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 @8k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | Q8_0 | fits | 29.0 GB | 27k48k with q8 cache | 9tok/sest. | 687 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 28.6 GB | 34k59k with q8 cache | 10tok/sest. | 687 tok/s | – |
| Gemma 4 31B | Q6_K | fits | 26.2 GB | 57k110k with q8 cache | 11tok/sest. | 599 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | UD-Q6_K | fits | 28.9 GB | 68k107k with q8 cache | 58tok/sest. | 5891 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 28.6 GB | 34k59k with q8 cache | 10tok/sest. | 687 tok/s | – |
| Gemma 4 26B-A4B | Q8_0 | fits | 26.7 GB | 153k245k with q8 cache | 34tok/sest. | 4489 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q6_K | fits | 28.4 GB | 85k133k with q8 cache | 58tok/sest. | 5891 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q6_K | fits | 24.8 GB | 106k183k with q8 cache | 34tok/sest. | 3297 tok/s | chat, coding |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 25.9 GB | 35k64k with q8 cache | 11tok/sest. | 775 tok/s | – |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | fits | 29.4 GB | 78k107k with q8 cache | 79tok/sest. | 5599 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 12.8 GB | 128k | 59tok/sest. | 4264 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q6_K | fits | 25.5 GB | 57k102k with q8 cache | 47tok/sest. | 4262 tok/s | chat, coding |
| Qwen3 32B Alibaba Qwen | Q6_K | fits | 28.4 GB | 15k29k with q8 cache | 10tok/sest. | 530 tok/s | – |
| Gemma 4 12B | Q8_0 | fits | 13.6 GB | 256k | 21tok/sest. | 1564 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 10.5 GB | 256k | 28tok/sest. | 1981 tok/s | chat, coding, long documents |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 25.9 GB | 35k64k with q8 cache | 11tok/sest. | 775 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q6_K | fits | 28.4 GB | 15k29k with q8 cache | 10tok/sest. | 554 tok/s | – |
| Gemma 3 27B | Q8_0 | fits | 29.1 GB | 23k45k with q8 cache | 9tok/sest. | 697 tok/s | – |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 16.0 GB | 97k176k with q8 cache | 18tok/sest. | 1285 tok/s | chat |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 17.2 GB | 40k | 16tok/sest. | 1195 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 10.6 GB | 128k | 28tok/sest. | 2091 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 10.6 GB | 40k | 28tok/sest. | 2091 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q8_0 | fits | 17.4 GB | 16k | 16tok/sest. | 1203 tok/s | chat |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 5.8 GB | 256k | 58tok/sest. | 3987 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 10.8 GB | 149k256k with q8 cache | 28tok/sest. | 1954 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q8_0 | fits | 11.3 GB | 125k128k with q8 cache | 26tok/sest. | 1939 tok/s | chat |
| Gemma 4 E4B | Q8_0 | fits | 9.2 GB | 128k | 33tok/sest. | 2400 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 10.1 GB | 125k | 105tok/sest. | 14009 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 8.5 GB | 128k | 37tok/sest. | 2158 tok/s | chat, coding |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 40.6 GB | – | 20tok/sest. | 1534 tok/s | chat |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 46.8 GB | – | 23tok/sest. | 3599 tok/s | chat |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | offload | 52.5 GB | – | 10tok/sest. | 1187 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.0 GB | – | 31tok/sest. | 2052 tok/s | chat, coding |
| GLM 4.5 Air Z.ai | Q2_K | offload | 45.0 GB | – | 8tok/sest. | 725 tok/s | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 46.8 GB | – | 30tok/sest. | 4526 tok/s | chat, coding |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 34.0 GB | – | 31tok/sest. | 5728 tok/s | chat, coding, long documents |
| Llama 3.3 70B Meta | Q4_K_M | offload | 43.4 GB | – | 3tok/sest. | 211 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 92.2 GB | – | – | – | – |
| GLM 5.3 Flash Z.ai | UD-Q2_K_XL | won't run | 102.8 GB | – | – | – | – |
| Qwen 3.8 Flash Next Alibaba Qwen | UD-Q2_K_XL | won't run | 75.1 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 73.4 GB | – | – | – | – |
| gpt-oss 120B OpenAI | MXFP4 | won't run | 60.7 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