Can an RTX 3070 run Qwen3 14B?
Barely
It only loads at IQ3_XXS, which compresses the weights far enough to visibly degrade the model, so we would not call that running it.
In practice
It loads, and we would not call that running it. The only quantization that fits the GeForce RTX 3070 is IQ3_XXS, which compresses the weights far enough that Qwen3 14B loses a visible amount of its ability, so we do not recommend it. At Q4_K_M it needs 9.56 GB against the 7.2 GB available.
Running it properly means a split with system RAM: at Q4_K_M about 29 of 40 layers fit on the card, and the estimate falls to 9.6 tokens per second. A smaller model at a proper quantization is a better answer than a larger one squeezed in, and the next section lists the ones that fit.
The numbers
Qwen3 14B has 14.77 billion parameters across 40 layers. The GeForce RTX 3070 has 8 GB of VRAM at 448 GB/s, of which about 7.2 GB is left for a model once the operating system has taken its share.
| Quantization | Total needed | Fits | Speed |
|---|---|---|---|
| Q8_0 | 15.54 GB | partial | 3.2 t/s |
| Q6_K | 12.38 GB | partial | 5.0 t/s |
| Q5_K_M | 10.96 GB | partial | 6.6 t/s |
| Q4_K_M | 9.56 GB | partial | 9.6 t/s |
| IQ4_XS | 8.61 GB | partial | 14.7 t/s |
| Q3_K_M | 8.06 GB | partial | 19.2 t/s |
| IQ3_XXS degraded | 6.67 GB | yes | 52.9 t/s |
| Q2_K degraded | 7.15 GB | yes | 49.1 t/s |
| IQ2_XXS degraded | 5.05 GB | yes | 71.6 t/s |
3 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.
What to run instead
A smaller model from the same family is the straightforward answer. These fit on an RTX 3070 at a quantization worth using:
- Qwen3.5 9B, 9.65B at Q5_K_M, 6.42 GB, about 54.8 tokens/s
- Qwen2.5 VL 7B Instruct, 8.29B at Q6_K, 6.74 GB, about 51.9 tokens/s
- Qwen3 8B, 8.19B at Q5_K_M, 6.54 GB, about 53.7 tokens/s
Shortening the context will not rescue this one: at 4k it still wants 8.93 GB against 9.56 GB at 8k, because the weights, not the cache, are what fill the card.
Or the hardware that does run it
The cheapest device we track that runs Qwen3 14B at a quantization worth using is the GeForce RTX 2060 12GB, around $160 used , running it at Q5_K_M at about 23.5 tokens per second. Check the current price (affiliate link, indicative price reviewed 2026-09-01). Compare every option.
What else an RTX 3070 runs well
For comparison, these are the other popular models that fit this device at a sound quantization, best pairings first.
| Model | Quantization | Memory | Speed |
|---|---|---|---|
| Qwen3.5 9B | Q5_K_M | 6.42 GB | 54.8 t/s |
| Qwen3 8B | Q5_K_M | 6.54 GB | 53.7 t/s |
| Qwen2.5 7B Instruct | Q6_K | 6.23 GB | 56.4 t/s |
| Llama 3.1 8B Instruct | Q6_K | 7.14 GB | 49.0 t/s |
The same model on nearby hardware
Memory decides whether Qwen3 14B 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.
| Device | Memory | Bandwidth | Result |
|---|---|---|---|
| GeForce RTX 3050 6GB | 6 GB | 168 GB/s | does not fit |
| GeForce RTX 4060 | 8 GB | 272 GB/s | does not fit |
| GeForce RTX 4070 | 12 GB | 504 GB/s | Q5_K_M, 35.3 t/s |
Questions people ask
How much VRAM does Qwen3 14B need on RTX 3070?
At Q4_K_M with an 8k context window it needs 9.56 GB in total: 7.87 GB of weights, 1.25 GB of KV cache and 0.44 GB of runtime overhead. The GeForce RTX 3070 makes about 7.2 GB available once the operating system has taken its share.
What should I run instead of Qwen3 14B on RTX 3070?
Qwen3.5 9B fits at Q5_K_M and runs at about 54.8 tokens per second. Smaller models from the same family are the usual answer.
Keep going
Everything the GeForce RTX 3070 runs, the full breakdown for Qwen3 14B, how the numbers are made in the methodology, or a different pairing in the calculator.