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 31 of the 125 open models we track fully in memory; the most capable is gpt-oss 20B at MXFP4, at about 52 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 | 2 h ago | Buy |
| AmazonASUS PRIME Radeon RX 9070 16GB GDDR6 OC Edition Gaming Graphics Card | New | $1,282+ $10 delivery | In stock | 2 h ago | Buy |
| AmazonGIGABYTE Radeon RX 9070 Gaming Graphics Card with 16GB GDDR6X | New | $1,354 | In stock | 33 min ago | Buy |
| AmazonSapphire Pulse AMD Radeon RX 9070 16GB GDDR6 Gaming GPU | New | $1,388 | In stock | 1 h ago | Buy |
| AmazonASUS PRIME Radeon RX 9070 EVO 16GB GDDR6 OC Edition Gaming Graphics Card | New | $1,420 | 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 |
|---|---|---|---|---|---|---|---|
| gpt-oss 20B OpenAI | MXFP4 | fits | 14.0 GB | 106k128k with q8 cache | 52tok/sest. | 851 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 14.3 GB | 106k171k with q8 cache | 25tok/sest. | 437 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 12.1 GB | 147k243k with q8 cache | 30tok/sest. | 535 tok/s | chat, coding, long documents |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q4_K_M | fits | 14.9 GB | 66k120k with q8 cache | 24tok/sest. | 354 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q4_K_M | fits | 14.9 GB | 40k | 24tok/sest. | 354 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.4 GB | 256k | 53tok/sest. | 928 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q4_K_M | fits | 14.5 GB | 68k125k with q8 cache | 25tok/sest. | 350 tok/s | chat, coding |
| Gemma 4 E4B | Q8_0 | fits | 10.6 GB | 128k | 35tok/sest. | 701 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 12.6 GB | 113k125k with q8 cache | 49tok/sest. | 1497 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q5_K_M | fits | 14.5 GB | 69k125k with q8 cache | 25tok/sest. | 380 tok/s | chat, coding |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 2.4 GB | 32k | 263tok/sest. | 3319 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 2.7 GB | 256k | 215tok/sest. | 3763 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 3.3 GB | 256k | 156tok/sest. | 2052 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 4.7 GB | 128k | 93tok/sest. | 1375 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 6.3 GB | 128k | 64tok/sest. | 775 tok/s | chat, coding, agents, long documents |
| Spark X2.5 4B XHToken | mlx-4bit | fits | 6.3 GB | 280k470k with q8 cache | 64tok/sest. | 951 tok/s | chat, coding, agents, long documents |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q8_0 | fits | 14.1 GB | 118k128k with q8 cache | 58tok/sest. | 1387 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Thinking 2506 Moonshot AI | Q4_K_M | fits | 12.9 GB | 128k | 53tok/sest. | 954 tok/s | chat, coding, long documents |
| FrogNano 4B 2609 Microsoft | Q8_0 | fits | 7.5 GB | 256k | 52tok/sest. | 928 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q8_0 | fits | 7.6 GB | 128k | 51tok/sest. | 940 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q8_0 | fits | 7.6 GB | 32k | 51tok/sest. | 884 tok/s | chat, coding, agents, long documents |
| Kimi VL A3B Moonshot AI | mlx-5bit | fits | 14.1 GB | 95k128k with q8 cache | 50tok/sest. | 954 tok/s | chat, coding, agents, long documents |
| granite vision 4.1 4b IBM | Q8_0 | fits | 9.5 GB | 128k | 39tok/sest. | 590 tok/s | chat, coding, long documents |
| granite 4.2 3b IBM | Q8_0 | fits | 9.8 GB | 128k | 38tok/sest. | 609 tok/s | chat, coding, agents, long documents |
| Ministral 3 3B Instruct 2512 Mistral AI | Q8_0 | fits | 11.1 GB | 102k183k with q8 cache | 33tok/sest. | 583 tok/s | chat, coding, agents |
| GLM 4 9B 0414 Z.ai | mlx-5bit | fits | 11.4 GB | 32k | 32tok/sest. | 314 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q8_0 | fits | 12.2 GB | 113k128k with q8 cache | 30tok/sest. | 445 tok/s | chat, coding |
| GLM 4.6V Flash Z.ai | Q8_0 | fits | 13.0 GB | 113k128k with q8 cache | 28tok/sest. | 300 tok/s | chat, coding |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q5_K_M | fits | 14.5 GB | 69k125k with q8 cache | 25tok/sest. | 380 tok/s | chat, coding |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q4_K_M | fits | 14.5 GB | 68k125k with q8 cache | 25tok/sest. | 350 tok/s | chat, coding |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | fits | 14.6 GB | 64k | 24tok/sest. | 300 tok/s | chat, coding |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 20.6 GB | – | 7tok/sest. | 154 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 21.0 GB | – | 6tok/sest. | 152 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 24.0 GB | – | 5tok/sest. | 130 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 40.0 GB | – | 12tok/sest. | 233 tok/s | chat |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 22.7 GB | – | 22tok/sest. | 879 tok/s | chat, coding |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 20.9 GB | – | 6tok/sest. | 153 tok/s | – |
| Gemma 4 26B-A4B | MXFP4 | offload | 18.0 GB | – | 27tok/sest. | 1023 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 23.0 GB | – | 22tok/sest. | 873 tok/s | chat, coding |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 21.5 GB | – | 12tok/sest. | 448 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 24.5 GB | 6k11k with q8 cache | 4tok/sest. | 138 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | MXFP4 | offload | 23.2 GB | – | 26tok/sest. | 1071 tok/s | chat, coding, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.7 GB | – | 23tok/sest. | 620 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 24.5 GB | – | 8tok/sest. | 303 tok/s | chat |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 35.6 GB | – | 2tok/sest. | 61 tok/s | – |
| Gemma 3 27B | Q4_K_M | offload | 22.0 GB | – | 6tok/sest. | 166 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 24.5 GB | 6k11k with q8 cache | 4tok/sest. | 138 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 35.7 GB | – | 2tok/sest. | 75 tok/s | – |
| Ministral 3 14B Mistral AI | Q4_K_M | offload | 18.8 GB | 41k75k with q8 cache | 9tok/sest. | 224 tok/s | chat, coding |
| Qwen3 14B Alibaba Qwen | Q4_K_M | offload | 19.6 GB | 37k40k with q8 cache | 8tok/sest. | 192 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q4_K_M | offload | 22.0 GB | 16k | 6tok/sest. | 181 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q4_K_M | offload | 16.3 GB | 57k103k with q8 cache | 15tok/sest. | 309 tok/s | chat, coding |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 20.5 GB | 1k2k with q8 cache | 13tok/sest. | 717 tok/s | chat, coding |
| Muse Glimmer 30B meta-models | Q4_K_M | offload | 18.2 GB | – | 10tok/sest. | 167 tok/s | – |
| Ministral 3 14B Reasoning 2512 Mistral AI | Q4_K_M | offload | 18.8 GB | 41k75k with q8 cache | 9tok/sest. | 224 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | offload | 21.5 GB | 31k57k with q8 cache | 6tok/sest. | 166 tok/s | chat, coding |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 24.5 GB | 6k11k with q8 cache | 4tok/sest. | 140 tok/s | chat |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 24.5 GB | 6k11k with q8 cache | 4tok/sest. | 140 tok/s | chat |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 24.5 GB | 6k11k with q8 cache | 4tok/sest. | 140 tok/s | chat |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 24.5 GB | 6k11k with q8 cache | 4tok/sest. | 138 tok/s | chat |
| Qwen3.8 27B OBLITERATED OBLITERATUS | mlx-4bit | offload | 24.6 GB | – | 4tok/sest. | 140 tok/s | – |
| granite 4.2 30b IBM | Q4_K_M | offload | 34.0 GB | – | 2tok/sest. | 89 tok/s | – |
| 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 | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 41.8 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.7 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 47.9 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 | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 47.9 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 R1 Zero DeepSeek | Q4_K_M | won't run | 382.1 GB | – | – | – | – |
| DeepSeek V3 DeepSeek | Q4_K_M | won't run | 382.1 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 V3.1 Terminus 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 | Q4_K_M | won't run | 92.9 GB | – | – | – | – |
| GLM 4.5 Z.ai | Q4_K_M | won't run | 225.8 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 71.9 GB | – | – | – | – |
| GLM 4.6 Z.ai | Q4_K_M | won't run | 225.0 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 Z.ai | MXFP4 | won't run | 389.0 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 Dev 72B Moonshot AI | Q6_K | won't run | 81.1 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 | MXFP4 | won't run | 248.4 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 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 64k context and generates at about 52 tok/s, an estimate from its memory bandwidth. 31 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.