Intel Arc Pro B60
24 GB · 456 GB/s · 200 W
Prices
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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 | UD-Q4_K_M | fits | 20.6 GB | 101k177k with q8 cache | 11tok/sest. | 432 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q4_K_M | fits | 21.0 GB | 96k168k with q8 cache | 11tok/sest. | 432 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | UD-Q4_K_M | fits | 23.1 GB | 68k106k with q8 cache | 39tok/sest. | 2599 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q4_K_M | fits | 20.9 GB | 97k170k with q8 cache | 11tok/sest. | 432 tok/s | – |
| Gemma 4 26B-A4B | UD-Q5_K_M | fits | 22.3 GB | 98k160k with q8 cache | 26tok/sest. | 2661 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 | 39tok/sest. | 2599 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q4_K_M | fits | 21.5 GB | 92k160k with q8 cache | 19tok/sest. | 1289 tok/s | chat, coding |
| gpt-oss 20B OpenAI | MXFP4 | fits | 14.0 GB | 128k | 31tok/sest. | 1989 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 14.3 GB | 256k | 16tok/sest. | 1023 tok/s | chat, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 12.1 GB | 256k | 19tok/sest. | 1252 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q4_K_M | fits | 22.0 GB | 78k128k with q8 cache | 10tok/sest. | 484 tok/s | – |
| Ministral 3 14B Mistral AI | Q6_K | fits | 21.5 GB | 74k135k with q8 cache | 10tok/sest. | 599 tok/s | chat |
| Qwen3 14B Alibaba Qwen | Q6_K | fits | 22.5 GB | 40k | 10tok/sest. | 524 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 18.3 GB | 97k128k with q8 cache | 12tok/sest. | 828 tok/s | chat |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 18.3 GB | 40k | 12tok/sest. | 828 tok/s | chat |
| Phi-4 14B Microsoft | Q4_K_M | fits | 22.0 GB | 16k | 10tok/sest. | 526 tok/s | chat |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 7.4 GB | 256k | 34tok/sest. | 2170 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 18.1 GB | 100k183k with q8 cache | 13tok/sest. | 819 tok/s | chat |
| Granite 4.2 8B IBM | Q8_0 | fits | 19.9 GB | 84k128k with q8 cache | 11tok/sest. | 757 tok/s | chat |
| Gemma 4 E4B | Q8_0 | fits | 10.6 GB | 128k | 23tok/sest. | 1640 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 12.6 GB | 125k | 29tok/sest. | 3500 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 15.3 GB | 124k128k with q8 cache | 15tok/sest. | 889 tok/s | chat, coding |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 41.8 GB | – | 10tok/sest. | 652 tok/s | – |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 47.9 GB | – | 11tok/sest. | 1421 tok/s | chat |
| Gemma 4 31B | Q4_K_M | offload | 24.0 GB | 54k103k with q8 cache | 8tok/sest. | 386 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 40.0 GB | – | 13tok/sest. | 654 tok/s | chat |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 47.9 GB | – | 13tok/sest. | 1621 tok/s | chat |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 24.5 GB | 55k101k with q8 cache | 8tok/sest. | 411 tok/s | – |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 34.2 GB | – | 16tok/sest. | 2564 tok/s | chat |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 29.7 GB | – | 30tok/sest. | 1802 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 24.5 GB | 51k91k with q8 cache | 13tok/sest. | 900 tok/s | chat, coding |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 35.6 GB | 15k28k with q8 cache | 3tok/sest. | 173 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 24.5 GB | 55k101k with q8 cache | 8tok/sest. | 411 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 35.7 GB | 15k28k with q8 cache | 3tok/sest. | 213 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 | – | – | – | – |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | won't run | 52.7 GB | – | – | – | – |
| gpt-oss 120B OpenAI | MXFP4 | won't run | 62.5 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 | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- Arc Pro B60
- Memory
- 24 GB GDDR6
- Memory bus
- 192-bit
- Memory bandwidth
- 456 GB/s
- FP16 compute
- 98.5 TFLOPS
- Software
- SYCL / oneAPI
- Board power
- 200 W
- PCIe generation
- Gen 5
- PCIe lanes
- x8