AMD Radeon RX 7900 XTX
24 GB · 960 GB/s · 355 W
In short
The AMD Radeon RX 7900 XTX has 24 GB of GDDR6 memory with 960 GB/s of bandwidth, which sets how fast it generates text. At 64k context it runs 40 of the 113 open models we track fully in memory; the most capable is Qwen 3.8 27B at Q4_K_M, at about 24 tok/s (estimated). The AMD Radeon RX 7900 XTX is not on sale new in Canada right now; used, it starts at $2,500 (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 |
|---|---|---|---|---|---|
| eBayASUS TUF Gaming Radeon RX 7900 XTX OC Edition 24GB | used, asking price | $2,500 | In stock | 2 h ago | Buy |
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 @64k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q4_K_M | fits | 21.6 GB | 87k153k with q8 cache | 24tok/sest. | 629 tok/s | chat, coding |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | fits | 21.0 GB | 96k168k with q8 cache | 25tok/sest. | 629 tok/s | chat, coding |
| Qwen 3.6 35B-A3B Alibaba Qwen | UD-Q4_K_M | fits | 23.1 GB | 68k106k with q8 cache | 97tok/sest. | 3787 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | fits | 20.9 GB | 97k170k with q8 cache | 25tok/sest. | 629 tok/s | chat, coding |
| Gemma 4 26B-A4B | UD-Q5_K_M | fits | 22.3 GB | 98k160k with q8 cache | 66tok/sest. | 3877 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | fits | 23.0 GB | 72k113k with q8 cache | 98tok/sest. | 3787 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q4_K_M | fits | 21.5 GB | 92k160k with q8 cache | 48tok/sest. | 1879 tok/s | chat, coding, agents, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 14.0 GB | 128k | 78tok/sest. | 2898 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 14.3 GB | 256k | 38tok/sest. | 1490 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 12.1 GB | 256k | 45tok/sest. | 1824 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q4_K_M | fits | 22.0 GB | 78k128k with q8 cache | 24tok/sest. | 705 tok/s | chat, coding |
| Ministral 3 14B Mistral AI | Q6_K | fits | 21.5 GB | 74k135k with q8 cache | 24tok/sest. | 872 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q6_K | fits | 22.5 GB | 40k | 23tok/sest. | 764 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 18.3 GB | 97k128k with q8 cache | 29tok/sest. | 1206 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 18.3 GB | 40k | 29tok/sest. | 1206 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q4_K_M | fits | 22.0 GB | 16k | 24tok/sest. | 767 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.4 GB | 256k | 79tok/sest. | 3162 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 18.1 GB | 100k183k with q8 cache | 29tok/sest. | 1193 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q8_0 | fits | 19.9 GB | 84k128k with q8 cache | 26tok/sest. | 1102 tok/s | chat, coding, agents |
| Gemma 4 E4B | Q8_0 | fits | 10.6 GB | 128k | 52tok/sest. | 2389 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 12.6 GB | 125k | 74tok/sest. | 5099 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 15.3 GB | 124k128k with q8 cache | 35tok/sest. | 1295 tok/s | chat, coding, long documents |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.4 GB | 32k | 395tok/sest. | 11309 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.7 GB | 256k | 323tok/sest. | 12822 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.3 GB | 256k | 234tok/sest. | 6990 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 4.7 GB | 128k | 140tok/sest. | 4684 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 6.3 GB | 128k | 96tok/sest. | 2640 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 14.1 GB | 128k | 87tok/sest. | 4725 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 7.6 GB | 128k | 77tok/sest. | 3201 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 7.6 GB | 32k | 77tok/sest. | 3011 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 19.7 GB | 128k | 60tok/sest. | 3250 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 9.5 GB | 128k | 59tok/sest. | 2010 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 9.8 GB | 128k | 57tok/sest. | 2076 tok/s | chat, coding, agents, long documents |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | fits | 20.5 GB | 96k128k with q8 cache | 48tok/sest. | 2921 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 12.2 GB | 128k | 45tok/sest. | 1517 tok/s | chat, coding, long documents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 13.0 GB | 128k | 42tok/sest. | 1024 tok/s | chat, coding, agents, long documents |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 14.6 GB | 64k | 37tok/sest. | 1024 tok/s | chat, coding, long documents |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 17.1 GB | 110k128k with q8 cache | 31tok/sest. | 1295 tok/s | chat, coding |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 18.1 GB | 100k183k with q8 cache | 29tok/sest. | 1193 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q5_K_M | fits | 23.0 GB | 65k119k with q8 cache | 23tok/sest. | 697 tok/s | chat, coding |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 41.8 GB | – | 12tok/sest. | 950 tok/s | chat |
| Gemma 4 31B | Q4_K_M | offload | 24.0 GB | 54k103k with q8 cache | 16tok/sest. | 562 tok/s | chat, coding |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 47.9 GB | – | 14tok/sest. | 2071 tok/s | chat |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 40.0 GB | – | 17tok/sest. | 953 tok/s | chat, coding |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 47.9 GB | – | 16tok/sest. | 2362 tok/s | chat, coding |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 24.5 GB | 55k101k with q8 cache | 14tok/sest. | 598 tok/s | chat, coding |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 34.2 GB | – | 21tok/sest. | 3736 tok/s | chat, coding, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.7 GB | – | 44tok/sest. | 2626 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 24.5 GB | 51k91k with q8 cache | 26tok/sest. | 1311 tok/s | chat, coding, agents |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 35.6 GB | 15k28k with q8 cache | 3tok/sest. | 252 tok/s | chat |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 24.5 GB | 55k101k with q8 cache | 14tok/sest. | 598 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 35.7 GB | 15k28k with q8 cache | 3tok/sest. | 311 tok/s | chat |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 24.5 GB | 55k101k with q8 cache | 14tok/sest. | 606 tok/s | chat, coding |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 24.5 GB | 40k | 14tok/sest. | 606 tok/s | chat, coding |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 24.5 GB | 40k | 14tok/sest. | 606 tok/s | chat, coding |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 24.5 GB | 55k101k with q8 cache | 14tok/sest. | 598 tok/s | chat, coding |
| granite 4.2 30b IBM | Q4_K_M | offload | 34.0 GB | 21k40k with q8 cache | 4tok/sest. | 372 tok/s | chat |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 96.7 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 103.2 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 76.2 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 86.8 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.7 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 61.9 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 54.9 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 60.8 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 382.1 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 382.6 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 60.8 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 382.1 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 383.0 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 383.0 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 152.2 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 161.0 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q8_0 | won't run | 146.9 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 71.9 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 78.3 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 225.8 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 426.6 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 440.5 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 753.0 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 583.6 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 584.0 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 584.0 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 584.0 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 145.5 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 145.5 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 131.9 GB | – | – | – | – |
| MiniMax M3 MiniMax | UD-Q4_K_M | won't run | 255.4 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 92.9 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- Radeon RX 7900 XTX
- Memory
- 24 GB GDDR6
- Memory bus
- 384-bit
- Memory bandwidth
- 960 GB/s
- FP16 compute
- 123 TFLOPS
- Software
- ROCm
- Board power
- 355 W
- PCIe generation
- Gen 4
- PCIe lanes
- x16
Compare with
Questions
- How much memory does the AMD Radeon RX 7900 XTX have for AI models?
- The AMD Radeon RX 7900 XTX has 24 GB of GDDR6 memory with 960 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the AMD Radeon RX 7900 XTX can run locally?
- Qwen 3.8 27B (Q4_K_M) fits fully in its memory at 64k context and generates at about 24 tok/s, an estimate from its memory bandwidth. 40 of the 113 models we track fit at that context.
- Can the AMD Radeon RX 7900 XTX run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 97 GB at 64k context, more than the AMD Radeon RX 7900 XTX and system RAM can hold.
- How much does the AMD Radeon RX 7900 XTX cost in Canada?
- The AMD Radeon RX 7900 XTX is not on sale new in Canada right now; used, it starts at $2,500 (asking price).
Speeds on this page are for 64k context. See the best hardware for local AI at every budget.