Intel Arc A770 16GB vs NVIDIA GeForce RTX 5080
For running models locally, priced in the UK. At 128k context the first runs 22 models fully in memory, the second 23.
In short
Both have 16 GB of memory for models; the Intel Arc A770 16GB has 560 GB/s of bandwidth and the NVIDIA GeForce RTX 5080 960 GB/s. At 128k context the NVIDIA GeForce RTX 5080 runs 23 of the models we track fully in memory and the Intel Arc A770 16GB 22; only the NVIDIA GeForce RTX 5080 holds gpt-oss 20B. On the models both run fully in memory, the NVIDIA GeForce RTX 5080 is about 2.1× as fast as the Intel Arc A770 16GB (estimated, median across models). In the UK the Intel Arc A770 16GB costs £1,354 at Amazon and the NVIDIA GeForce RTX 5080 £1,372 at Amazon: the Intel Arc A770 16GB is £18 cheaper.
Updated . Speeds are estimates; how they are worked out.
Specifications
| Spec | Intel Arc A770 16GB | NVIDIA GeForce RTX 5080 |
|---|---|---|
| GPU | Arc A770 16GB | GeForce RTX 5080 |
| Memory | 16 GB GDDR6 | 16 GB GDDR7 |
| Memory bus | 256-bit | 256-bit |
| Memory bandwidth | 560 GB/s | 960 GB/s |
| FP16 compute | 131 TFLOPS | 113 TFLOPS |
| Software | SYCL / oneAPI | CUDA |
| Board power | 225 W | 360 W |
| PCIe generation | Gen 4 | Gen 5 |
| PCIe lanes | x16 | x16 |
What each runs
Estimated decode speed with the most precise quant that fits each one est.
| Model | Intel Arc A770 16GB | NVIDIA GeForce RTX 5080 |
|---|---|---|
| gpt-oss 20B | offload | 64tok/sQ4_K_M |
| Gemma 4 12B | 23tok/sQ6_K | 49tok/sQ6_K |
| Qwen 3.5 9B | 20tok/sQ8_0 | 43tok/sQ8_0 |
| Qwen 3.5 4B | 32tok/sQ8_0 | 67tok/sQ8_0 |
| Gemma 4 E4B | 23tok/sQ8_0 | 50tok/sQ8_0 |
| LFM2.5 8B-A1B | 21tok/sUD-Q6_K | 49tok/sUD-Q6_K |
| Qwen2.5 0.5B | 131tok/sQ8_0 | 278tok/sQ8_0 |
| Qwen3.5 0.8B | 115tok/sQ8_0 | 244tok/sQ8_0 |
| Qwen3.5 2B | 91tok/sQ5_K_M | 194tok/sQ5_K_M |
| LFM3 1.7B | 81tok/sQ8_0 | 172tok/sQ8_0 |
| DeepSeek R1 Distill Qwen 1.5B | 50tok/sQ8_0 | 105tok/sQ8_0 |
| Mellum2.1 12B A2.5B Thinking | 36tok/sQ6_K | 78tok/sQ8_0 |
| Spark X2.5 4B | 35tok/smlx-4bit | 75tok/smlx-4bit |
| MiniCPM5 2B | 34tok/sQ8_0 | 72tok/sQ8_0 |
| FrogNano 4B 2609 | 31tok/sQ8_0 | 66tok/sQ8_0 |
| Kimi VL A3B Thinking 2506 | 26tok/sQ4_K_M | 60tok/sQ4_K_M |
| LFM2.5 2.6B | 26tok/sQ8_0 | 55tok/sQ8_0 |
| LFM2.5 VL 3B | 26tok/sQ8_0 | 55tok/sQ8_0 |
| GLM 4.6V Flash | 24tok/sQ4_K_M | 52tok/sQ4_K_M |
| GLM 4 9B 0414 | 21tok/smlx-5bit | 44tok/smlx-5bit |
| DeepSeek R1 Distill Qwen 7B | 20tok/sQ6_K | 43tok/sQ6_K |
| granite vision 4.1 4b | 20tok/sQ8_0 | 42tok/sQ8_0 |
| granite 4.2 3b | 19tok/sQ8_0 | 41tok/sQ8_0 |
| Qwen 3.8 27B | offload | offload |
| Qwen 3.6 27B | offload | offload |
| Gemma 4 31B | offload | offload |
| Qwen 3.6 35B-A3B | offload | offload |
| Qwen 3.5 27B | offload | offload |
| Gemma 4 26B-A4B | offload | offload |
| Qwen 3.5 35B-A3B | offload | offload |
| GLM 4.7 Flash | offload | offload |
| Devstral Small 2 24B | offload | offload |
| Nemotron 3.5 Lightning 30B-A3B | offload | offload |
| Kimi Linear 48B-A3B | offload | offload |
| Qwen3 Coder 30B-A3B | offload | offload |
| Gemma 3 27B | offload | offload |
| Mistral Small 3.2 24B | offload | offload |
| Ministral 3 14B | offload | offload |
| Qwen3 14B | offload | offload |
| DeepSeek R1 0528 Qwen3 8B | offload | offload |
| Qwen3 8B | offload | offload |
| Phi-4 14B | offload | offload |
| Ministral 3 8B | offload | offload |
| Granite 4.2 8B | offload | offload |
| Llama 3.1 8B | offload | offload |
| Kimi VL A3B | offload | offload |
| Ministral 3 3B Instruct 2512 | offload | offload |
| GLM 4.1V 9B Thinking | offload | offload |
| Muse Glimmer 30B | offload | offload |
| DeepSeek R1 Distill Llama 8B | offload | offload |
| Ministral 3 8B Reasoning 2512 | offload | offload |
| LFM2.5 24B A2B | offload | offload |
| Qwen3.8 27B OBLITERATED | offload | offload |
| Ministral 3 14B Reasoning 2512 | offload | offload |
| DeepSeek R1 Distill Qwen 14B | offload | offload |
| Devstral Small 2507 | offload | offload |
| Magistral Small 2506 | offload | offload |
| Magistral Small 2507 | offload | offload |
| Magistral Small 2509 | offload | offload |
| DeepSeek V4 Flash | won't run | won't run |
| GLM 5.3 Flash | won't run | won't run |
| Qwen 3.8 Flash Next | won't run | won't run |
| MiniMax M2.7 | won't run | won't run |
| Qwen 3.5 122B-A10B | won't run | won't run |
| Nemotron 3 Super 120B-A12B | won't run | won't run |
| Qwen3 Coder Next | won't run | won't run |
| gpt-oss 120B | won't run | won't run |
| Mistral Small 4 119B | won't run | won't run |
| GLM 4.5 Air | won't run | won't run |
| Qwen3 Next 80B-A3B | won't run | won't run |
| Qwen3 32B | won't run | won't run |
| DeepSeek R1 Distill Qwen 32B | won't run | won't run |
| Llama 3.3 70B | won't run | won't run |
| DeepSeek R1 | won't run | won't run |
| DeepSeek R1 0528 | won't run | won't run |
| DeepSeek R1 Distill Llama 70B | won't run | won't run |
| DeepSeek R1 Zero | won't run | won't run |
| DeepSeek V3 | won't run | won't run |
| DeepSeek V3 0324 | won't run | won't run |
| DeepSeek V3.1 | won't run | won't run |
| DeepSeek V3.1 Terminus | won't run | won't run |
| DeepSeek V3.2 | won't run | won't run |
| DeepSeek V4 Flash 0731 | won't run | won't run |
| DeepSeek V4 Flash Vision Exp | won't run | won't run |
| Devstral 2 123B Instruct 2512 | won't run | won't run |
| GLM 4.5 | won't run | won't run |
| GLM 4.5V | won't run | won't run |
| GLM 4.6 | won't run | won't run |
| GLM 4.6V | won't run | won't run |
| GLM 4.7 | won't run | won't run |
| GLM 5 | won't run | won't run |
| GLM 5.1 | won't run | won't run |
| GLM 5.2 | won't run | won't run |
| GLM 5.3 | won't run | won't run |
| Kimi Dev 72B | won't run | won't run |
| Kimi K2 | won't run | won't run |
| Kimi K2 Instruct 0905 | won't run | won't run |
| Kimi K2 Thinking | won't run | won't run |
| Kimi K2.5 | won't run | won't run |
| MiniMax M2 | won't run | won't run |
| MiniMax M2.1 | won't run | won't run |
| MiniMax M2.5 | won't run | won't run |
| MiniMax M3 | won't run | won't run |
| Mistral Medium 3.5 128B | won't run | won't run |
| granite 4.2 30b | won't run | won't run |
Questions
- Which is better for local AI, the Intel Arc A770 16GB or the NVIDIA GeForce RTX 5080?
- Choose the NVIDIA GeForce RTX 5080 to run bigger models. Choose the NVIDIA GeForce RTX 5080 for speed. Choose the Intel Arc A770 16GB to spend less.
- Which can run bigger models, the Intel Arc A770 16GB or the NVIDIA GeForce RTX 5080?
- At 128k context the NVIDIA GeForce RTX 5080 runs 23 of the models we track fully in memory and the Intel Arc A770 16GB 22; only the NVIDIA GeForce RTX 5080 holds gpt-oss 20B.
- Which is faster for local AI, the Intel Arc A770 16GB or the NVIDIA GeForce RTX 5080?
- On the models both run fully in memory, the NVIDIA GeForce RTX 5080 is about 2.1× as fast as the Intel Arc A770 16GB (estimated, median across models).
- What is the price difference between the Intel Arc A770 16GB and the NVIDIA GeForce RTX 5080?
- In the UK the Intel Arc A770 16GB costs £1,354 at Amazon and the NVIDIA GeForce RTX 5080 £1,372 at Amazon: the Intel Arc A770 16GB is £18 cheaper.
More comparisons
- Intel Arc A770 16GB vs Intel Arc B580
- Intel Arc A770 16GB vs Intel Arc Pro B60
- Intel Arc A770 16GB vs NVIDIA GeForce RTX 3090
- Intel Arc A770 16GB vs NVIDIA GeForce RTX 4070 Ti Super
- Intel Arc A770 16GB vs NVIDIA GeForce RTX 4080 Super
- Intel Arc A770 16GB vs NVIDIA GeForce RTX 5060 Ti 16GB
- Intel Arc A770 16GB vs NVIDIA GeForce RTX 5070 Ti
- Intel Arc A770 16GB vs AMD Radeon RX 7800 XT
- Intel Arc A770 16GB vs AMD Radeon RX 9070
- NVIDIA GeForce RTX 3090 vs NVIDIA GeForce RTX 5080