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 32k context it runs 35 of the 125 open models we track fully in memory; the most capable is gpt-oss 20B at MXFP4, at about 65 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 | 51 min ago | Buy |
| AmazonASUS PRIME Radeon RX 9070 16GB GDDR6 OC Edition Gaming Graphics Card | New | $1,282+ $10 delivery | In stock | 51 min ago | Buy |
| AmazonSapphire Pulse AMD Radeon RX 9070 16GB GDDR6 Gaming GPU | New | $1,388 | In stock | 11 min ago | Buy |
| AmazonASUS PRIME Radeon RX 9070 EVO 16GB GDDR6 OC Edition Gaming Graphics Card | New | $1,420 | In stock | 51 min 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 @32k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| gpt-oss 20B OpenAI | MXFP4 | fits | 13.0 GB | 106k128k with q8 cache | 65tok/sest. | 1086 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 13.6 GB | 106k171k with q8 cache | 26tok/sest. | 473 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 10.9 GB | 147k243k with q8 cache | 33tok/sest. | 589 tok/s | chat, coding, long documents |
| Qwen3 14B Alibaba Qwen | Q4_K_M | fits | 14.4 GB | 37k40k with q8 cache | 25tok/sest. | 294 tok/s | chat, coding |
| Ministral 3 14B Mistral AI | Q5_K_M | fits | 14.9 GB | 33k61k with q8 cache | 24tok/sest. | 327 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 13.6 GB | 42k78k with q8 cache | 26tok/sest. | 485 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 13.6 GB | 40k | 26tok/sest. | 485 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 6.2 GB | 256k | 63tok/sest. | 1102 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 13.6 GB | 43k78k with q8 cache | 26tok/sest. | 469 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q8_0 | fits | 14.7 GB | 35k64k with q8 cache | 24tok/sest. | 446 tok/s | chat, coding |
| Gemma 4 E4B | Q8_0 | fits | 9.5 GB | 128k | 38tok/sest. | 740 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 10.9 GB | 113k125k with q8 cache | 79tok/sest. | 2420 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 11.1 GB | 63k114k with q8 cache | 32tok/sest. | 513 tok/s | chat, coding |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 1.9 GB | 32k | 377tok/sest. | 5270 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.1 GB | 256k | 285tok/sest. | 4951 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 2.7 GB | 256k | 190tok/sest. | 2360 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 3.6 GB | 128k | 124tok/sest. | 1983 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 4.8 GB | 128k | 86tok/sest. | 1184 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 5.0 GB | 280k470k with q8 cache | 82tok/sest. | 1163 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 5.5 GB | 128k | 72tok/sest. | 1341 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 5.5 GB | 32k | 72tok/sest. | 1230 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | fits | 11.8 GB | 128k | 72tok/sest. | 1313 tok/s | chat, coding, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 13.5 GB | 118k128k with q8 cache | 67tok/sest. | 1747 tok/s | chat, coding, agents, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 6.3 GB | 256k | 61tok/sest. | 1102 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Moonshot AI | mlx-6bit | fits | 14.8 GB | 42k70k with q8 cache | 60tok/sest. | 1313 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 6.9 GB | 128k | 56tok/sest. | 859 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 7.1 GB | 128k | 54tok/sest. | 901 tok/s | chat, coding, agents, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 7.6 GB | 102k183k with q8 cache | 49tok/sest. | 861 tok/s | chat, coding, agents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 9.9 GB | 32k | 37tok/sest. | 428 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 10.3 GB | 113k128k with q8 cache | 35tok/sest. | 579 tok/s | chat, coding |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 11.6 GB | 113k128k with q8 cache | 31tok/sest. | 403 tok/s | chat, coding |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q8_0 | fits | 12.9 GB | 49k89k with q8 cache | 27tok/sest. | 513 tok/s | chat, coding |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 13.2 GB | 64k | 27tok/sest. | 403 tok/s | chat, coding |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q8_0 | fits | 13.6 GB | 43k78k with q8 cache | 26tok/sest. | 469 tok/s | chat, coding |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q5_K_M | fits | 14.9 GB | 33k61k with q8 cache | 24tok/sest. | 327 tok/s | chat, coding |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 18.5 GB | – | 9tok/sest. | 181 tok/s | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 40.8 GB | – | 11tok/sest. | 293 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 18.8 GB | – | 9tok/sest. | 179 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 21.3 GB | – | 6tok/sest. | 149 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.1 GB | – | 15tok/sest. | 331 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 21.9 GB | – | 30tok/sest. | 1176 tok/s | chat, coding |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 18.7 GB | – | 9tok/sest. | 180 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 17.2 GB | – | 36tok/sest. | 1198 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 22.2 GB | – | 29tok/sest. | 1168 tok/s | chat, coding |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 19.7 GB | – | 19tok/sest. | 650 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 8tok/sest. | 186 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 22.8 GB | – | 29tok/sest. | 1312 tok/s | chat, coding, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.3 GB | – | 26tok/sest. | 880 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 21.3 GB | – | 16tok/sest. | 549 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 27.4 GB | – | 4tok/sest. | 92 tok/s | – |
| Gemma 3 27B | Q4_K_M | offload | 19.3 GB | – | 8tok/sest. | 187 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 8tok/sest. | 186 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 27.5 GB | – | 4tok/sest. | 105 tok/s | – |
| Phi-4 14B Microsoft | Q4_K_M | offload | 15.5 GB | 16k | 20tok/sest. | 292 tok/s | chat, coding |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 17.8 GB | 1k2k with q8 cache | 29tok/sest. | 1224 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | offload | 15.4 GB | 31k57k with q8 cache | 22tok/sest. | 275 tok/s | chat, coding |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 17.6 GB | – | 11tok/sest. | 179 tok/s | – |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 8tok/sest. | 189 tok/s | chat |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 8tok/sest. | 189 tok/s | chat |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 8tok/sest. | 189 tok/s | chat |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 19.3 GB | 6k11k with q8 cache | 8tok/sest. | 186 tok/s | chat |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 22.4 GB | – | 5tok/sest. | 163 tok/s | – |
| granite 4.2 30b IBM | Q4_K_M | offload | 25.8 GB | – | 4tok/sest. | 124 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 R1 Zero DeepSeek | Q4_K_M | won't run | 379.8 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 379.8 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 V3.1 Terminus 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 | Q4_K_M | won't run | 81.7 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 214.1 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 66.0 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 213.3 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 Z.ai | MXFP4 | won't run | 386.1 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 Dev 72B Moonshot AI | Q6_K | won't run | 70.9 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 | MXFP4 | won't run | 244.4 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 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?
- gpt-oss 20B (MXFP4) fits fully in its memory at 32k context and generates at about 65 tok/s, an estimate from its memory bandwidth. 35 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 94 GB at 32k 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 32k context. See the best hardware for local AI at every budget.