Calculate the TPS of the Switch 2 GPU on local AI models
Every model in our catalogue assessed against this card at the context length and minimum quality you choose. Speed is an estimate for a single request, calculated from this card's memory bandwidth and the size of each model once compressed.
Calculated for this card
Largest model it holds
ERNIE-4.5-21B-A3B
21B · Q3_K_M · 31.0 tok/s
Fastest model
Gemma 3 QAT 1B
43.4 tok/s · 1B
What AI models can a Switch 2 GPU run?
Set the inputs, read the answer
More context means more memory for the conversation cache. Speed is for a fresh conversation and does not change with this setting.
Hides models that would only fit by being compressed below this point.
396 models match
Calculating| Quantisation | Fit | ||||||
|---|---|---|---|---|---|---|---|
|
43.4
tok/s
37–52 |
Gemma 3 1B | 1B | Mar 2025 | 1.8 GB | 33k tokens | Q8_0 | Comfortable |
|
43.4
tok/s
37–52 |
Gemma 3 QAT 1B | 1B | Apr 2025 | 1.8 GB | 33k tokens | Q8_0 | Comfortable |
|
43.4
tok/s
26–69 · low confidence |
HGRN 1B (WT 103) ≈ | 1B | Nov 2023 | 1.8 GB | 131k tokens ? | Q8_0 | Comfortable |
|
43.4
tok/s
26–69 · low confidence |
LLama 3..2 Typhoon 2 1B ≈ | 1B | Dec 2024 | 1.8 GB | 131k tokens ? | Q8_0 | Comfortable |
|
43.4
tok/s
26–69 · low confidence |
OLMo-1B ≈ | 1B | Feb 2024 | 1.8 GB | 131k tokens ? | Q8_0 | Comfortable |
|
43.4
tok/s
26–69 · low confidence |
Pythia-1b ≈ | 1B | Apr 2023 | 1.8 GB | 131k tokens ? | Q8_0 | Comfortable |
|
40.2
tok/s
24–64 · low confidence |
OpenELM-1.1B ≈ | 1.1B | May 2024 | 1.9 GB | 131k tokens ? | Q8_0 | Comfortable |
|
39.4
tok/s
24–63 · low confidence |
DeciCoder-1B ≈ | 1.1B | Aug 2023 | 1.9 GB | 131k tokens ? | Q8_0 | Comfortable |
|
39.4
tok/s
24–63 · low confidence |
SantaCoder ≈ | 1.1B | Jan 2023 | 1.9 GB | 131k tokens ? | Q8_0 | Comfortable |
|
39.4
tok/s
24–63 · low confidence |
TinyLlama-1.1B (1T token checkpoint) ≈ | 1.1B | Oct 2023 | 1.9 GB | 131k tokens ? | Q8_0 | Comfortable |
|
39.4
tok/s
24–63 · low confidence |
TinyLlama-1.1B (3T token checkpoint) ≈ | 1.1B | Oct 2023 | 1.9 GB | 131k tokens ? | Q8_0 | Comfortable |
|
36.1
tok/s
22–58 · low confidence |
EXAONE 4.0 (1.2B) ≈ | 1.2B | Jul 2025 | 2.0 GB | 131k tokens ? | Q8_0 | Comfortable |
|
36.1
tok/s
22–58 · low confidence |
MinerU2.5 ≈ | 1.2B | Sep 2025 | 2.0 GB | 131k tokens ? | Q8_0 | Comfortable |
|
36.1
tok/s
22–58 · low confidence |
Pleias 1.0 1.2B ≈ | 1.2B | Dec 2024 | 2.0 GB | 131k tokens ? | Q8_0 | Comfortable |
|
36.1
tok/s
22–58 · low confidence |
Pleias-RAG-1B ≈ | 1.2B | Apr 2025 | 2.0 GB | 131k tokens ? | Q8_0 | Comfortable |
|
35.3
tok/s
30–42 |
Llama 3.2 1B | 1.2B | Sep 2024 | 2.2 GB | 131k tokens | Q8_0 | Comfortable |
|
34.8
tok/s
21–56 · low confidence |
DeepSeekMoE-16B | 16B | Jan 2024 | 10.0 GB | 4k tokens | Q4_K_M | Tight |
|
34.8
tok/s
21–56 · low confidence |
MiniCPM-1.2B ≈ | 1.2B | Jun 2024 | 2.0 GB | 131k tokens ? | Q8_0 | Comfortable |
|
33.4
tok/s
20–53 · low confidence |
DeepSeek Coder 1.3B ≈ | 1.3B | Jan 2024 | 2.1 GB | 131k tokens ? | Q8_0 | Comfortable |
|
33.4
tok/s
20–53 · low confidence |
DeepSeek-VL-1.3B ≈ | 1.3B | Mar 2024 | 2.1 GB | 131k tokens ? | Q8_0 | Comfortable |
|
33.4
tok/s
20–53 · low confidence |
DigiRL ≈ | 1.3B | Jun 2024 | 2.1 GB | 131k tokens ? | Q8_0 | Comfortable |
|
33.4
tok/s
20–53 · low confidence |
GLA Transformer 1.3B ≈ | 1.3B | Aug 2024 | 2.1 GB | 131k tokens ? | Q8_0 | Comfortable |
|
33.4
tok/s
20–53 · low confidence |
Janus 1.3B ≈ | 1.3B | Oct 2024 | 2.1 GB | 131k tokens ? | Q8_0 | Comfortable |
|
33.4
tok/s
20–53 · low confidence |
Kosmos-2.5 ≈ | 1.3B | Aug 2024 | 2.1 GB | 131k tokens ? | Q8_0 | Comfortable |
|
33.4
tok/s
20–53 · low confidence |
Otter ≈ | 1.3B | May 2023 | 2.1 GB | 131k tokens ? | Q8_0 | Comfortable |
Speeds are estimates for a single request — one conversation at a time — calculated from memory bandwidth, model size and quantisation. Real throughput varies with the inference runtime and its version. Figures published by hardware vendors measure many simultaneous requests and are much higher.
On record
Switch 2 GPU full specification
Everything on record for this board, ordered by how much it bears on running a language model rather than by how a spec sheet would list it. Memory comes first because it decides the outcome; the rest is context.
Memory
The two specifications that decide what this card can run and how quickly. Capacity sets which models fit; bandwidth sets how many tokens per second they produce once they do.
- Memory size
- 12 GB
- Memory bandwidth
- 102 GB/s
- Memory type
- LPDDR5X
- Memory bus width
- 128 bit
- Memory clock
- 800 MHz
The chip
Which processor is on the board and how it was manufactured. A smaller process size generally means more performance for the same power.
- Graphics processor
- GA10B
- Architecture
- Ampere
- Generation
- Console GPU(Nintendo)
- Foundry
- Samsung
- Process size
- 8 nm
- Die size
- 200 mm²
- Released
- 5 June 2025
Clock speeds
How fast the processor runs. Worth far less here than on a gaming benchmark: generating text is limited by memory bandwidth, so a higher clock barely moves the result.
- Base clock
- 561 MHz
- Boost clock
- 1.4 GHz
Processing units
What the chip contains. These drive graphics performance and matter mainly for processing a long prompt rather than for producing the answer.
- Shading units
- 1,536
- Texture mapping units
- 48
- Render output units
- 16
- Streaming multiprocessors
- 12
- Tensor cores
- 48
- Ray tracing cores
- 12
- L1 cache
- 128 KB
- L2 cache
- 4 MB
Theoretical performance
Peak arithmetic rates published for the board. These are ceilings that no real workload reaches, and generating text reaches a small fraction of them because it is limited by memory rather than arithmetic.
- Half precision (FP16)
- 8.6 TFLOPS
- Single precision (FP32)
- 4.3 TFLOPS
- Double precision (FP64)
- 2.2 TFLOPS
- Pixel rate
- 22 GPixel/s
- Texture rate
- 67 GTexel/s
The board
What it takes to physically install and power the card — the practical constraints that decide whether it fits the machine you already own.
- Power draw (TDP)
- 40 W
- Dimensions
- 272 mm × 14 mm
Software support
Which graphics and compute interfaces the card supports. CUDA compute capability is the one that bears on inference: below 7.0 there are no tensor cores, and modern inference software falls back to slower code paths.
- CUDA compute capability
- 8.7
- DirectX
- 12.2
- OpenGL
- 4.6
- Vulkan
- 1.4
- OpenCL
- 3.0
- Shader model
- 6.8
Listings
Where to buy a Switch 2 GPU
No vendor is currently listing this card. Listings come from vendors who publish them here directly — browse the vendor directory to see who is selling what.
What the numbers mean
Why memory is the number that matters here
Memory
12 GB
Bandwidth
102 GB/s
Largest model
ERNIE-4.5-21B-A3B
12 GB of LPDDR5X puts the Switch 2 GPU comfortably into small and mid-sized models, with roughly 10.8 GB usable once the driver overhead is taken out. The largest models are out of reach without splitting them.
At 102 GB/s across a 128-bit bus, bandwidth is this card's real constraint. Every token requires reading the entire model out of memory, so a large model will feel slow here even when it fits.
That comes from a 800 MHz memory clock across the bus width above. Widening the bus and raising the clock are the two levers a manufacturer has, which is why a card with unremarkable cores can still generate quickly.
In practice that combination tops out at ERNIE-4.5-21B-A3B — 21B, compressed to Q3_K_M, generating around 31.0 tokens per second.
The chip and how it was built
The Switch 2 GPU is built on the GA10B graphics processor, using NVIDIA's Ampere architecture, as part of the Console GPU(Nintendo) generation.
The chip is manufactured by Samsung, on a 8 nm process, with a die measuring 200 mm². A smaller process generally means more performance for the same power, though for language models it matters far less than the memory subsystem.
It was released in June 2025, roughly 1 years ago. Inference software support tends to follow hardware by a year or two, so a card of this age generally has mature, well-optimised code paths available to it.
Compute throughput, and why it matters less than it looks
FP16
8.6 TFLOPS
FP64
2.2 TFLOPS
Tensor cores
48
On paper the Switch 2 GPU reaches 8.6 TFLOPS at half precision and 4.3 TFLOPS at single precision. These are peak figures no real workload sustains, and generating text reaches only a small fraction of them — decoding is limited by memory rather than arithmetic, which is why a card can look enormously powerful here and still produce tokens at an ordinary rate.
Double-precision throughput is 2.2 TFLOPS. It has no bearing on running a language model — no inference runtime uses it — but it separates datacentre parts from consumer ones, since the latter deliberately restrict it.
The card carries 48 tensor cores across 12 streaming multiprocessors. These accelerate the matrix arithmetic at the heart of a transformer, and they are what make prompt processing — reading a long document before answering — dramatically faster than it would otherwise be.
Clocks run from 561 MHz at base to 1.4 GHz boosted. Worth far less here than on a gaming benchmark: raising the clock speeds up the arithmetic, and the arithmetic is not what generation is waiting on.
Cache and processing units
The Switch 2 GPU has 128 KB of L1 cache, backed by 4 MB of L2. Cache absorbs a share of the memory traffic that would otherwise hit the main bus, which is the one place on this page where a number other than bandwidth quietly affects generation speed — a large L2 lets more of the working set stay close to the cores.
There are 1,536 shading units, 48 texture mapping units, and 16 render output units. These drive graphics workloads and contribute to prompt processing, but they sit idle for much of the time a model spends generating a reply.
Power, size and installation
Power draw
40 W
The Switch 2 GPU is rated at 40 W. Running a language model keeps a card busy in bursts rather than continuously — it draws hard while generating and idles between requests — so sustained draw over a working day is usually well below the rated figure.
measuring 272 mm long. Worth checking against the case and power supply already in the machine, since the largest cards need considerably more of both than a typical desktop provides.
The extremes
The largest AI models a Switch 2 GPU can run
The biggest open-weight models that fit on this card, newest first. Each is shown at the best compression the card can hold.
The fastest AI models on a Switch 2 GPU
Where this card produces tokens quickest. Smaller models dominate here, because generating each token means reading the whole model out of memory once.
Step by step
How to work out the tokens per second of a Switch 2 GPU
You do not have to calculate anything by hand — the gputps.com calculator on this page has already worked it out for every model this card can hold. Reading off the answer takes six steps.
-
01
Search for the model you want
Every one of the 396 models this Switch 2 GPU runs is in the table above. Search narrows it by name or by size.
-
02
Set the context length you will actually use
Set the context to your real working length. Short questions cost almost nothing; a long document can consume a large share of the card's 12 GB.
-
03
Pin the comparison to one quality level
Compression is what lets bigger models fit. The quality control drops any model that needs more of it than you are willing to give.
-
04
Read the speed and the range
The figures are calculated, not measured. 43.4 tok/s on Gemma 3 QAT 1B is the fastest result on this card, and like every row it carries a range that reflects how much the runtime matters.
-
05
Read the fit verdict last
The fit column separates models that just fit from those with room to spare — worth checking against the card's 12 GB before settling on one.
-
06
Cross-check against other hardware
Every model name in the table links to its own page, which runs the same calculation across every card we hold. That is where you see whether the Switch 2 GPU is the right buy for it or merely a card that fits.
Answers
Switch 2 GPU — common questions
How much cache does a Switch 2 GPU have?
The Switch 2 GPU has 128 KB of L1 cache, and 4 MB of L2 cache. Cache absorbs part of the memory traffic that would otherwise reach the main bus, so a larger L2 gives a modest lift to generation speed beyond what bandwidth alone predicts.
What are the TFLOPS of a Switch 2 GPU?
The Switch 2 GPU is rated at 8.6 TFLOPS at half precision and 4.3 TFLOPS at single precision. These are peak arithmetic ceilings rather than achievable rates, and text generation reaches only a small fraction of them because it is limited by memory bandwidth instead.
How many tensor cores does a Switch 2 GPU have?
The Switch 2 GPU has 48 tensor cores across 12 streaming multiprocessors. They accelerate the matrix arithmetic a transformer is built from, which mainly speeds up processing a long prompt rather than producing the reply.
Does the Switch 2 GPU support CUDA?
Yes. The Switch 2 GPU reports CUDA compute capability 8.7. Capability 7.0 and above has tensor cores, which modern inference software uses; below that it falls back to slower code paths for quantised models.
Is the Switch 2 GPU good for running local AI models?
Its memory covers small and mid-sized models, though the largest are out of reach though its bandwidth means generation will feel slow on larger models. In total it runs 396 of the models we track. Whether that is enough depends entirely on which model you want — the table above answers that directly.
Can a Switch 2 GPU run a model that does not fit in its memory?
Only partly. Layers beyond the 12 GB sit in system memory and run at a fraction of the speed, so a mostly-offloaded model is rarely worth using. Every figure here assumes it is fully resident on the card.
Would two Switch 2 GPU cards be twice as fast?
No. A second Switch 2 GPU doubles the memory to 24 GB, which lets you hold models neither could hold alone, but generation does not split that way. These figures describe one card.
What AI models can a Switch 2 GPU run?
396 of the 679 open-weight language models we track fit on a Switch 2 GPU and can be run locally on it. The table on this page lists every one, with the memory it needs, the quantisation it runs at and an estimated generation speed.
What is the largest AI model a Switch 2 GPU can run?
The largest model in our catalogue that fits on a Switch 2 GPU is ERNIE-4.5-21B-A3B at 21B parameters, compressed to Q3_K_M. It generates roughly 31.0 tokens per second and needs about 10.1 GB of the card's memory.
How many tokens per second does a Switch 2 GPU produce?
It depends on the model. On a Switch 2 GPU the fastest model we track is Gemma 3 QAT 1B at about 43.4 tokens per second, while larger models run proportionally slower because each token requires reading the whole model out of memory once. Speeds are estimates for a single conversation at a time.
Can a Switch 2 GPU run a 7B model?
Yes. For example a Switch 2 GPU runs DeepSeek Coder 6.7B at Q6_K, using about 9.9 GB of memory and generating around 9.4 tokens per second.
Can a Switch 2 GPU run a 13B model?
Yes. For example a Switch 2 GPU runs DeepSeekMoE-16B at Q4_K_M, using about 10.0 GB of memory and generating around 34.8 tokens per second.
How much memory does a Switch 2 GPU have?
A Switch 2 GPU has 12 GB of LPDDR5X memory. Around a tenth of that is reserved by the inference runtime and the driver, leaving roughly 10.8 GB available for a model and its conversation.
What is the memory bandwidth of a Switch 2 GPU?
The Switch 2 GPU has 102 GB/s of memory bandwidth, across a 128-bit memory bus. This is the single best predictor of how fast it generates text, because producing each token means reading the entire model out of memory once.
What type of memory does a Switch 2 GPU use?
It uses LPDDR5X clocked at 800 MHz. HBM types are found on datacentre accelerators and carry far more bandwidth than the GDDR used on desktop cards, which is why they generate tokens considerably faster at the same capacity.
Who makes the Switch 2 GPU?
The Switch 2 GPU is a NVIDIA product, with the chip manufactured by Samsung, on a 8 nm process.
When was the Switch 2 GPU released?
The Switch 2 GPU was released in June 2025.
How much power does a Switch 2 GPU use?
The Switch 2 GPU has a rated board power of 40 W. Generating text draws hard in bursts and idles between requests, so average consumption over a working session is normally well below the rated figure.
The other direction
Looking at it from the other side?
This page starts from the hardware. If you already know which model you want and need to know what it takes to run it, start from the model instead.