Can I run Qwen3.6-35B-A3B on an RX 9060 XT 16GB?
Key facts
No: it needs about 23 GB and this card has 16 GB of graphics memory.
It needs about 23.1 GB at standard quality (estimate). Checked . unsloth UD-Q4_K_M GGUF.
Updated · Qwen3.6-35B-A3B on every card
How much memory it needs
That is about 1.5 times what this card has free.
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Get a 1-line alert when a new open-weight model fits 24 GB VRAM (23.1 GB at Q4 for Qwen3.6-35B-A3B) or when used RTX 3090 / 4090 & Mac Studio prices drop >10% — weekly, zero spam.
What runs Qwen3.6-35B-A3B instead
The cheapest graphics card on our list that holds the whole model (it still needs the rest of a PC):
GeForce RTX 3090 24GB$1,395€1,246used (median of sold listings)
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
$1,395€1,246
How we priced this
Used price, the typical price of second-hand cards that actually sold.
Source: pcprice.watch, checked 24 Oct 2026.
New price, the lowest in stock in the EU: $2,052€2,218 at GPU PRIX, 16 Oct 2026. A Zotac Trinity OC from France.
Used median €1,246 (typical €1,136–€1,334) from 235 cards sold on eBay in the past 90 days, recorded 24 Oct 2026. pcprice.watch refreshed that page on 23 Oct 2026. Not an EU shop price.
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.
A complete machine that runs it: Mac Studio M4 Max 36GB, about $2,116€1,890 (used).
See our picks for Qwen3.6-35B-A3B in Find hardware. Add your budget to see cheaper machines.
For comparison, an RX 9060 XT 16GB costs $522€564, new (cheapest in-stock board on GPU PRIX's German board list). Card details
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Qwen3.6-35B-A3B on other graphics cards
Runs well6
The whole model fits in the graphics memory.
Doesn't fit4
Not enough graphics memory: it needs about 23.1 GB.
- RTX 3060 12GBhas 12 GB
- RTX 4060 Ti 16GBhas 16 GB
- RTX 5080has 16 GB
- RX 9060 XT 16GBhas 16 GB
More about the model itself, what it is good at and its licence: Qwen3.6-35B-A3B.
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 | Model file | Conversation memory | Working space | Total needed | Free memory |
|---|---|---|---|---|---|---|---|
| Q4 · standard (smallest that keeps quality) | ~12 pages8,192 tokens | Doesn't fit | 22.1 GBmeasured file | 0.2 GB | 0.8 GB | 23.1 GB | 15.4 GB |
| Q5 · a bit sharper, a bit bigger | ~12 pages8,192 tokens | Doesn't fit | 25.5 GB | 0.2 GB | 0.8 GB | 26.5 GB | 15.4 GB |
| Q8 · near full quality, almost twice Q4 | ~12 pages8,192 tokens | Doesn't fit | 38.5 GB | 0.2 GB | 0.8 GB | 39.4 GB | 15.4 GB |
| FP16 · full quality, over three times Q4 | ~12 pages8,192 tokens | Doesn't fit | 71.9 GB | 0.2 GB | 0.8 GB | 72.9 GB | 15.4 GB |
| Q4 · standard, longer conversation | ~49 pages32,768 tokens | Doesn't fit | 22.1 GBmeasured file | 0.7 GB | 0.8 GB | 23.6 GB | 15.4 GB |
speed: not estimated for MoE yet. This model only uses part of itself for each word (a mixture of experts), and our speed estimate does not handle that yet.
Sources and method
Memory and speed on this page are our estimate, not a measured test. Checked . unsloth UD-Q4_K_M GGUF.
Mixture-of-experts vision-language model, Apache-2.0. The card says 35B in total and 3B activated. Hugging Face safetensors metadata lists 35,951,822,704 parameters, all BF16. 35.95B is that count to two decimals, and 3B active is the card's round figure, so our parameter count is an estimate. Our memory estimate uses the total. 256 experts, 8 routed per token in the config. The card adds 1 shared expert. 40 layers: 30 linear_attention (Gated DeltaNet) and 10 full_attention (Gated Attention). 16 query heads, 2 KV heads, head dim 256. Linear-attention layers are stored with a sliding window of 0 so our estimate gives them no conversation memory. The conversation-memory figure uses only the 10 full-attention layers and is an FP16 estimate. Config max_position_embeddings is 262,144. The card says that window is extensible to 1,010,000 tokens; we use 262,144. The card's citation is April 2026. Hugging Face lists the repo as created on 15 April 2026. Speed is not estimated: our speed estimate reads every weight for each token and would understate a sparse MoE, so we show no speed figure. Unsloth GGUF sizes, decimal GB, checked 24 Oct 2026 (https://huggingface.co/unsloth/Qwen3.6-35B-A3B-GGUF): UD-Q3_K_XL 16.85, UD-IQ4_XS 17.73, MXFP4_MOE 21.71, UD-Q4_K_M 22.13, UD-Q4_K_XL 22.36, Q8_0 36.90. Q8_0 is 36,903,140,320 bytes. mmproj-F16 is 0.90 GB (899,283,680 bytes) and is not a row in the memory table.
Questions
- Can I run Qwen3.6-35B-A3B on an RX 9060 XT 16GB?
- No: it needs about 23 GB and this card has 16 GB of graphics memory.
- How much memory does Qwen3.6-35B-A3B need?
- About 23.1 GB at the standard quality (Q4) for a conversation of up to about 12 pages of text (8,192 tokens), by our estimate: 22.1 GB for the model file (measured), 0.2 GB to hold the conversation and 0.8 GB of working space.
- How fast is Qwen3.6-35B-A3B on an RX 9060 XT 16GB?
- We don't give a speed for this model yet. This model only uses part of itself for each word (a mixture of experts), and our speed estimate does not handle that yet.
Speeds and memory are our estimate from the hardware specs, not a measured test. Prices are dated and may change. How we calculate