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 @32k | Prefill | Good for |
|---|---|---|---|---|---|---|---|
| Qwen 3.8 27B Alibaba Qwen | UD-Q6_K | fits | 24.1 GB | 124k217k with q8 cache | 12tok/sest. | 634 tok/s | – |
| Qwen 3.6 27B Alibaba Qwen | Q8_0 | fits | 30.3 GB | 34k59k with q8 cache | 9tok/sest. | 634 tok/s | – |
| Gemma 4 31B | Q6_K | fits | 28.2 GB | 57k110k with q8 cache | 10tok/sest. | 565 tok/s | – |
| Qwen 3.6 35B-A3B Alibaba Qwen | UD-Q6_K | fits | 29.5 GB | 68k107k with q8 cache | 48tok/sest. | 4525 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 27B Alibaba Qwen | Q8_0 | fits | 30.3 GB | 34k59k with q8 cache | 9tok/sest. | 634 tok/s | – |
| Gemma 4 26B-A4B | Q8_0 | fits | 27.3 GB | 153k245k with q8 cache | 31tok/sest. | 4026 tok/s | chat, coding, agents, long documents |
| Qwen 3.5 35B-A3B Alibaba Qwen | Q6_K | fits | 29.0 GB | 85k133k with q8 cache | 49tok/sest. | 4525 tok/s | chat, coding, agents, long documents |
| GLM 4.7 Flash Z.ai | Q6_K | fits | 26.1 GB | 106k183k with q8 cache | 26tok/sest. | 2363 tok/s | chat, coding |
| Devstral Small 2 24B Mistral AI | Q8_0 | fits | 29.8 GB | 35k64k with q8 cache | 9tok/sest. | 669 tok/s | – |
| Kimi Linear 48B-A3B Moonshot AI | Q4_K_M | fits | 29.8 GB | 78k107k with q8 cache | 72tok/sest. | 3900 tok/s | chat, coding, long documents |
| gpt-oss 20B OpenAI | MXFP4 | fits | 13.5 GB | 128k | 48tok/sest. | 3378 tok/s | chat, coding, agents, long documents |
| Qwen3 Coder 30B-A3B Alibaba Qwen | Q6_K | fits | 27.9 GB | 57k102k with q8 cache | 27tok/sest. | 2081 tok/s | chat, coding |
| Qwen3 32B Alibaba Qwen | Q4_K_M | fits | 27.9 GB | 40k | 10tok/sest. | 394 tok/s | – |
| Gemma 4 12B | Q8_0 | fits | 14.1 GB | 256k | 21tok/sest. | 1470 tok/s | chat, coding, long documents |
| Qwen 3.5 9B Alibaba Qwen | Q8_0 | fits | 11.4 GB | 256k | 26tok/sest. | 1832 tok/s | chat, coding, long documents |
| Gemma 3 27B | Q6_K | fits | 25.0 GB | 95k128k with q8 cache | 11tok/sest. | 673 tok/s | – |
| DeepSeek R1 Distill Qwen 32B DeepSeek | Q4_K_M | fits | 28.0 GB | 41k76k with q8 cache | 10tok/sest. | 452 tok/s | – |
| Mistral Small 3.2 24B Mistral AI | Q8_0 | fits | 29.8 GB | 35k64k with q8 cache | 9tok/sest. | 669 tok/s | – |
| Ministral 3 14B Mistral AI | Q8_0 | fits | 19.9 GB | 97k176k with q8 cache | 14tok/sest. | 1017 tok/s | chat |
| Qwen3 14B Alibaba Qwen | Q8_0 | fits | 21.1 GB | 40k | 13tok/sest. | 915 tok/s | chat |
| DeepSeek R1 0528 Qwen3 8B DeepSeek | Q8_0 | fits | 14.1 GB | 128k | 21tok/sest. | 1509 tok/s | chat, coding |
| Qwen3 8B Alibaba Qwen | Q8_0 | fits | 14.1 GB | 40k | 21tok/sest. | 1509 tok/s | chat, coding |
| Phi-4 14B Microsoft | Q8_0 | fits | 22.2 GB | 16k | 13tok/sest. | 920 tok/s | chat |
| Qwen 3.5 4B Alibaba Qwen | Q8_0 | fits | 6.7 GB | 256k | 50tok/sest. | 3427 tok/s | chat, coding, long documents |
| Ministral 3 8B Mistral AI | Q8_0 | fits | 14.1 GB | 149k256k with q8 cache | 21tok/sest. | 1458 tok/s | chat, coding |
| Granite 4.2 8B IBM | Q8_0 | fits | 15.2 GB | 125k128k with q8 cache | 19tok/sest. | 1388 tok/s | chat |
| Gemma 4 E4B | Q8_0 | fits | 10.0 GB | 128k | 31tok/sest. | 2301 tok/s | chat, coding, long documents |
| LFM2.5 8B-A1B Liquid AI | Q8_0 | fits | 11.4 GB | 125k | 58tok/sest. | 7527 tok/s | chat, coding, long documents |
| Llama 3.1 8B Meta | Q6_K | fits | 11.6 GB | 128k | 26tok/sest. | 1594 tok/s | chat, coding |
| Qwen 3.5 122B-A10B Alibaba Qwen | UD-Q2_K_XL | offload | 41.3 GB | – | 17tok/sest. | 1241 tok/s | chat |
| Qwen3 Coder Next Alibaba Qwen | Q4_K_M | offload | 47.5 GB | – | 19tok/sest. | 2783 tok/s | chat |
| Nemotron 3 Super 120B-A12B NVIDIA | UD-Q2_K_XL | offload | 52.8 GB | – | 10tok/sest. | 1109 tok/s | – |
| Mistral Small 4 119B Mistral AI | UD-Q2_K_XL | offload | 39.6 GB | – | 24tok/sest. | 1412 tok/s | chat, coding |
| GLM 4.5 Air Z.ai | Q2_K | offload | 49.4 GB | – | 4tok/sest. | 421 tok/s | – |
| Qwen3 Next 80B-A3B Alibaba Qwen | Q4_K_M | offload | 47.5 GB | – | 23tok/sest. | 3312 tok/s | chat, coding |
| Nemotron 3.5 Lightning 30B-A3B NVIDIA | UD-Q6_K_XL | offload | 34.3 GB | – | 29tok/sest. | 4794 tok/s | chat, coding, long documents |
| Llama 3.3 70B Meta | Q4_K_M | offload | 51.1 GB | – | 2tok/sest. | 160 tok/s | – |
| DeepSeek V4 Flash DeepSeek | UD-Q2_K_XL | won't run | 94.4 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 | 75.8 GB | – | – | – | – |
| MiniMax M2.7 MiniMax | UD-Q2_K_XL | won't run | 79.4 GB | – | – | – | – |
| gpt-oss 120B OpenAI | MXFP4 | won't run | 61.7 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