Intel Arc A770 16GB
16 GB · 560 GB/s · 225 W
Prices
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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 @128k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | UD-Q5_K_M | fits | 28.6 GB | 154k256k with q8 cache | 10tok/sest. | 483 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q5_K_M | fits | 28.4 GB | 157k256k with q8 cache | 10tok/sest. | 483 tok/s | – |
| Gemma 4 31B | Q4_K_M | fits | 29.9 GB | 133k245k with q8 cache | 9tok/sest. | 459 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | UD-Q5_K_M | fits | 29.2 GB | 173k256k with q8 cache | 31tok/sest. | 2348 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q5_K_M | fits | 28.5 GB | 156k256k with q8 cache | 10tok/sest. | 483 tok/s | – |
| Gemma 4 26B-A4B | Q8_0 | fits | 29.8 GB | 153k245k with q8 cache | 22tok/sest. | 2850 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q5_K_M | fits | 29.1 GB | 180k256k with q8 cache | 31tok/sest. | 2348 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q5_K_M | fits | 28.6 GB | 159k198k with q8 cache | 15tok/sest. | 1108 tok/s | chat, coding |
| gpt-oss 20B OpenAI | MXFP4 | fits | 16.3 GB | 128k | 27tok/sest. | 1845 tok/s | chat, coding, agents, long documents |
| Gemma 4 12B | Q8_0 | fits | 16.2 GB | 256k | 19tok/sest. | 1184 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 15.0 GB | 256k | 20tok/sest. | 1409 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q4_K_M | fits | 27.9 GB | 128k | 10tok/sest. | 591 tok/s | chat |
| Ministral 3 14B Mistral AI | Q4_K_M | fits | 29.7 GB | 132k241k with q8 cache | 9tok/sest. | 555 tok/s | chat, coding |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 28.2 GB | 128k | 10tok/sest. | 714 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 28.2 GB | 40k | 10tok/sest. | 714 tok/s | chat, coding |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 10.3 GB | 256k | 32tok/sest. | 2194 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 27.5 GB | 149k256k with q8 cache | 10tok/sest. | 723 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q6_K | fits | 29.1 GB | 128k | 10tok/sest. | 649 tok/s | chat, coding |
| Gemma 4 E4B | Q8_0 | fits | 13.2 GB | 128k | 23tok/sest. | 1975 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 16.4 GB | 125k | 21tok/sest. | 2640 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 24.2 GB | 128k | 12tok/sest. | 779 tok/s | chat, coding |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 44.2 GB | – | 10tok/sest. | 690 tok/s | chat |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 50.3 GB | – | 10tok/sest. | 1433 tok/s | chat |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | offload | 54.1 GB | – | 8tok/sest. | 876 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 42.3 GB | – | 13tok/sest. | 613 tok/s | chat, coding |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 50.3 GB | – | 11tok/sest. | 1566 tok/s | chat, coding |
| Devstral Small 2 24B Mistral AI | Q4_K_M | offload | 35.4 GB | 97k177k with q8 cache | 5tok/sest. | 393 tok/s | chat |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 35.4 GB | – | 23tok/sest. | 2872 tok/s | chat, coding, long documents |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | offload | 31.1 GB | 78k107k with q8 cache | 48tok/sest. | 1737 tok/s | chat, coding, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q4_K_M | offload | 31.3 GB | 118k212k with q8 cache | 9tok/sest. | 670 tok/s | chat, coding, agents |
| Qwen3 32B Alibaba Qwen | Q4_K_M | offload | 52.5 GB | 40k | 2tok/sest. | 143 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q4_K_M | offload | 35.4 GB | 97k128k with q8 cache | 5tok/sest. | 393 tok/s | chat |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | offload | 52.5 GB | 41k76k with q8 cache | 2tok/sest. | 191 tok/s | – |
| Qwen3 14B Alibaba Qwen | Q4_K_M | offload | 30.4 GB | 40k | 9tok/sest. | 472 tok/s | chat |
| Phi-4 14B Microsoft | Q4_K_M | offload | 35.3 GB | 16k | 5tok/sest. | 431 tok/s | chat |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 103.0 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 104.8 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 78.6 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 103.2 GB | – | – | – | – |
| gpt-oss 120B OpenAI | MXFP4 | won't run | 65.6 GB | – | – | – | – |
| GLM 4.5 Air Z.ai | Q2_K | won't run | 67.3 GB | – | – | – | – |
| Llama 3.3 70B Meta | Q4_K_M | won't run | 81.7 GB | – | – | – | – |
Specifications
From the manufacturer's published specifications; sources are linked where we have them.
- GPU
- Arc A770 16GB
- Memory
- 16 GB GDDR6
- Memory bus
- 256-bit
- Memory bandwidth
- 560 GB/s
- FP16 compute
- 131 TFLOPS
- Software
- SYCL / oneAPI
- Board power
- 225 W
- PCIe generation
- Gen 4
- PCIe lanes
- x16