NVIDIA GeForce RTX 4090 Max-Q vs NVIDIA N1 16SM Comparison

The NVIDIA GeForce RTX 4090 Max-Q and the NVIDIA N1 16SM occupy opposite ends of the mobile GPU spectrum, despite both being integrated-class parts from the same manufacturer. The RTX 4090 Max-Q is a high-end discrete solution from the Ada Lovelace generation, while the N1 16SM is a Blackwell 2.0 IGP designed for a different performance envelope. The recorded data shows a clear split: the RTX 4090 Max-Q delivers massive compute throughput, while the N1 16SM counters with a much newer architecture, a vastly larger memory pool, and a higher boost clock. The following analysis breaks down where each part wins, how their architectures diverge, and what the specifications imply for real-world workloads.

Where Each One Wins

The RTX 4090 Max-Q wins decisively in raw shader performance. With 9,728 shading units compared to the N1 16SM’s 2,048, the Ada Lovelace part has nearly five times the parallel processing capacity. This translates directly to its FP32 output: 28.31 TFLOPS against the N1 16SM’s 9.609 TFLOPS. For graphics rendering, game physics, and general compute tasks that rely on floating-point math, the RTX 4090 Max-Q is the clear leader. Its texture rate of 442.3 GTexel/s also dwarfs the N1 16SM’s 300.3 GTexel/s, and its pixel rate of 163.0 GPixel/s more than doubles the N1 16SM’s 56.30 GPixel/s. The data indicates that any workload dominated by pixel shading or texture fetching will favor the RTX 4090 Max-Q.

The N1 16SM wins in memory capacity and architecture recency. It packs 128 GB of LPDDR5X memory, a figure eight times larger than the RTX 4090 Max-Q’s 16 GB of GDDR6. This makes the N1 16SM suited for large datasets, in-memory computing, or AI inference workloads that require holding massive models or buffers without spilling to system storage. Additionally, the N1 16SM operates on the Blackwell 2.0 architecture, a newer design than Ada Lovelace, which suggests improvements in instruction efficiency and feature support that are not captured by raw throughput numbers alone. Its boost clock of 2,346 MHz is substantially higher than the RTX 4090 Max-Q’s 1,455 MHz, indicating that single-threaded or lightly-threaded tasks may run faster on the N1 16SM despite its lower core count.

The bus interface also differs: the N1 16SM uses PCIe 5.0 x16, while the RTX 4090 Max-Q uses PCIe 4.0 x16. For data transfer to and from the host system, the newer standard offers a potential bandwidth advantage, although the actual benefit depends on system-level support.

Architecture Differences

The RTX 4090 Max-Q is built on the AD103 chip using the Ada Lovelace architecture, manufactured by TSMC on a 5 nm process. It contains 45,900 million transistors on a 379 mm² die, yielding a transistor density of 121.1M per mm². The N1 16SM uses the GB20B chip under the Blackwell 2.0 architecture, also on a 5 nm TSMC process, with a die size of 382 mm² (transistor count is not recorded). The die sizes are nearly identical, but the architectural philosophies diverge sharply.

The RTX 4090 Max-Q is a full-featured GPU with 304 texture mapping units, 112 ROPs, 76 ray tracing cores, and 304 tensor cores. It supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, making it a complete graphics solution for gaming and professional applications. The N1 16SM, in contrast, reports no API support in the database (DirectX, OpenGL, and Vulkan are all listed as N/A), which implies it is not designed for traditional graphics rendering. Instead, it has 128 texture mapping units, 24 ROPs, 16 ray tracing cores, and 64 tensor cores. The lower ROP and TMU counts suggest a compute-focused design, where memory capacity and tensor core throughput matter more than rasterization.

The memory subsystems are fundamentally different. The RTX 4090 Max-Q uses 16 GB of GDDR6 with a 256-bit bus, achieving 576.0 GB/s of bandwidth. The N1 16SM uses 128 GB of LPDDR5X with the same 256-bit bus width but only 273.2 GB/s of bandwidth. The RTX 4090 Max-Q offers more than double the memory bandwidth, which is critical for high-resolution textures and real-time effects. The N1 16SM trades bandwidth for capacity, a decision that favors workloads where storing large working sets locally outweighs the need for fast streaming.

Power delivery also contrasts. The RTX 4090 Max-Q has a recorded TDP of 80 W and requires no power connectors, indicating a power-efficient mobile design. The N1 16SM’s TDP is listed as unknown, but it also uses no power connectors. Both are IGP-class (integrated graphics processor) in terms of slot width, meaning they are designed for compact, low-power systems.

Head-to-Head Benchmarks

The database lists no direct head-to-head benchmark results between these two parts, and both have an average benchmark score of 0 with a percentile rank of 50 against all GPUs. Despite the absence of measured scores, the specification data provides clear comparative signals.

The most significant win for the RTX 4090 Max-Q is in FP32 compute: 28.31 TFLOPS versus 9.609 TFLOPS for the N1 16SM. This is a 2.95x advantage, meaning the Ada Lovelace part can process roughly three times as many floating-point operations per second. For workloads like physics simulation, scientific computing, or AI training (where FP32 is still used), this gap is decisive. The RTX 4090 Max-Q also leads in texture fill rate (442.3 GTexel/s vs 300.3 GTexel/s, a 1.47x gap) and pixel fill rate (163.0 GPixel/s vs 56.30 GPixel/s, a 2.90x gap). These metrics confirm that the RTX 4090 Max-Q is the superior rasterizer.

The N1 16SM counters with a higher boost clock: 2,346 MHz versus 1,455 MHz. This 891 MHz difference suggests that for tasks that are latency-bound or single-threaded, the N1 16SM may complete operations faster, even with fewer cores. Its base clock is lower (741 MHz vs 930 MHz), but the boost behavior indicates a design that can ramp up significantly under load. Memory capacity is another clear win: 128 GB versus 16 GB. For any workload that exceeds 16 GB of working set, the N1 16SM can proceed without swapping, while the RTX 4090 Max-Q would be forced to use system memory, incurring a performance penalty.

Memory bandwidth favors the RTX 4090 Max-Q at 576.0 GB/s versus 273.2 GB/s. This means that while the N1 16SM has more memory, it accesses it at less than half the speed. For applications that stream data continuously, such as video processing or large matrix operations, the RTX 4090 Max-Q will sustain higher throughput.

Specification Differences

The two parts differ in nearly every specification field. The RTX 4090 Max-Q has a base clock of 930 MHz and a boost clock of 1,455 MHz, while the N1 16SM runs at 741 MHz base and 2,346 MHz boost. Memory speed differs: the RTX 4090 Max-Q uses 2,250 MHz (18 Gbps effective) GDDR6, while the N1 16SM uses 1,067 MHz (8.5 Gbps effective) LPDDR5X. Memory size is 16 GB versus 128 GB, bandwidth is 576.0 GB/s versus 273.2 GB/s, and both use a 256-bit bus.

Shading units: 9,728 versus 2,048. TMUs: 304 versus 128. ROPs: 112 versus 24. Ray tracing cores: 76 versus 16. Tensor cores: 304 versus 64. Pixel rate: 163.0 GPixel/s versus 56.30 GPixel/s. Texture rate: 442.3 GTexel/s versus 300.3 GTexel/s. FP32 and FP16 are both 28.31 TFLOPS on the RTX 4090 Max-Q and 9.609 TFLOPS on the N1 16SM, with a 1:1 ratio on both.

The RTX 4090 Max-Q has a TDP of 80 W; the N1 16SM’s TDP is unknown. The RTX 4090 Max-Q supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, while the N1 16SM has N/A for all three. Display outputs: the RTX 4090 Max-Q is "Portable Device Dependent," while the N1 16SM has 1x HDMI. Bus interface: PCIe 4.0 x16 versus PCIe 5.0 x16. Process node is 5 nm for both, and both use TSMC as the foundry. The RTX 4090 Max-Q has a die size of 379 mm² and 45,900 million transistors; the N1 16SM has a die size of 382 mm² and an unknown transistor count. Release dates differ: the RTX 4090 Max-Q launched on 2023-01-02, while the N1 16SM is dated 2026-05-31.

FAQ

Q: Which GPU has higher FP32 compute performance?

A: The RTX 4090 Max-Q delivers 28.31 TFLOPS, which is 2.95 times the N1 16SM’s 9.609 TFLOPS.

Q: How much memory does each part have?

A: The RTX 4090 Max-Q has 16 GB of GDDR6, while the N1 16SM has 128 GB of LPDDR5X.

Q: Which one has a faster boost clock?

A: The N1 16SM boosts to 2,346 MHz, compared to the RTX 4090 Max-Q’s 1,455 MHz.

Q: What is the memory bandwidth difference?

A: The RTX 4090 Max-Q achieves 576.0 GB/s, more than double the N1 16SM’s 273.2 GB/s.

Q: Do both parts support the same graphics APIs?

A: No. The RTX 4090 Max-Q supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4. The N1 16SM lists N/A for all three.

Q: Which part has more texture mapping units?

A: The RTX 4090 Max-Q has 304 TMUs, while the N1 16SM has 128 TMUs.

The Verdict

The data points to a clear division of roles. The RTX 4090 Max-Q is the choice for graphics-intensive and compute-heavy tasks where throughput is paramount. Its 28.31 TFLOPS FP32, 576.0 GB/s bandwidth, and full API support make it suitable for gaming, 3D rendering, and real-time effects. The 80 W TDP and IGP form factor indicate it can fit in power-constrained mobile devices, but the performance is unmistakably high-end.

The N1 16SM is oriented toward memory capacity and architectural novelty. Its 128 GB LPDDR5X pool is unmatched by the RTX 4090 Max-Q, and the Blackwell 2.0 architecture with a 2,346 MHz boost clock suggests it is built for workloads that benefit from large resident datasets and high single-thread responsiveness. The lack of graphics API support implies it is not intended for conventional rendering, but rather for compute, AI inference, or specialized data processing where API compatibility is irrelevant.

For a system designer choosing between them, the decision rests on the workload. If the application demands raw floating-point throughput, texture filtering, or pixel output, the RTX 4090 Max-Q is the superior part. If the application requires holding more than 16 GB of data on the GPU and can tolerate lower bandwidth, the N1 16SM is the only option. The RTX 4090 Max-Q is a mature, fully-featured GPU; the N1 16SM is a specialized IGP with a different set of priorities. Neither part is universally better; their advantages are complementary and workload-specific.