Can an RTX 5070 Ti run Qwen3 30B A3B?

Yes

At Q3_K_M it needs 14.84 GB of the 15.2 GB available and generates around 170 tokens per second at an 8k context window.

In practice

It fits, with very little to spare. Qwen3 30B A3B at Q3_K_M needs 14.84 GB and the GeForce RTX 5070 Ti offers 15.2 GB, a margin of 0.36 GB. That is enough to load it and run at about 170 tokens per second, and not enough to be relaxed about.

Three things take the margin away. A longer window is the first: at 16k the cache alone grows by 0.75 GB. Another program holding VRAM is the second, since a browser with hardware acceleration can take a gigabyte. And a runtime that places layers conservatively is the third, which Ollama does. Store the cache at 8 bits and close the other programs before you load it, and go down one quantization if it still will not.

Reading a 4,000-token prompt, roughly a long email or a few pages of text, takes under a second before the first word appears. That part is limited by compute and not by bandwidth, so it follows a different spec from the writing speed.

The numbers

Qwen3 30B A3B has 30.53 billion parameters across 48 layers, of which 3.34 billion are read for each token. The GeForce RTX 5070 Ti has 16 GB of VRAM at 896 GB/s, of which about 15.2 GB is left for a model once the operating system has taken its share.

QuantizationTotal neededFitsSpeed
Q8_0 30.99 GB experts in RAM 24.9 t/s
Q6_K 24.17 GB experts in RAM 39.6 t/s
Q5_K_M 21.11 GB experts in RAM 53.8 t/s
Q4_K_M 18.08 GB experts in RAM 83.6 t/s
IQ4_XS 16.04 GB experts in RAM 133 t/s
Q3_K_M 14.84 GB yes 170 t/s
IQ3_XXS degraded 11.85 GB yes 198 t/s
Q2_K degraded 12.87 GB yes 188 t/s
IQ2_XXS degraded 8.34 GB yes 248 t/s

4 of the 9 levels fit entirely. Levels marked degraded are listed for completeness, not as advice. Rows marked partial or experts in RAM run with part of the model in system RAM, at the speed shown.

How long a conversation it holds

Memory rises with the length of the conversation because the attention cache keeps a key and a value for every token. At Q3_K_M, the longest window that still fits on this device is 8k tokens.

ContextCacheTotalFits
4k 0.38 GB 14.47 GB yes
8k 0.75 GB 14.84 GB yes
16k 1.5 GB 15.59 GB no
32k 3 GB 17.09 GB no

The settings we would use

llama-server -m <model>.gguf -ngl all -c 8192 -fa on -ctk q8_0 -ctv q8_0

The cache is stored at 8 bits because headroom is under 1 GB. That halves it for a small quality cost.

In Ollama, set OLLAMA_CONTEXT_LENGTH to the window you want, run ollama ps while the model is loaded and check that the processor column reads 100% GPU. If it shows a split on a model that fits, the Ollama guide shows how to fix it. The llama.cpp flags guide explains each option above.

What else an RTX 5070 Ti runs well

For comparison, these are the other popular models that fit this device at a sound quantization, best pairings first.

ModelQuantizationMemorySpeed
Qwen3.5 27B IQ4_XS 14.2 GB 47.9 t/s
Gemma 4 12B Instruct Q8_0 13.55 GB 50.1 t/s
GPT OSS 20B MXFP4 11.55 GB 160 t/s
Qwen3 14B Q6_K 12.38 GB 55.2 t/s

The same model on nearby hardware

Memory decides whether Qwen3 30B A3B loads and bandwidth decides how quickly it answers. Here is what a step down, a card with the same memory and a step up do with it.

DeviceMemoryBandwidthResult
GeForce RTX 4070 12 GB 504 GB/s partial, 42.1 t/s
GeForce RTX 5080 16 GB 960 GB/s Q3_K_M, 182 t/s
GeForce RTX 4090 24 GB 1008 GB/s Q5_K_M, 146 t/s

See how fast it feels

GeForce RTX 5070 Ti running Qwen3 30B A3B at Q3_K_M

Wait for the first word51 ms
Then writes at169.6 tok/s
Whole answer1.1 s

YouWhy does my model use more memory when the conversation gets longer?

Model

Simulated from our estimate at a 512-token question, not a recording. Assumes nothing else is competing for the GPU.

Questions people ask

How much VRAM does Qwen3 30B A3B need on RTX 5070 Ti?

At Q4_K_M with an 8k context window it needs 18.08 GB in total: 16.99 GB of weights, 0.75 GB of KV cache and 0.34 GB of runtime overhead. The GeForce RTX 5070 Ti makes about 15.2 GB available once the operating system has taken its share.

What context length can RTX 5070 Ti handle with Qwen3 30B A3B?

At Q3_K_M the longest window that still fits is about 8k tokens. Memory grows with the window, so a shorter one leaves room for a higher quantization.

How fast is Qwen3 30B A3B on RTX 5070 Ti?

We estimate about 170 tokens per second at Q3_K_M, which is faster than most people read. A 500-token answer takes about 3 seconds. Memory bandwidth of 896 GB/s sets that ceiling, and the estimate is good to about 10 to 30 percent.

Keep going

Everything the GeForce RTX 5070 Ti runs, the full breakdown for Qwen3 30B A3B, how the numbers are made in the methodology, or a different pairing in the calculator.