AMD Radeon RX 9060 XT 16GB
16 GB · 320 GB/s · 160 W
In short
The AMD Radeon RX 9060 XT 16GB has 16 GB of GDDR6 memory with 320 GB/s of bandwidth, which sets how fast it generates text. At 32k context it runs 29 of the 113 open models we track fully in memory; the most capable is gpt-oss 20B at MXFP4, at about 33 tok/s (estimated). The best new price for the AMD Radeon RX 9060 XT 16GB in Canada is $800 at Amazon; used, it starts at $665 (asking price).
Updated . Speeds are estimates; how they are worked out.
Prices
Every retailer we track in Canada, cheapest first. Buy links may earn us a commission.
| Retailer | Condition | Price | Stock | Checked | Buy |
|---|---|---|---|---|---|
| eBayGigabyte Radeon RX 9060 XT Gaming OC 16GB | used, asking price | $665 | In stock | 2 h ago | Buy |
| AmazonSapphire Pulse AMD Radeon RX 9060 XT 16GB GDDR6 Gaming GPU | New | $800 | In stock | 5 h ago | Buy |
| AmazonSapphire Pure AMD Radeon RX 9060 XT 16GB GDDR6 Gaming GPU | New | $820 | In stock | 26 min ago | Buy |
| AmazonASUS AMD Dual Radeon RX 9060 XT 16GB GDDR6 Video Card DUAL-RX9060XT-16G | New | $900 | In stock | 26 min ago | Buy |
| AmazonASUS Dual Radeon RX 9060 XT 16GB GDDR6 Gaming Graphics Card | New | $937 | In stock | 35 min ago | Buy |
| AmazonXFX Swift AMD Radeon RX 9060 XT OC Triple Fan Gaming Edition with 16GB GDDR6… | New | $968 | In stock | 26 min ago | Buy |
| AmazonASUS Prime Radeon RX 9060 XT 16GB GDDR6 OC Edition Gaming Graphics Card | New | $980 | In stock | 35 min ago | Buy |
| AmazonSapphire Technology Nitro+ AMD Radeon RX 9060 XT Gaming OC | New | $1,000 | In stock | 26 min ago | Buy |
| AmazonGigabyte Radeon RX 9060 XT Gaming OC 16G Graphics Card | New | $1,100 | In stock | 26 min ago | Buy |
| AmazonASUS Dual Radeon RX 9060 XT 16GB GDDR6 White Edition | New | $1,140 | In stock | 26 min ago | Buy |
| AmazonASUS AMD Radeon RX 9060 XT Video Card 16GB GDDR6 OC Edition… | New | $2,181 | In stock | 21 min ago | Buy |
Price history
Lowest price shown each day over the last 90 days.
Not enough price history yet.
What it runs
Every model in the catalogue, with the best quant for this hardware. Estimates, not measurements.
| Model | Quant | Fits | Memory | Max context | Decode @32k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| gpt-oss 20B OpenAI | MXFP4 | fits | 13.0 GB | 106k128k with q8 cache | 33tok/sest. | 3099 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 13.6 GB | 106k171k with q8 cache | 13tok/sest. | 1348 tok/s | – |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 10.9 GB | 147k243k with q8 cache | 17tok/sest. | 1680 tok/s | chat |
| Qwen3 14B Alibaba Qwen | Q4_K_M | fits | 14.4 GB | 37k40k with q8 cache | 12tok/sest. | 839 tok/s | chat |
| Ministral 3 14B Mistral AI | Q5_K_M | fits | 14.9 GB | 33k61k with q8 cache | 12tok/sest. | 933 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 13.6 GB | 42k78k with q8 cache | 13tok/sest. | 1384 tok/s | chat |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 13.6 GB | 40k | 13tok/sest. | 1384 tok/s | chat |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 6.2 GB | 256k | 31tok/sest. | 3144 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 13.6 GB | 43k78k with q8 cache | 13tok/sest. | 1337 tok/s | chat |
| Granite 4.2 8B IBM | Q8_0 | fits | 14.7 GB | 35k64k with q8 cache | 12tok/sest. | 1273 tok/s | chat |
| Gemma 4 E4B | Q8_0 | fits | 9.5 GB | 128k | 19tok/sest. | 2111 tok/s | chat |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 10.9 GB | 113k125k with q8 cache | 40tok/sest. | 6905 tok/s | chat, coding |
| Llama 3.1 8B Meta | Q6_K | fits | 11.1 GB | 63k114k with q8 cache | 16tok/sest. | 1462 tok/s | chat |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.9 GB | 32k | 189tok/sest. | 15037 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.1 GB | 256k | 143tok/sest. | 14125 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.7 GB | 256k | 95tok/sest. | 6734 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 3.6 GB | 128k | 62tok/sest. | 5657 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 4.8 GB | 128k | 43tok/sest. | 3378 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 5.5 GB | 128k | 36tok/sest. | 3827 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 5.5 GB | 32k | 36tok/sest. | 3509 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 13.5 GB | 118k128k with q8 cache | 33tok/sest. | 4985 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Moonshot AI | mlx-6bit | fits | 14.8 GB | 42k70k with q8 cache | 30tok/sest. | 3746 tok/s | chat, coding |
| granite vision 4.1 4b IBM | Q8_0 | fits | 6.9 GB | 128k | 28tok/sest. | 2452 tok/s | chat, coding |
| granite 4.2 3b IBM | Q8_0 | fits | 7.1 GB | 128k | 27tok/sest. | 2569 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 10.3 GB | 113k128k with q8 cache | 18tok/sest. | 1653 tok/s | chat |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 11.6 GB | 113k128k with q8 cache | 16tok/sest. | 1151 tok/s | chat |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 12.9 GB | 49k89k with q8 cache | 14tok/sest. | 1462 tok/s | chat |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 13.2 GB | 64k | 13tok/sest. | 1151 tok/s | – |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 13.6 GB | 43k78k with q8 cache | 13tok/sest. | 1337 tok/s | chat |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 18.5 GB | – | 7tok/sest. | 516 tok/s | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 40.8 GB | – | 10tok/sest. | 837 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 18.8 GB | – | 6tok/sest. | 511 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 21.3 GB | – | 5tok/sest. | 424 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.1 GB | – | 14tok/sest. | 945 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 21.9 GB | – | 24tok/sest. | 3354 tok/s | chat, coding |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 18.7 GB | – | 6tok/sest. | 512 tok/s | – |
| Gemma 4 26B-A4B | UD-Q4_K_M | offload | 17.6 GB | – | 23tok/sest. | 3374 tok/s | chat, coding |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 22.2 GB | – | 24tok/sest. | 3331 tok/s | chat, coding |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 19.7 GB | – | 14tok/sest. | 1855 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 6tok/sest. | 531 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 33.8 GB | – | 13tok/sest. | 3125 tok/s | – |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.3 GB | – | 23tok/sest. | 2510 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 21.3 GB | – | 13tok/sest. | 1566 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 27.4 GB | – | 3tok/sest. | 261 tok/s | – |
| Gemma 3 27B | Q4_K_M | offload | 19.3 GB | – | 6tok/sest. | 534 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 6tok/sest. | 531 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 27.5 GB | – | 3tok/sest. | 299 tok/s | – |
| Phi-4 14B Microsoft | Q4_K_M | offload | 15.5 GB | 16k | 11tok/sest. | 832 tok/s | chat |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 17.8 GB | 1k2k with q8 cache | 20tok/sest. | 3493 tok/s | chat |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | offload | 15.4 GB | 31k57k with q8 cache | 11tok/sest. | 785 tok/s | chat |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 6tok/sest. | 539 tok/s | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 6tok/sest. | 539 tok/s | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 6tok/sest. | 539 tok/s | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 6tok/sest. | 531 tok/s | – |
| granite 4.2 30b IBM | Q4_K_M | offload | 25.8 GB | – | 3tok/sest. | 354 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 93.9 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.7 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 75.3 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 78.9 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.3 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 47.0 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 60.6 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 48.9 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 47.0 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 50.6 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 379.8 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 380.3 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 50.6 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 379.8 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 380.7 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 380.7 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 149.3 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 158.1 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q8_0 | won't run | 135.7 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 66.0 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 72.3 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 214.1 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 423.7 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 437.6 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 750.1 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 581.3 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 581.7 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 581.7 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 581.7 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 137.6 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 137.6 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 124.0 GB | – | – | – | – |
| MiniMax M3 MiniMax | UD-Q4_K_M | won't run | 251.5 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 81.7 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- Radeon RX 9060 XT 16GB
- Memory
- 16 GB GDDR6
- Memory bus
- 128-bit
- Memory bandwidth
- 320 GB/s
- FP16 compute
- 103 TFLOPS
- Software
- ROCm
- Board power
- 160 W
- PCIe generation
- Gen 5
- PCIe lanes
- x16
Compare with
Questions
- How much memory does the AMD Radeon RX 9060 XT 16GB have for AI models?
- The AMD Radeon RX 9060 XT 16GB has 16 GB of GDDR6 memory with 320 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the AMD Radeon RX 9060 XT 16GB can run locally?
- gpt-oss 20B (MXFP4) fits fully in its memory at 32k context and generates at about 33 tok/s, an estimate from its memory bandwidth. 29 of the 113 models we track fit at that context.
- Can the AMD Radeon RX 9060 XT 16GB run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 94 GB at 32k context, more than the AMD Radeon RX 9060 XT 16GB and system RAM can hold.
- How much does the AMD Radeon RX 9060 XT 16GB cost in Canada?
- The best new price for the AMD Radeon RX 9060 XT 16GB in Canada is $800 at Amazon; used, it starts at $665 (asking price).
Speeds on this page are for 32k context. See the best hardware for local AI at every budget.