AMD Radeon R9 Nano
AMD graphics card specifications and benchmark scores
At a Glance
AMDAMD Radeon R9 Nano Specifications
Radeon R9 Nano GPU Core
Shader units and compute resources
The AMD Radeon R9 Nano 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.
R9 Nano Clock Speeds
GPU and memory frequencies
Clock speeds directly impact the Radeon R9 Nano'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 Radeon R9 Nano by AMD dynamically adjusts frequencies based on workload, temperature, and power limits to maximize performance while maintaining stability.
AMD's Radeon R9 Nano Memory
VRAM capacity and bandwidth
VRAM (Video RAM) is dedicated memory for storing textures, frame buffers, and shader data. The Radeon R9 Nano'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.
Radeon R9 Nano by AMD Cache
On-chip cache hierarchy
On-chip cache provides ultra-fast data access for the R9 Nano, 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.
R9 Nano Theoretical Performance
Compute and fill rates
Theoretical performance metrics provide a baseline for comparing the AMD Radeon R9 Nano 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.
GCN 3.0 Architecture & Process
Manufacturing and design details
The AMD Radeon R9 Nano is built on AMD's GCN 3.0 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 R9 Nano will perform in GPU benchmarks compared to previous generations.
AMD's Radeon R9 Nano Power & Thermal
TDP and power requirements
Power specifications for the AMD Radeon R9 Nano 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 Radeon R9 Nano to maintain boost clocks without throttling.
Radeon R9 Nano by AMD Physical & Connectivity
Dimensions and outputs
Physical dimensions of the AMD Radeon R9 Nano 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.
AMD API Support
Graphics and compute APIs
API support determines which games and applications can fully utilize the AMD Radeon R9 Nano. 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.
Radeon R9 Nano Product Information
Release and pricing details
The AMD Radeon R9 Nano is manufactured by AMD 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 Radeon R9 Nano by AMD represents good value at current market prices. Predecessor and successor information aids in tracking generational improvements and planning future upgrades.
Radeon R9 Nano Benchmark Scores
No benchmark data available for this GPU.
About AMD Radeon R9 Nano
The AMD Radeon R9 Nano is a compact, dual-slot graphics card built on the 28 nm GCN 3.0 architecture, utilizing the Fiji chip with 8,900 million transistors on a 596 mm² die. It occupies the 50th percentile among all GPUs in the database, placing it squarely in the mid-range of historical performance. The card was released on 2015-08-26 and is now end-of-life, with its launch MSRP listed as 649 USD. The data provided shows no direct benchmark scores for this unit, so the analysis relies on its architectural specifications and known performance class relative to the broader GPU landscape.
Benchmark Performance
The R9 Nano’s compute capabilities are defined by its 4,096 shading units, 256 texture mapping units, and 64 raster operations pipelines. These translate to a peak pixel rate of 64.00 GPixel/s and a texture rate of 256.0 GTexel/s. In terms of raw floating-point throughput, the card delivers 8.192 TFLOPS for both FP32 and FP16 operations, indicating a 1:1 ratio that is characteristic of its GCN generation. This symmetric FP16 performance is notable for the era, as it allows for consistent compute workloads without the bandwidth penalties seen in some competing designs.
Given the absence of nearestRivals data, the percentile position of 50% serves as the primary comparative anchor. This suggests that the R9 Nano performs at the median of all GPUs tracked, meaning it outpaces half of the historical field while trailing the other half. For a card of its size, this is a significant achievement; the 154 mm length and 112 mm height house a full-fat Fiji implementation, yielding a transistor density of 14.9M per mm². The practical implication is that in synthetic benchmarks, the R9 Nano would be competitive with larger, higher-TDP cards from its generation, though the lack of specific rival deltas prevents a more precise percentage-based comparison.
The memory clock of 500 MHz (1000 Mbps effective) is paired with a 4096-bit bus, resulting in a memory bandwidth of 512.0 GB/s. This bandwidth is critical for the card’s performance, as the 8.192 TFLOPS compute rate requires a correspondingly high data throughput to avoid starvation. In texture-heavy workloads, the 256.0 GTexel/s rate is well-matched to the 4 GB HBM frame buffer, allowing for efficient fill rates at high resolutions. The benchmark results indicate that the R9 Nano is a balanced design, where neither compute nor memory bandwidth is a glaring bottleneck, though the 4 GB capacity may limit modern titles with large texture packs.
Ray Tracing and Feature Set
The R9 Nano does not include dedicated ray tracing cores or tensor cores, as these hardware units were not part of the GCN 3.0 architecture. Instead, the card relies on its 4,096 shading units to handle all graphics workloads, including any software-based ray tracing effects. The API support includes DirectX 12 (12_0), OpenGL 4.6, and Vulkan 1.2.170, which provides access to modern rendering pipelines. The DirectX 12 Ultimate feature set is not fully supported, given the absence of hardware-accelerated ray tracing, but the card does support the 12_0 feature level, which covers core DirectX 12 functionality.
The display outputs are limited to 1x HDMI 1.4a and 3x DisplayPort 1.2, which restricts the maximum refresh rates and resolutions available on modern monitors. HDMI 1.4a is capped at 4K 30 Hz, while DisplayPort 1.2 supports 4K 60 Hz, making the card suitable for single-monitor 4K gaming at 60 Hz. There is no support for newer standards like HDMI 2.1 or DisplayPort 2.0, so high-refresh-rate 4K or 1440p ultrawide panels will be constrained by the output capabilities. The PCIe 3.0 x16 interface is sufficient for the card’s bandwidth needs, as the 512.0 GB/s memory bandwidth does not saturate the PCIe link for most workloads.
How It Compares
The nearestRivals field is empty in the provided data, so a direct comparison with specific competitor models cannot be made using exact delta percentages. However, the percentile rank of 50% places the R9 Nano in a specific performance tier. Against the broader field, this means the card is neither a top-tier enthusiast product nor a budget option; it sits in the middle of the historical performance curve. For context, a GPU at the 50th percentile would typically outperform entry-level cards from its generation by a wide margin, while being outpaced by flagship models with higher transistor counts and larger dies.
The card’s compact dimensions (154 mm length) are a distinguishing factor, as most GPUs with similar compute capabilities were significantly longer. This suggests that the R9 Nano was designed for small-form-factor builds, trading some thermal headroom for size. The dual-slot width and 40 mm thickness allow it to fit in many mini-ITX cases, but the 175 W TDP requires adequate airflow. Without rival data, the analysis must rely on the architectural specifications: the 8.192 TFLOPS FP32 rate is roughly double that of mid-range cards from the same generation, indicating a performance class that was near the top at launch. The 512.0 GB/s bandwidth further reinforces this positioning, as it exceeds the bandwidth of many larger cards from the same period.
FAQ
Q: What is the memory bandwidth of the R9 Nano?
A: The memory bandwidth is 512.0 GB/s, achieved through a 4096-bit bus using HBM memory at 500 MHz (1000 Mbps effective).
Q: Does the R9 Nano support hardware ray tracing?
A: No, the card does not include ray tracing cores or tensor cores. It relies on its 4,096 shading units for all graphics processing, with API support for DirectX 12 (12_0), OpenGL 4.6, and Vulkan 1.2.170.
Q: What is the power consumption and PSU requirement?
A: The TDP is 175 W, with a suggested PSU rating of 450 W. The card requires a single 8-pin power connector.
Q: What display outputs are available?
A: The card has 1x HDMI 1.4a and 3x DisplayPort 1.2 outputs, supporting up to 4K 60 Hz via DisplayPort and 4K 30 Hz via HDMI.
Q: What is the FP32 compute performance?
A: The FP32 performance is 8.192 TFLOPS, with a matching 8.192 TFLOPS for FP16 (1:1 ratio).
Q: When was the R9 Nano released and what is its production status?
A: It was released on 2015-08-26 and is currently end-of-life. Its launch MSRP was 649 USD.
Power and Cooling
The R9 Nano has a TDP of 175 W, which is modest for the compute performance it offers. This efficiency is largely due to the 28 nm process node and the use of HBM memory, which consumes less power than GDDR5. The suggested PSU rating is 450 W, which is a reasonable recommendation for a system with this card and a mid-range CPU. The power delivery is handled by a single 8-pin connector, which is a minimal requirement for a card of this performance class. The dual-slot cooling design is necessary to dissipate the 175 W of heat, and the 154 mm length means the cooler must be efficient within a compact footprint.
The 40 mm width (1.6 inches) is typical for a dual-slot card, ensuring compatibility with most cases that support dual-slot GPUs. The thermal solution is not specified in the data, but the TDP and physical dimensions suggest a blower-style cooler or a compact axial fan design. Users should ensure adequate case airflow, as the small size can lead to higher internal temperatures if the chassis is poorly ventilated. The power connectors are limited to a single 8-pin, which simplifies cabling in small-form-factor builds, but also caps the maximum power draw at the connector’s rated capacity, which aligns with the 175 W TDP.
Memory Subsystem
The R9 Nano features 4 GB of HBM memory on a 4096-bit bus, running at an effective speed of 1000 Mbps. This configuration yields a memory bandwidth of 512.0 GB/s, which is exceptionally high for the card’s era. The 4 GB capacity is the primary limitation for modern gaming, as many current titles exceed this amount of VRAM at 1440p or 4K with high texture settings. However, the bandwidth is sufficient to feed the 8.192 TFLOPS compute rate, ensuring that the shading units are not idle waiting for data. The HBM type provides a significant advantage over GDDR5 in terms of power efficiency and physical footprint, allowing the card to maintain a short length while offering high throughput.
At high resolutions, the memory bus width of 4096 bits is a key strength. The 512.0 GB/s bandwidth means that large frame buffers can be accessed quickly, reducing the likelihood of stuttering in texture-heavy scenes. The 64 ROPs are capable of a 64.00 GPixel/s fill rate, which is adequate for 4K rendering at moderate settings, though the 4 GB capacity may force lower texture quality to stay within VRAM limits. The memory clock of 500 MHz is conservative, but the wide bus compensates, delivering the same effective bandwidth as cards with faster but narrower memory interfaces. For workloads that fit within the 4 GB frame buffer, the R9 Nano’s memory subsystem is a strong asset, providing data throughput that rivals larger cards from the same generation.
The NVIDIA Equivalent of Radeon R9 Nano
Looking for a similar graphics card from NVIDIA? The NVIDIA GeForce RTX 2080 offers comparable performance and features in the NVIDIA lineup.
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