AMD Radeon RX 9070
16 GB · 640 GB/s · 220 W
In short
The AMD Radeon RX 9070 has 16 GB of GDDR6 memory with 640 GB/s of bandwidth, which sets how fast it generates text. At 64k context it runs 58 of the 125 open models we track fully in memory; the most capable is Qwen 3.8 27B at Q6_K, at about 12 tok/s (estimated). The best new price for the AMD Radeon RX 9070 in Canada is $1,074 at Amazon.
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 |
|---|---|---|---|---|---|
| AmazonPowerColor Hellhound AMD Radeon RX 9070 16GB GDDR6 | New | $1,074 | In stock | 3 h ago | Buy |
| AmazonASUS PRIME Radeon RX 9070 16GB GDDR6 OC Edition Gaming Graphics Card | New | $1,282+ $10 delivery | In stock | 3 h ago | Buy |
| AmazonGIGABYTE Radeon RX 9070 Gaming Graphics Card with 16GB GDDR6X | New | $1,354 | In stock | 2 h ago | Buy |
| AmazonSapphire Pulse AMD Radeon RX 9070 16GB GDDR6 Gaming GPU | New | $1,388 | In stock | 2 h ago | Buy |
| AmazonASUS PRIME Radeon RX 9070 EVO 16GB GDDR6 OC Edition Gaming Graphics Card | New | $1,420 | In stock | 3 h ago | Buy |
What two of them run
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 | Q6_K | fits | 28.0 GB | 98k172k with q8 cache | 12tok/sest. | 185 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q6_K | fits | 26.8 GB | 116k204k with q8 cache | 13tok/sest. | 185 tok/s | chat |
| Gemma 4 31B | Q5_K_M | fits | 27.6 GB | 97k179k with q8 cache | 13tok/sest. | 169 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | UD-Q6_K | fits | 30.3 GB | 68k107k with q8 cache | 55tok/sest. | 1111 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q6_K | fits | 26.7 GB | 117k206k with q8 cache | 13tok/sest. | 185 tok/s | chat |
| Gemma 4 26B-A4B | Q8_0 | fits | 28.1 GB | 153k245k with q8 cache | 37tok/sest. | 1138 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q6_K | fits | 29.9 GB | 85k133k with q8 cache | 55tok/sest. | 1111 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q6_K | fits | 28.0 GB | 106k183k with q8 cache | 28tok/sest. | 551 tok/s | chat, coding, agents, long documents |
| Devstral Small 2 24B Mistral AI | Q6_K | fits | 29.7 GB | 68k124k with q8 cache | 12tok/sest. | 182 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q5_K_M | fits | 30.2 GB | 78k101k with q8 cache | 64tok/sest. | 1370 tok/s | chat, coding, agents, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | fits | 30.2 GB | 78k107k with q8 cache | 88tok/sest. | 893 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 14.5 GB | 128k | 52tok/sest. | 851 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q5_K_M | fits | 27.9 GB | 89k159k with q8 cache | 25tok/sest. | 398 tok/s | chat, coding, agents |
| Gemma 4 12B | Q8_0 | fits | 14.8 GB | 256k | 25tok/sest. | 437 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 12.6 GB | 256k | 30tok/sest. | 535 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q6_K | fits | 27.7 GB | 95k128k with q8 cache | 13tok/sest. | 207 tok/s | chat |
| Mistral Small 3.2 24B Mistral AI | Q6_K | fits | 29.7 GB | 68k124k with q8 cache | 12tok/sest. | 182 tok/s | chat |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 25.0 GB | 97k176k with q8 cache | 14tok/sest. | 256 tok/s | chat |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 26.3 GB | 40k | 13tok/sest. | 224 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 18.8 GB | 128k | 19tok/sest. | 354 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 18.8 GB | 40k | 19tok/sest. | 354 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q8_0 | fits | 28.7 GB | 16k | 12tok/sest. | 225 tok/s | chat |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.9 GB | 256k | 53tok/sest. | 928 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 18.6 GB | 149k256k with q8 cache | 19tok/sest. | 350 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q8_0 | fits | 20.4 GB | 125k128k with q8 cache | 18tok/sest. | 324 tok/s | chat, coding |
| Gemma 4 E4B | Q8_0 | fits | 11.1 GB | 128k | 35tok/sest. | 701 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 13.1 GB | 125k | 49tok/sest. | 1497 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 15.8 GB | 128k | 23tok/sest. | 380 tok/s | chat, coding |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.9 GB | 32k | 263tok/sest. | 3319 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 3.2 GB | 256k | 215tok/sest. | 3763 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.8 GB | 256k | 156tok/sest. | 2052 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 5.2 GB | 128k | 93tok/sest. | 1375 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 6.8 GB | 128k | 64tok/sest. | 775 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 6.8 GB | 639k1024k with q8 cache | 64tok/sest. | 951 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 14.6 GB | 128k | 58tok/sest. | 1387 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 8.0 GB | 256k | 52tok/sest. | 928 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 8.1 GB | 128k | 51tok/sest. | 940 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 8.1 GB | 32k | 51tok/sest. | 884 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q8_0 | fits | 19.4 GB | 128k | 41tok/sest. | 954 tok/s | chat, coding, long documents |
| Kimi VL A3B Moonshot AI | mlx-8bit | fits | 20.2 GB | 128k | 40tok/sest. | 954 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 10.0 GB | 128k | 39tok/sest. | 590 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 10.3 GB | 128k | 38tok/sest. | 609 tok/s | chat, coding, agents, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 11.6 GB | 239k256k with q8 cache | 33tok/sest. | 583 tok/s | chat, coding, agents, long documents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 11.9 GB | 32k | 32tok/sest. | 314 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 12.7 GB | 128k | 30tok/sest. | 445 tok/s | chat, coding, long documents |
| LFM2.5 24B A2B Liquid AI | Q6_K | fits | 26.4 GB | 111k128k with q8 cache | 30tok/sest. | 857 tok/s | chat, coding, agents |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 13.5 GB | 128k | 28tok/sest. | 300 tok/s | chat, coding |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 15.1 GB | 64k | 24tok/sest. | 300 tok/s | chat, coding |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 17.6 GB | 128k | 21tok/sest. | 380 tok/s | chat, coding |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 18.6 GB | 149k256k with q8 cache | 19tok/sest. | 350 tok/s | chat, coding |
| Muse Glimmer 30B meta-models | Q6_K | fits | 24.4 GB | 128k | 14tok/sest. | 186 tok/s | – |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q8_0 | fits | 25.0 GB | 97k176k with q8 cache | 14tok/sest. | 256 tok/s | chat |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | fits | 25.1 GB | 142k248k with q8 cache | 14tok/sest. | 185 tok/s | chat |
| Devstral Small 2507 Mistral AI | Q5_K_M | fits | 27.3 GB | 83k128k with q8 cache | 13tok/sest. | 184 tok/s | chat |
| Magistral Small 2507 Mistral AI | Q5_K_M | fits | 27.3 GB | 40k | 13tok/sest. | 184 tok/s | chat |
| Magistral Small 2509 Mistral AI | Q5_K_M | fits | 27.3 GB | 83k128k with q8 cache | 13tok/sest. | 182 tok/s | chat |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q8_0 | fits | 28.3 GB | 74k128k with q8 cache | 12tok/sest. | 205 tok/s | chat |
| Magistral Small 2506 Mistral AI | Q6_K | fits | 29.7 GB | 40k | 12tok/sest. | 184 tok/s | chat |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 42.3 GB | – | 16tok/sest. | 317 tok/s | chat |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 48.4 GB | – | 17tok/sest. | 684 tok/s | chat, coding |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | offload | 53.2 GB | – | 10tok/sest. | 328 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 40.5 GB | – | 22tok/sest. | 319 tok/s | chat, coding |
| GLM 4.5 Air Z.ai | Q2_K | offload | 55.4 GB | – | 3tok/sest. | 90 tok/s | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 48.4 GB | – | 19tok/sest. | 781 tok/s | chat, coding |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 36.1 GB | 40k | 5tok/sest. | 85 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 36.2 GB | 41k76k with q8 cache | 5tok/sest. | 105 tok/s | chat |
| granite 4.2 30b IBM | Q4_K_M | offload | 34.5 GB | 48k88k with q8 cache | 6tok/sest. | 126 tok/s | chat |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 97.2 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 103.7 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 76.7 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 87.3 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 62.4 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 61.3 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 382.6 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 383.1 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 61.3 GB | – | – | – | – |
| DeepSeek R1 Zero DeepSeek | Q4_K_M | won't run | 382.6 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 382.6 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 382.6 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 383.5 GB | – | – | – | – |
| DeepSeek V3.1 Terminus DeepSeek | Q4_K_M | won't run | 383.5 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 383.5 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 152.7 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 161.5 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q4_K_M | won't run | 93.4 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 226.3 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 72.4 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 225.5 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 78.8 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 226.3 GB | – | – | – | – |
| GLM 5 Z.ai | MXFP4 | won't run | 389.5 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 427.1 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 441.0 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 753.5 GB | – | – | – | – |
| Kimi Dev 72B Moonshot AI | Q6_K | won't run | 81.6 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 584.1 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 584.5 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 584.5 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 584.5 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 146.0 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 146.0 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 132.4 GB | – | – | – | – |
| MiniMax M3 MiniMax | MXFP4 | won't run | 248.9 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 93.4 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- Radeon RX 9070
- Memory
- 16 GB GDDR6
- Memory bus
- 256-bit
- Memory bandwidth
- 640 GB/s
- FP16 compute
- 36.1 TFLOPS
- Software
- ROCm
- Board power
- 220 W
- PCIe generation
- Gen 5
- PCIe lanes
- x16
Compare with
Questions
- How much memory does the AMD Radeon RX 9070 have for AI models?
- The AMD Radeon RX 9070 has 16 GB of GDDR6 memory with 640 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the AMD Radeon RX 9070 can run locally?
- Qwen 3.8 27B (Q6_K) fits fully in its memory at 64k context and generates at about 12 tok/s, an estimate from its memory bandwidth. 58 of the 125 models we track fit at that context.
- Can the AMD Radeon RX 9070 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 9070 and system RAM can hold.
- How much does the AMD Radeon RX 9070 cost in Canada?
- The best new price for the AMD Radeon RX 9070 in Canada is $1,074 at Amazon.
Speeds on this page are for 64k context. See the best hardware for local AI at every budget.