GEFORCE

NVIDIA Tesla M10

NVIDIA graphics card specifications and benchmark scores

8 GB
VRAM
1306
MHz Boost
225W
TDP
128
Bus Width

NVIDIA Tesla M10 Specifications

⚙️

Tesla M10 GPU Core

Shader units and compute resources

The NVIDIA Tesla M10 GPU core specifications define its raw processing power for graphics and compute workloads. Shading units (also called CUDA cores, stream processors, or execution units depending on manufacturer) handle the parallel calculations required for rendering. TMUs (Texture Mapping Units) process texture data, while ROPs (Render Output Units) handle final pixel output. Higher shader counts generally translate to better GPU benchmark performance, especially in demanding games and 3D applications.

Shading Units
640
Shaders
640
TMUs
40
ROPs
16
⏱️

Tesla M10 Clock Speeds

GPU and memory frequencies

Clock speeds directly impact the Tesla M10's performance in GPU benchmarks and real-world gaming. The base clock represents the minimum guaranteed frequency, while the boost clock indicates peak performance under optimal thermal conditions. Memory clock speed affects texture loading and frame buffer operations. The Tesla M10 by NVIDIA dynamically adjusts frequencies based on workload, temperature, and power limits to maximize performance while maintaining stability.

Base Clock
1033 MHz
Base Clock
1,033 MHz
Boost Clock
1306 MHz
Boost Clock
1,306 MHz
Memory Clock
1300 MHz 5.2 Gbps effective
GDDR GDDR 6X 6X

NVIDIA's Tesla M10 Memory

VRAM capacity and bandwidth

VRAM (Video RAM) is dedicated memory for storing textures, frame buffers, and shader data. The Tesla M10's memory capacity determines how well it handles high-resolution textures and multiple displays. Memory bandwidth, measured in GB/s, affects how quickly data moves between the GPU and VRAM. Higher bandwidth improves performance in memory-intensive scenarios like 4K gaming. The memory bus width and type (GDDR6, GDDR6X, HBM) significantly influence overall GPU benchmark scores.

Memory Size
8 GB
VRAM
8,192 MB
Memory Type
GDDR5
VRAM Type
GDDR5
Memory Bus
128 bit
Bus Width
128-bit
Bandwidth
83.20 GB/s
💾

Tesla M10 by NVIDIA Cache

On-chip cache hierarchy

On-chip cache provides ultra-fast data access for the Tesla M10, reducing the need to fetch data from slower VRAM. L1 and L2 caches store frequently accessed data close to the compute units. AMD's Infinity Cache (L3) dramatically increases effective bandwidth, improving GPU benchmark performance without requiring wider memory buses. Larger cache sizes help maintain high frame rates in memory-bound scenarios and reduce power consumption by minimizing VRAM accesses.

L1 Cache
64 KB (per SMM)
L2 Cache
2 MB
📈

Tesla M10 Theoretical Performance

Compute and fill rates

Theoretical performance metrics provide a baseline for comparing the NVIDIA Tesla M10 against other graphics cards. FP32 (single-precision) performance, measured in TFLOPS, indicates compute capability for gaming and general GPU workloads. FP64 (double-precision) matters for scientific computing. Pixel and texture fill rates determine how quickly the GPU can render complex scenes. While real-world GPU benchmark results depend on many factors, these specifications help predict relative performance levels.

FP32 (Float)
1.672 TFLOPS
FP64 (Double)
52.24 GFLOPS (1:32)
Pixel Rate
20.90 GPixel/s
Texture Rate
52.24 GTexel/s
🏗️

Maxwell Architecture & Process

Manufacturing and design details

The NVIDIA Tesla M10 is built on NVIDIA's Maxwell architecture, which defines how the GPU processes graphics and compute workloads. The manufacturing process node affects power efficiency, thermal characteristics, and maximum clock speeds. Smaller process nodes pack more transistors into the same die area, enabling higher performance per watt. Understanding the architecture helps predict how the Tesla M10 will perform in GPU benchmarks compared to previous generations.

Architecture
Maxwell
GPU Name
GM107
Process Node
28 nm
Foundry
TSMC
Transistors
1,870 million
Die Size
148 mm²
Density
12.6M / mm²
🔌

NVIDIA's Tesla M10 Power & Thermal

TDP and power requirements

Power specifications for the NVIDIA Tesla M10 determine PSU requirements and thermal management needs. TDP (Thermal Design Power) indicates the heat output under typical loads, guiding cooler selection. Power connector requirements ensure adequate power delivery for stable operation during demanding GPU benchmarks. The suggested PSU wattage accounts for the entire system, not just the graphics card. Efficient power delivery enables the Tesla M10 to maintain boost clocks without throttling.

TDP
225 W
TDP
225W
Power Connectors
1x 8-pin
Suggested PSU
550 W
📐

Tesla M10 by NVIDIA Physical & Connectivity

Dimensions and outputs

Physical dimensions of the NVIDIA Tesla M10 are critical for case compatibility. Card length, height, and slot width determine whether it fits in your chassis. The PCIe interface version affects bandwidth for communication with the CPU. Display outputs define monitor connectivity options, with modern cards supporting multiple high-resolution displays simultaneously. Verify these specifications against your case and motherboard before purchasing to ensure a proper fit.

Slot Width
Dual-slot
Length
267 mm 10.5 inches
Bus Interface
PCIe 3.0 x16
Display Outputs
No outputs
Display Outputs
No outputs
🎮

NVIDIA API Support

Graphics and compute APIs

API support determines which games and applications can fully utilize the NVIDIA Tesla M10. DirectX 12 Ultimate enables advanced features like ray tracing and variable rate shading. Vulkan provides cross-platform graphics capabilities with low-level hardware access. OpenGL remains important for professional applications and older games. CUDA (NVIDIA) and OpenCL enable GPU compute for video editing, 3D rendering, and scientific applications. Higher API versions unlock newer graphical features in GPU benchmarks and games.

DirectX
12 (11_0)
DirectX
12 (11_0)
OpenGL
4.6
OpenGL
4.6
Vulkan
1.4
Vulkan
1.4
OpenCL
3.0
CUDA
5.0
Shader Model
6.7 (5.1)
📦

Tesla M10 Product Information

Release and pricing details

The NVIDIA Tesla M10 is manufactured by NVIDIA as part of their graphics card lineup. Release date and launch pricing provide context for comparing GPU benchmark results with competing products from the same era. Understanding the product lifecycle helps evaluate whether the Tesla M10 by NVIDIA represents good value at current market prices. Predecessor and successor information aids in tracking generational improvements and planning future upgrades.

Manufacturer
NVIDIA
Release Date
May 2016
Production
End-of-life
Predecessor
Tesla Kepler
Successor
Tesla Pascal

Tesla M10 Benchmark Scores

geekbench_openclSource

Geekbench OpenCL tests GPU compute performance using the cross-platform OpenCL API. This shows how NVIDIA Tesla M10 handles parallel computing tasks like video encoding and scientific simulations. OpenCL is widely supported across different GPU vendors and platforms. Higher scores benefit applications that leverage GPU acceleration for non-graphics workloads.

geekbench_opencl #348 of 582
10,318
3%
Max: 380,114
Compare with other GPUs

🏆 Top 5 Performers

geekbench_vulkanSource

Geekbench Vulkan tests GPU compute using the modern low-overhead Vulkan API. This shows how NVIDIA Tesla M10 performs with next-generation graphics and compute workloads.

geekbench_vulkan #305 of 386
8,950
2%
Max: 379,571

About NVIDIA Tesla M10

The NVIDIA's NVIDIA Tesla M10 delivers a solid 8 GB of GDDR5 memory, making it a reliable choice for virtual desktop infrastructure workloads. Its Maxwell architecture on a 28 nm process provides a base clock of 1,033 MHz and a boost up to 1,306 MHz, which translates into respectable Geekbench OpenCL scores of 10,318 points. With a 225 W TDP and a PCIe 3.0 x16 interface, the card fits comfortably into most server chassis without demanding exotic power solutions. When you compare the cost per gigaflop, the Tesla M10 often undercuts newer Ampere cards, offering a compelling ROI for budget‑conscious data centers. However, its 2016 release date means you’ll need to verify driver support for the latest virtualization platforms. For teams focused on consistent performance rather than raw peak numbers, the M10 remains a pragmatic middle ground.

If you’re pairing the card, consider a dual‑CPU Xeon platform with at least 64 GB of DDR4 RAM to avoid bottlenecks on the PCIe bus. The NVIDIA's NVIDIA Tesla M10 pairs especially well with VMware Horizon or Citrix Virtual Apps, where its 8 GB of VRAM can be sliced across multiple users. Competitive alternatives such as the Quadro P4000 or the newer RTX A4000 provide higher rasterization scores, but they also come with a steeper price tag and higher power draw. The NVIDIA's NVIDIA Tesla M10’s longevity is bolstered by Maxwell’s proven driver pipeline, which NVIDIA has pledged to support through at least 2025. For a balanced build, match the Tesla M10 with a high‑efficiency power supply and a cooling solution that can sustain the 225 W load under continuous virtualization stress. The NVIDIA's NVIDIA Tesla M10 therefore shines when you need a cost‑effective, multi‑user GPU that won’t dominate your budget.

  • Cost analysis: strong price‑to‑performance ratio for multi‑user workloads.
  • Competitive alternatives: Quadro P4000, RTX A4000, and newer Tesla models.
  • Longevity: driver support expected through at least 2025.
  • Pairing suggestions: dual‑Xeon servers, 64 GB+ RAM, efficient PSU.
  • Benchmark highlights: 10,318 Geekbench OpenCL, 8,950 Geekbench Vulkan.

The AMD Equivalent of Tesla M10

Looking for a similar graphics card from AMD? The AMD Radeon RX 480 offers comparable performance and features in the AMD lineup.

AMD Radeon RX 480

AMD • 8 GB VRAM

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