NVIDIA Tesla C870
NVIDIA graphics card specifications and benchmark scores
At a Glance
NVIDIANVIDIA Tesla C870 Specifications
GPU Core
Shader units and compute resources
The NVIDIA Tesla C870 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.
Tesla C870 Clock Speeds
GPU and memory frequencies
Clock speeds directly impact the Tesla C870'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 C870 by NVIDIA dynamically adjusts frequencies based on workload, temperature, and power limits to maximize performance while maintaining stability.
NVIDIA's Tesla C870 Memory
VRAM capacity and bandwidth
VRAM (Video RAM) is dedicated memory for storing textures, frame buffers, and shader data. The Tesla C870'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.
Tesla C870 by NVIDIA Cache
On-chip cache hierarchy
On-chip cache provides ultra-fast data access for the Tesla C870, 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.
Tesla C870 Theoretical Performance
Compute and fill rates
Theoretical performance metrics provide a baseline for comparing the NVIDIA Tesla C870 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.
Tesla Architecture & Process
Manufacturing and design details
The NVIDIA Tesla C870 is built on NVIDIA's Tesla 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 C870 will perform in GPU benchmarks compared to previous generations.
Power & Thermal
TDP and power requirements
Power specifications for the NVIDIA Tesla C870 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 C870 to maintain boost clocks without throttling.
Tesla C870 by NVIDIA Physical & Connectivity
Dimensions and outputs
Physical dimensions of the NVIDIA Tesla C870 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.
NVIDIA API Support
Graphics and compute APIs
API support determines which games and applications can fully utilize the NVIDIA Tesla C870. 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.
Tesla C870 Product Information
Release and pricing details
The NVIDIA Tesla C870 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 C870 by NVIDIA represents good value at current market prices. Predecessor and successor information aids in tracking generational improvements and planning future upgrades.
About NVIDIA Tesla C870
The NVIDIA Tesla C870 is a foundational compute accelerator built on the 90 nm G80 chip, positioned as an end-of-life product within its generation. With a percentile rank of 50 among all GPUs, this card represents the median of historical performance, offering 345.6 GFLOPS of FP32 compute and 76.80 GB/s of memory bandwidth. This analysis interprets its specifications and capabilities relative to its era, focusing on compute-oriented workloads rather than gaming.
How It Compares
The data for the Tesla C870 shows no nearest rivals in the provided benchmark database, which indicates it was a unique compute-focused product without direct contemporaries in the comparison set. This absence of comparative scores means its 50th percentile ranking is derived from the broader pool of all GPUs, not from peer-to-peer matchups.
Without rival deltas to reference, the C870's position must be understood through its absolute specifications. Its 345.6 GFLOPS FP32 throughput and 76.80 GB/s bandwidth place it as a mid-pack performer in the historical context, capable of handling scientific and rendering workloads that were common in its release period but far behind modern accelerators.
The lack of nearestRivals data also means that any performance comparison must rely on the raw figures provided: the 14.40 GPixel/s pixel rate and 38.40 GTexel/s texture rate. These numbers indicate a card designed for compute density, not for rasterization speed, which aligns with its Tesla branding as a dedicated processing unit.
Memory Subsystem
The Tesla C870 is equipped with 1536 MB of GDDR3 memory, a substantial capacity for its time, connected via a 384-bit bus. This configuration yields a peak bandwidth of 76.80 GB/s, which is the critical metric for compute workloads that stream large datasets.
For high-resolution rendering or scientific simulation, the bandwidth figure determines how quickly data can be fed to the 128 shading units. The 384-bit interface provides a wide path, but the 1600 Mbps effective memory speed limits the overall throughput compared to later GDDR5 or HBM solutions.
At resolutions typical of the 2007 era, such as 1920x1200, this bandwidth is sufficient for texture-heavy scenes, but the card's lack of display outputs confirms it was never intended for direct visualization. Instead, the memory subsystem is optimized for data-parallel tasks where the 76.80 GB/s can be fully utilized by compute shaders.
The 1536 MB capacity is notable, as it allows larger working sets to reside on-card, reducing PCIe 1.0 x16 transfers. This bus interface, with its limited bandwidth, would bottleneck frequent data exchange, making the large framebuffer a necessity for serious compute applications.
Ray Tracing and Feature Set
The Tesla C870 has no dedicated ray tracing cores and no tensor cores, as the architecture predates those specialized units. The G80 chip relies entirely on its 128 unified shading units for all processing, handling both vertex and pixel work in a single pipeline.
API support includes DirectX 11.1 (feature level 10_0) and OpenGL 3.3, with no Vulkan support. This means the card cannot execute modern ray-traced workloads via hardware acceleration, and any ray tracing would need to be implemented in software on the shading units, which would be severely limited by the 345.6 GFLOPS compute capacity.
The feature set is compute-first: the 32 texture mapping units and 24 ROPs are present for basic rasterization, but the card's real value lies in its FP32 throughput. For the era, the Tesla architecture introduced unified shaders, which allowed more flexible workload distribution compared to separate pixel and vertex pipelines.
Lacking Vulkan support further restricts its use in contemporary applications, but for legacy compute frameworks like CUDA (implied by the Tesla branding), the 128 shaders provide a predictable execution model. The absence of display outputs confirms this is a pure coprocessor, offloading simulation or rendering tasks from the host CPU.
FAQ
Q: What is the memory bandwidth of the Tesla C870?
A: The card provides 76.80 GB/s of bandwidth via a 384-bit bus with GDDR3 memory running at 1600 Mbps effective.
Q: Does the Tesla C870 support hardware ray tracing?
A: No, it has zero RT cores and zero tensor cores, so all ray tracing must be done in software, which is impractical given the 345.6 GFLOPS FP32 limit.
Q: What power connectors does this card require?
A: The Tesla C870 uses two 6-pin power connectors, and the suggested power supply is rated at 450 W.
Q: Can this card output video to a display?
A: No, the Tesla C870 has no display outputs, making it strictly a compute device.
Q: What is the transistor count and die size?
A: The G80 chip contains 681 million transistors on a 484 mm² die, manufactured on a 90 nm process by TSMC.
Q: What is the pixel and texture fill rate?
A: The card achieves 14.40 GPixel/s pixel rate and 38.40 GTexel/s texture rate, based on the 24 ROPs and 32 TMUs.
Benchmark Performance
The Tesla C870 has an average benchmark score of 0, with a percentile rank of 50 against all GPUs in the database. This zero score is not representative of failure but rather indicates that no standardized benchmarks were recorded for this compute card, which is common for non-gaming accelerators.
Without nearestRivals data, the performance analysis relies on the theoretical throughput figures. The FP32 rate of 345.6 GFLOPS is the headline number, and for context, this is derived from 128 shading units operating at the memory clock's base frequency, assuming one FMA operation per cycle per unit.
The pixel rate of 14.40 GPixel/s and texture rate of 38.40 GTexel/s are modest by any standard, and they confirm that the C870 was not optimized for traditional rendering. In compute tasks such as dense linear algebra or finite-difference simulations, the 345.6 GFLOPS would be the limiting factor, and the 76.80 GB/s bandwidth would support a compute-to-memory ratio that is well-balanced for 2007-era algorithms.
The 50th percentile rank suggests that, across the entire historical GPU landscape, this card sits exactly in the middle. This is a reasonable position for a 2007 product that has been surpassed by over a decade of architectural improvements, but it also indicates that the C870 was not a low-end part at launch, given its $1,499 launch MSRP.
Power and Cooling
The Tesla C870 has a thermal design power of 171 W, which is a substantial draw for a dual-slot card. The cooling solution is unspecified beyond the dual-slot width, but the power connectors are two 6-pin PCIe power plugs, requiring a power supply rated at 450 W or higher.
The 90 nm process node is relatively large, contributing to the 171 W TDP despite the modest clock speeds. The 681 million transistors on a 484 mm² die generate significant heat, and the dual-slot cooler is necessary to dissipate it under sustained compute loads.
For system integration, the 450 W PSU recommendation is modest by modern standards, but the 2x 6-pin requirement means older power supplies without these connectors would need adapters. The card's PCIe 1.0 x16 interface draws up to 75 W from the slot, with the remainder supplied by the auxiliary connectors.
In a server chassis with adequate airflow, the 171 W TDP is manageable, but the lack of display outputs means this card was intended for rack-mounted systems where noise and heat are secondary to compute density. The dual-slot design also limits the number of cards that can be installed in a given chassis.
Who Should Consider It
The Tesla C870 is suitable for users running legacy compute applications that were compiled for the Tesla architecture, particularly those using CUDA or OpenCL frameworks that do not require newer features. The 1536 MB memory capacity is sufficient for datasets that fit within that limit, and the 76.80 GB/s bandwidth can sustain moderate throughput.
At a 50th percentile ranking, this card is not competitive for modern gaming or professional rendering; its 14.40 GPixel/s pixel rate is far below any current integrated GPU. However, for historical analysis or retro compute projects, the 345.6 GFLOPS FP32 performance offers a deterministic platform for benchmarking older algorithms.
Users with a 450 W PSU and a motherboard with a PCIe 1.0 x16 slot can install this card, but they must accept the 171 W TDP and the need for two 6-pin connectors. The absence of display outputs means it cannot serve as a primary GPU, so a separate card is required for any visual output.
Given its end-of-life status and the lack of Vulkan support, the C870 is strictly for niche applications. Enthusiasts of vintage hardware or researchers replicating 2007-era compute results will find the specifications well-documented, but for any practical modern workload, the performance is insufficient. The card's 50th percentile standing confirms its historical mediocrity, yet its role as a dedicated compute accelerator makes it a curious artifact of the pre-GPGPU era.
Detailed benchmark scores and charts for the NVIDIA Tesla C870 are below.
Benchmark Scores
No benchmark data available for this GPU.
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