Intel Arc B580
12 GB · 456 GB/s · 190 W
In short
The Intel Arc B580 has 12 GB of GDDR6 memory with 456 GB/s of bandwidth, which sets how fast it generates text. At 128k context it runs 11 of the 113 open models we track fully in memory; the most capable is Gemma 4 12B at Q4_K_M, at about 24 tok/s (estimated). The best new price for the Intel Arc B580 in Canada is $550 at eBay; used, it starts at $450 (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.
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 @128k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Gemma 4 12B | Q4_K_M | fits | 10.5 GB | 160k254k with q8 cache | 24tok/sest. | 1053 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q4_K_M | fits | 10.9 GB | 136k225k with q8 cache | 23tok/sest. | 1253 tok/s | chat, coding, long documents |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 9.8 GB | 166k256k with q8 cache | 26tok/sest. | 1952 tok/s | chat, coding, long documents |
| Gemma 4 E4B | Q5_K_M | fits | 10.2 GB | 128k | 25tok/sest. | 1757 tok/s | chat, coding, long documents |
| Qwen2.5 0.5B Alibaba Qwen | Q8_0 | fits | 3.5 GB | 32k | 107tok/sest. | 5275 tok/s | chat, coding, long documents |
| Qwen3.5 0.8B Alibaba Qwen | Q8_0 | fits | 3.8 GB | 256k | 93tok/sest. | 7035 tok/s | chat, coding, agents, long documents |
| Qwen3.5 2B Alibaba Qwen | Q5_K_M | fits | 4.4 GB | 256k | 74tok/sest. | 4498 tok/s | chat, coding, agents, long documents |
| DeepSeek R1 Distill Qwen 1.5B DeepSeek | Q8_0 | fits | 6.8 GB | 128k | 40tok/sest. | 2357 tok/s | chat, coding, long documents |
| MiniCPM5 2B openbmb | Q8_0 | fits | 9.3 GB | 128k | 27tok/sest. | 1267 tok/s | chat, coding, agents, long documents |
| LFM2.5 2.6B Liquid AI | Q6_K | fits | 11.1 GB | 128k | 22tok/sest. | 1626 tok/s | chat, coding, agents, long documents |
| LFM2.5 VL 3B Liquid AI | Q6_K | fits | 11.1 GB | 32k | 22tok/sest. | 1564 tok/s | chat, coding, agents, long documents |
| Qwen 3.8 27B Alibaba Qwen | UD-Q4_K_M | offload | 25.0 GB | – | 3tok/sest. | 278 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | offload | 25.4 GB | – | 3tok/sest. | 276 tok/s | – |
| Gemma 4 31B | Q4_K_M | offload | 29.4 GB | – | 2tok/sest. | 248 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | MXFP4 | offload | 24.3 GB | – | 10tok/sest. | 1366 tok/s | chat |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | offload | 25.3 GB | – | 3tok/sest. | 277 tok/s | – |
| Gemma 4 26B-A4B | UD-Q4_K_M | offload | 20.0 GB | – | 9tok/sest. | 1808 tok/s | chat |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q4_K_M | offload | 24.6 GB | – | 10tok/sest. | 1360 tok/s | chat |
| GLM 4.7 Flash Z.ai | Q4_K_M | offload | 25.2 GB | – | 4tok/sest. | 635 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 34.9 GB | – | 2tok/sest. | 220 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 34.9 GB | – | 9tok/sest. | 1611 tok/s | – |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 30.6 GB | – | 14tok/sest. | 939 tok/s | chat |
| gpt-oss 20B OpenAI | Q4_K_M | offload | 15.4 GB | – | 11tok/sest. | 1344 tok/s | chat, coding |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 30.8 GB | – | 3tok/sest. | 363 tok/s | chat |
| Gemma 3 27B | Q4_K_M | offload | 27.4 GB | – | 3tok/sest. | 328 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 34.9 GB | – | 2tok/sest. | 220 tok/s | – |
| Ministral 3 14B Mistral AI | Q4_K_M | offload | 29.2 GB | 16k30k with q8 cache | 3tok/sest. | 301 tok/s | chat |
| Qwen3 14B Alibaba Qwen | Q4_K_M | offload | 29.9 GB | 12k22k with q8 cache | 2tok/sest. | 254 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q4_K_M | offload | 24.2 GB | 39k70k with q8 cache | 3tok/sest. | 416 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q4_K_M | offload | 24.2 GB | 39k40k with q8 cache | 3tok/sest. | 416 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q4_K_M | offload | 34.8 GB | 10k16k with q8 cache | 2tok/sest. | 242 tok/s | chat |
| Ministral 3 8B Mistral AI | Q4_K_M | offload | 23.4 GB | 40k72k with q8 cache | 4tok/sest. | 428 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q4_K_M | offload | 26.7 GB | 32k58k with q8 cache | 3tok/sest. | 364 tok/s | chat, coding |
| LFM2.5 8B-A1B Liquid AI | UD-Q4_K_M | offload | 12.5 GB | 103k125k with q8 cache | 13tok/sest. | 2180 tok/s | chat, coding |
| Llama 3.1 8B Meta | Q4_K_M | offload | 22.1 GB | 44k80k with q8 cache | 4tok/sest. | 472 tok/s | chat, coding |
| Mellum2.1 12B A2.5B Thinking JetBrains | Q6_K | offload | 14.0 GB | – | 17tok/sest. | 2349 tok/s | chat, coding, agents, long documents |
| GLM 4.6V Flash Z.ai | Q4_K_M | offload | 12.3 GB | 103k128k with q8 cache | 15tok/sest. | 517 tok/s | chat, coding, agents |
| DeepSeek R1 Distill Qwen 7B DeepSeek | Q4_K_M | offload | 12.9 GB | 99k128k with q8 cache | 13tok/sest. | 765 tok/s | chat, coding |
| granite vision 4.1 4b IBM | Q4_K_M | offload | 13.5 GB | 100k128k with q8 cache | 11tok/sest. | 887 tok/s | chat, coding |
| granite 4.2 3b IBM | Q4_K_M | offload | 13.7 GB | 98k128k with q8 cache | 11tok/sest. | 896 tok/s | chat, coding, agents |
| Kimi VL A3B Moonshot AI | mlx-5bit | offload | 16.4 GB | – | 9tok/sest. | 1349 tok/s | chat, coding |
| GLM 4.1V 9B Thinking Z.ai | mlx-8bit | offload | 17.5 GB | – | 6tok/sest. | 420 tok/s | – |
| DeepSeek R1 Distill Llama 8B DeepSeek | Q4_K_M | offload | 22.1 GB | 44k80k with q8 cache | 4tok/sest. | 472 tok/s | chat, coding |
| LFM2.5 24B A2B Liquid AI | Q4_K_M | offload | 25.8 GB | – | 4tok/sest. | 876 tok/s | chat |
| Ministral 3 8B Reasoning 2512 Mistral AI | Q4_K_M | offload | 23.4 GB | 40k72k with q8 cache | 4tok/sest. | 428 tok/s | chat, coding |
| DeepSeek R1 Distill Qwen 14B DeepSeek | Q4_K_M | offload | 33.9 GB | 10k19k with q8 cache | 2tok/sest. | 215 tok/s | chat |
| Devstral Small 2507 Mistral AI | Q4_K_M | offload | 34.9 GB | – | 2tok/sest. | 223 tok/s | – |
| Magistral Small 2506 Mistral AI | Q4_K_M | offload | 34.9 GB | – | 2tok/sest. | 223 tok/s | – |
| Magistral Small 2507 Mistral AI | Q4_K_M | offload | 34.9 GB | – | 2tok/sest. | 223 tok/s | – |
| Magistral Small 2509 Mistral AI | Q4_K_M | offload | 34.9 GB | – | 2tok/sest. | 220 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 102.5 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 104.3 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 78.1 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 102.7 GB | – | – | – | – |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | won't run | 43.7 GB | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 53.6 GB | – | – | – | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | won't run | 49.8 GB | – | – | – | – |
| gpt-oss 120B OpenAI | Q4_K_M | won't run | 64.5 GB | – | – | – | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | won't run | 41.8 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 66.8 GB | – | – | – | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | won't run | 49.8 GB | – | – | – | – |
| Qwen3 32B Alibaba Qwen | Q4_K_M | won't run | 52.0 GB | – | – | – | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | won't run | 52.0 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 81.2 GB | – | – | – | – |
| DeepSeek R1 DeepSeek | Q4_K_M | won't run | 386.8 GB | – | – | – | – |
| DeepSeek R1 0528 DeepSeek | Q4_K_M | won't run | 387.3 GB | – | – | – | – |
| DeepSeek R1 Distill Llama 70B DeepSeek | Q4_K_M | won't run | 81.2 GB | – | – | – | – |
| DeepSeek V3 0324 DeepSeek | Q4_K_M | won't run | 386.8 GB | – | – | – | – |
| DeepSeek V3.1 DeepSeek | Q4_K_M | won't run | 387.7 GB | – | – | – | – |
| DeepSeek V3.2 DeepSeek | Q4_K_M | won't run | 387.7 GB | – | – | – | – |
| DeepSeek V4 Flash 0731 DeepSeek | MXFP4 | won't run | 157.9 GB | – | – | – | – |
| DeepSeek V4 Flash Vision Exp DeepSeek | MXFP4 | won't run | 166.7 GB | – | – | – | – |
| Devstral 2 123B Instruct 2512 Mistral AI | Q8_0 | won't run | 169.3 GB | – | – | – | – |
| GLM 4.5V Z.ai | Q4_K_M | won't run | 83.8 GB | – | – | – | – |
| GLM 4.6V Z.ai | Q4_K_M | won't run | 90.2 GB | – | – | – | – |
| GLM 4.7 Z.ai | Q4_K_M | won't run | 249.1 GB | – | – | – | – |
| GLM 5.1 Z.ai | MXFP4 | won't run | 432.5 GB | – | – | – | – |
| GLM 5.2 Z.ai | UD-Q4_K_M | won't run | 446.4 GB | – | – | – | – |
| GLM 5.3 Z.ai | Q8_0 | won't run | 758.8 GB | – | – | – | – |
| Kimi K2 Moonshot AI | Q4_K_M | won't run | 588.3 GB | – | – | – | – |
| Kimi K2 Instruct 0905 Moonshot AI | Q4_K_M | won't run | 588.7 GB | – | – | – | – |
| Kimi K2 Thinking Moonshot AI | Q4_K_M | won't run | 588.7 GB | – | – | – | – |
| Kimi K2.5 Moonshot AI | Q4_K_M | won't run | 588.7 GB | – | – | – | – |
| MiniMax M2 MiniMax | Q4_K_M | won't run | 161.4 GB | – | – | – | – |
| MiniMax M2.1 MiniMax | Q4_K_M | won't run | 161.4 GB | – | – | – | – |
| MiniMax M2.5 MiniMax | MXFP4 | won't run | 147.8 GB | – | – | – | – |
| MiniMax M3 MiniMax | UD-Q4_K_M | won't run | 263.3 GB | – | – | – | – |
| Mistral Medium 3.5 128B Mistral AI | Q4_K_M | won't run | 115.3 GB | – | – | – | – |
| granite 4.2 30b IBM | Q4_K_M | won't run | 50.3 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- Arc B580
- Memory
- 12 GB GDDR6
- Memory bus
- 192-bit
- Memory bandwidth
- 456 GB/s
- FP16 compute
- 116.5 TFLOPS
- Software
- SYCL / oneAPI
- Board power
- 190 W
- PCIe generation
- Gen 4
- PCIe lanes
- x8
Compare with
Questions
- How much memory does the Intel Arc B580 have for AI models?
- The Intel Arc B580 has 12 GB of GDDR6 memory with 456 GB/s of bandwidth, which sets how fast it generates text.
- What is the best model the Intel Arc B580 can run locally?
- Gemma 4 12B (Q4_K_M) fits fully in its memory at 128k context and generates at about 24 tok/s, an estimate from its memory bandwidth. 11 of the 113 models we track fit at that context.
- Can the Intel Arc B580 run DeepSeek V4 Flash?
- No: even at UD-Q2_K_XL, DeepSeek V4 Flash needs about 102 GB at 128k context, more than the Intel Arc B580 and system RAM can hold.
- How much does the Intel Arc B580 cost in Canada?
- The best new price for the Intel Arc B580 in Canada is $550 at eBay; used, it starts at $450 (asking price).
Speeds on this page are for 128k context. See the best hardware for local AI at every budget.