Can I run DeepSeek R1 Distill Qwen 14B on an RTX 4060 Ti 16GB?
Key facts
Yes. DeepSeek R1 Distill Qwen 14B runs on an RTX 4060 Ti 16GB, about 21 tokens per second (tok/s).
It needs about 11.4 GB at standard quality (estimate). Checked . unsloth Q4_K_M GGUF.
The cheapest graphics card on our list that holds it at Q4 is the Radeon RX 9060 XT 16GB. On an RTX 4060 Ti 16GB, at 32,768 tokens of context, it does not fit (estimate).
How much memory it needs
It uses about 74% of the memory that is free on this card. A longer conversation of about 49 pages of text (32,768 tokens) would not fit.
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What an RTX 4060 Ti 16GB costs
GeForce RTX 4060 Ti 16GB$832€899new (lowest in-stock EU)
EU shops · Shown to visitors in Europe.US shops · Shown to visitors outside Europe.
We never pass off an estimate as a benchmark. Commissions never change which hardware we recommend. How we calculate
Price details
$832€899
How we priced this
New price, the lowest in stock in the EU.
Source: GPU PRIX, checked 16 Oct 2026.
Lowest new price in stock on 16 Oct 2026: €899, an MSI Gaming X Slim 16GB from the Netherlands. Over the past 3 months the typical price was €629.
Prices excl. shipping unless marked. Euro prices incl. VAT where the seller charges it. Dollar prices are converted from our euro prices without the 21% EU VAT, before US sales tax.
The cheapest graphics card on our list that also runs it (it still needs the rest of a PC): Radeon RX 9060 XT 16GB, $522€564, new (cheapest in-stock board on GPU PRIX's German board list). Fast~23 tok/s
A complete machine that runs it at least as fast as you read: Mac Studio M4 Max 36GB, about $2,116€1,890 (used). Comfortable~18.5 tok/s
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DeepSeek R1 Distill Qwen 14B on other graphics cards
Runs well9
The whole model fits in the graphics memory.
Doesn't fit1
Not enough graphics memory: it needs about 11.4 GB.
- RTX 3060 12GBhas 12 GB
More about the model itself, what it is good at and its licence: DeepSeek R1 Distill Qwen 14B.
The numbers behind this answer
A model comes in several sizes. Q4 is the standard one most people use; the bigger ones answer a little better but need more memory. Each row adds up the model file, the memory a conversation takes, and some working space, and compares the total with what is free on this card.
Swipe the table sideways to see every column.
| Quality | Conversation | Result | Speed | Model file | Conversation memory | Working space | Total needed | Free memory |
|---|---|---|---|---|---|---|---|---|
| Q4 · standard (smallest that keeps quality) | ~12 pages8,192 tokens | Runs | Fast~21 tok/s | 9.0 GBmeasured file | 1.6 GB | 0.8 GB | 11.4 GB | 15.4 GB |
| Q5 · a bit sharper, a bit bigger | ~12 pages8,192 tokens | Runs | Comfortable~18.5 tok/s | 10.5 GB | 1.6 GB | 0.8 GB | 12.9 GB | 15.4 GB |
| Q8 · near full quality, almost twice Q4 | ~12 pages8,192 tokens | Doesn't fit | — | 15.8 GB | 1.6 GB | 0.8 GB | 18.2 GB | 15.4 GB |
| FP16 · full quality, over three times Q4 | ~12 pages8,192 tokens | Doesn't fit | — | 29.5 GB | 1.6 GB | 0.8 GB | 32.0 GB | 15.4 GB |
| Q4 · standard, longer conversation | ~49 pages32,768 tokens | Doesn't fit | — | 9.0 GBmeasured file | 6.4 GB | 0.8 GB | 16.2 GB | 15.4 GB |
Sources and method
Memory and speed on this page are our estimate, not a measured test. Checked . unsloth Q4_K_M GGUF.
DeepSeek's dense reasoning distill of DeepSeek-R1 onto Qwen2.5-14B, MIT licence. Hugging Face safetensors metadata lists 14,770,033,664 parameters (14.77B). 48 layers, 8 KV heads, head dim 128, context 131,072. The Q4_K_M GGUF is 8.99 GB (unsloth, 24 Oct 2026). At 8,192 tokens the rounded parts are 8.99 GB weights + 1.61 GB conversation memory + 0.80 GB working space = 11.40 GB, which equals the 11.4 GB usable line of a 12 GB card. The unrounded sum is a fraction over 11.4 GB, so the fit table does not mark Q4 as a full fit on 12 GB. IQ4_XS is an 8.12 GB file, about 10.53 GB in total at 8,192 tokens (our estimate), and that fits a 12 GB card. Only the 2-bit IQ2_XS file (4.70 GB, about 7.11 GB in total) fits an 8 GB card (about 7.4 GB usable). Ollama tag: deepseek-r1:14b.
Measured DeepSeek R1 Distill Qwen 14B on an RTX 4060 Ti 16GB yourself? Send us your llama-bench result.
Questions
- Can I run DeepSeek R1 Distill Qwen 14B on an RTX 4060 Ti 16GB?
- Yes. DeepSeek R1 Distill Qwen 14B runs on an RTX 4060 Ti 16GB, about 21 tokens per second (tok/s).
- How much memory does DeepSeek R1 Distill Qwen 14B need?
- About 11.4 GB at the standard quality (Q4) for a conversation of up to about 12 pages of text (8,192 tokens), by our estimate: 9.0 GB for the model file (measured), 1.6 GB to hold the conversation and 0.8 GB of working space.
- How fast is DeepSeek R1 Distill Qwen 14B on an RTX 4060 Ti 16GB?
- Fast: about 21 tokens per second (tok/s). Answers appear faster than you can read them. This is our estimate, not a measured test.
Speeds and memory are our estimate from the hardware specs, not a measured test. Prices are dated and may change. How we calculate