Power (per unit) | \~400 W (A100 SXM) | \~700 W (H100 SXM) |

| GPUs per server | 8 | 8 |

| Servers per rack | 3–4 | 3–4 |

| Total GPUs per rack | 24–32 | 24–32 |

| GPU Power Total (rack) | 9.6–12.8 kW | 16.8–22.4 kW |

| Additional System Power (CPU, etc) | 2–4 kW | 2.5–5 kW |

| Total Rack Power Consumption | 12–16 kW | 22–30 kW |

| Cooling Requirement (BTU/hr) | 40,944–54,592 BTU/hr | 75,064–102,360 BTU/hr |

| Cooling (Tons of Refrigeration) | \~3.4–4.6 tons | \~6.3–8.5 tons |

| Cooling Method | Air or liquid (large clusters) | Liquid or immersion required |

| Typical Rack Density (U) | 42U standard, may require custom airflow | 42U with high-flow or liquid manifolds |

---

Key Observations

H100 racks require nearly double the power and cooling compared to A100 racks due to higher TDP (thermal design power).

H100 SXM modules are typically not air-cooled—direct-to-chip liquid cooling is the standard.

A100 can still be found in air-cooled PCIe variants, allowing for slightly more flexible deployments.

As AI model sizes and compute intensity grow, data centers upgrading from A100 to H100 will need major cooling infrastructure upgrades, including:

Higher-rated power feeds per rack (30–40 kW)

Chilled water loop integration

Liquid-to-air or liquid-to-liquid cooling manifolds

A100 vs H100 GPU Rack Comparison: Power and Cooling Requirements for AI Data Centers

A100 vs H100 GPU Rack Comparison: Power and Cooling Requirements for AI Data Centers

---

Meta Description

Compare the power and cooling requirements of NVIDIA A100 and H100 GPU racks for AI data centers. Understand how each affects infrastructure planning and thermal management.

---

Teaser

Upgrading to NVIDIA H100 GPUs? Learn how their power and cooling demands compare to A100-based racks and what it means for your data center design.

---

Article: Comparing A100 and H100 GPU Rack Requirements for AI Infrastructure

Overview

As AI workloads grow more complex, data centers are rapidly shifting from NVIDIA A100 GPUs to the more powerful H100 architecture. However, this performance leap brings a significant increase in power consumption and cooling requirements per rack. This article provides a side-by-side comparison of A100 and H100 GPU-based racks to help guide infrastructure decisions.

---

Power Requirements per Rack

The A100 SXM GPU typically draws around 400 watts per unit, while the H100 SXM GPU can draw up to 700 watts. When configured in standard high-density AI training racks, the total rack power demand increases dramatically when moving from A100 to H100.

| Parameter | A100 Rack | H100 Rack |

| -----------------------• | --------------• | --------------• |

| GPUs per rack | 24 to 32 | 24 to 32 |

| Rack power (GPU only) | 9.6 to 12.8 kW | 16.8 to 22.4 kW |

| Additional system power | 2 to 4 kW | 2.5 to 5 kW |

| Total power per rack | 12 to 16 kW | 22 to 30 kW |

This nearly doubles the electrical demand for H100 racks compared to A100.

---

Cooling Requirements

Higher power consumption translates directly into increased heat output, which must be removed to maintain system reliability.

1 kW = 3,412 BTU/hr

Therefore:

A100 racks require \~40,000 to 55,000 BTU/hr

H100 racks require \~75,000 to 102,000 BTU/hr

| Metric | A100 Rack | H100 Rack |

| --------------• | ---------------• | ----------------• |

| BTU/hr | 40,944 to 54,592 | 75,064 to 102,360 |

| Tons of cooling | 3.4 to 4.6 tons | 6.3 to 8.5 tons |

---

Cooling Strategies

| Feature | A100 Rack | H100 Rack |

| -------------• | ------------• | ---------------------------• |

| Cooling method | Air or liquid | Liquid or immersion required |

| Rack density | 42U standard | 42U standard |

| Thermal risk | Moderate | High without liquid cooling |

Due to the heat density of H100 racks, data centers must adopt direct-to-chip liquid cooling or immersion cooling systems to prevent thermal throttling and ensure uptime.

---

Infrastructure Implications

For operators planning a migration from A100 to H100, this shift involves:

Upgrading electrical feeds per rack (up to 40 kW per rack)

Redesigning cooling systems, including hot aisle containment or chilled water loops

Adjusting rack spacing and airflow design

Failure to accommodate these needs may result in thermal failure, reduced GPU performance, or infrastructure overload.

---

Conclusion

NVIDIA H100 racks offer massive performance gains for AI workloads, but they double the energy and cooling requirements compared to A100 racks. Data centers must plan for these elevated demands by investing in next-generation cooling and power delivery systems. Accurate assessment and proactive infrastructure scaling are essential to future-proof AI facilities.

A100 vs H100 GPU Rack Comparison: Power and Cooling Requirements for AI Data Centers

---

Meta Description

Compare the power and cooling requirements of NVIDIA A100 and H100 GPU racks for AI data centers. Understand how each affects infrastructure planning and thermal management.

---

Teaser

Upgrading to NVIDIA H100 GPUs? Learn how their power and cooling demands compare to A100-based racks and what it means for your data center design.

---

Article: Comparing A100 and H100 GPU Rack Requirements for AI Infrastructure

Overview

As AI workloads grow more complex, data centers are rapidly shifting from NVIDIA A100 GPUs to the more powerful H100 architecture. However, this performance leap brings a significant increase in power consumption and cooling requirements per rack. This article provides a side-by-side comparison of A100 and H100 GPU-based racks to help guide infrastructure decisions.

---

Power Requirements per Rack

The A100 SXM GPU typically draws around 400 watts per unit, while the H100 SXM GPU can draw up to 700 watts. When configured in standard high-density AI training racks, the total rack power demand increases dramatically when moving from A100 to H100.

| Parameter | A100 Rack | H100 Rack |

| -----------------------• | --------------• | --------------• |

| GPUs per rack | 24 to 32 | 24 to 32 |

| Rack power (GPU only) | 9.6 to 12.8 kW | 16.8 to 22.4 kW |

| Additional system power | 2 to 4 kW | 2.5 to 5 kW |

| Total power per rack | 12 to 16 kW | 22 to 30 kW |

This nearly doubles the electrical demand for H100 racks compared to A100.

---

Cooling Requirements

Higher power consumption translates directly into increased heat output, which must be removed to maintain system reliability.

1 kW = 3,412 BTU/hr

Therefore:

A100 racks require \~40,000 to 55,000 BTU/hr

H100 racks require \~75,000 to 102,000 BTU/hr

| Metric | A100 Rack | H100 Rack |

| --------------• | ---------------• | ----------------• |

| BTU/hr | 40,944 to 54,592 | 75,064 to 102,360 |

| Tons of cooling | 3.4 to 4.6 tons | 6.3 to 8.5 tons |

---

Cooling Strategies

| Feature | A100 Rack | H100 Rack |

| -------------• | ------------• | ---------------------------• |

| Cooling method | Air or liquid | Liquid or immersion required |

| Rack density | 42U standard | 42U standard |

| Thermal risk | Moderate | High without liquid cooling |

Due to the heat density of H100 racks, data centers must adopt direct-to-chip liquid cooling or immersion cooling systems to prevent thermal throttling and ensure uptime.

---

Infrastructure Implications

For operators planning a migration from A100 to H100, this shift involves:

Upgrading electrical feeds per rack (up to 40 kW per rack)

Redesigning cooling systems, including hot aisle containment or chilled water loops

Adjusting rack spacing and airflow design

Failure to accommodate these needs may result in thermal failure, reduced GPU performance, or infrastructure overload.

---

Conclusion

NVIDIA H100 racks offer massive performance gains for AI workloads, but they double the energy and cooling requirements compared to A100 racks. Data centers must plan for these elevated demands by investing in next-generation cooling and power delivery systems. Accurate assessment and proactive infrastructure scaling are essential to future-proof AI facilities.

Infinity Turbine Sales | Design | Develop | Analysis TEL: 1-608-238-6001 Email: greg@infinityturbine.com

For Data Centers Gas Turbine Waste Heat to Power Owners of Cat Solar Gas Turbine Generators and the new Boom Aero Derivative Gas Turbines Generators: Take your waste heat and make additional Combined Cycle power or generate cooling for your data center... More Info

IT250 Supercritical CO2 Gas Turbine Generator Silent Prime Power $999,000 250 kW (natural gas, solar thermal, thermal battery heat) ... More Info

IT1000 Supercritical CO2 Gas Turbine Generator Silent Prime Power $3M 1 MW (natural gas, solar thermal, thermal battery heat) ... More Info

IT50MW Supercritical CO2 Gas Turbine Generator Silent Prime Power $50M (natural gas, solar thermal, thermal battery heat) ... More Info

Data Center Consulting Prime power and energy consulting for AI and data centers... More Info

Quantum Super Turbine... Developing in 2026: High efficiency topping cycle turbine generator with bottoming cycle cooling, specifically designed for Data Centers with back-end combined cycle modules for cooling, hydraulic, or heat pump capabilities... More Info

ORC and Products Index Infinity Turbine ORC Index... More Info

CONTACT TEL: 1-608-238-6001 Email: greg@infinityturbine.com (Standard Web Page) | PDF