Desktop GPU · Intel
What AI models can an Arc A750 run?
8 GB is the awkward size. It runs the 7 to 9 billion parameter class comfortably and hits a wall immediately above it, so most of the decisions here are about context length rather than model choice. At 512 GB/s there is enough bandwidth to keep generation responsive for anything that fits.
The short answer
Assuming an 8k context window and default settings, these are the models worth downloading first.
Best all-rounder
Qwen3.5 9B
Q5_K_M · 6.42 GB · about 48.3 tokens/s
Best for code
Qwen2.5 Coder 7B Instruct
Q6_K · 6.23 GB · about 49.8 tokens/s
Largest that still runs well
Mistral Nemo Instruct 2407
12.25B parameters · Q3_K_M · about 44.6 tokens/s
Fastest useful answer
LFM2.5 8B A1B
about 130.5 tokens/s · 6.9 GB
See how fast it feels
Arc A750 running Qwen3.5 9B at Q5_K_M
YouWhy does my model use more memory when the conversation gets longer?
Reading your question
Simulated from our estimate at a 512-token question, not a recording. Assumes nothing else is competing for the GPU.
Where it sits
With 8 GB it belongs to the 8 GB tier. The 8 GB guide explains what that tier runs and where it runs out, and the bandwidth guide explains why 512 GB/s decides how fast it answers.
Our indicative price for this card is $200 used, reviewed 2026-09-01. That is 4.0 GB of memory and 256 GB/s of bandwidth for every $100. Prices move, so treat these as a place to start a search and not a quote.
Devices in a similar price band, fastest memory first:
| Device | Price | Memory | Bandwidth | Best all-round pick |
|---|---|---|---|---|
| GeForce RTX 2080 Ti | $250 used | 11 GB | 616 GB/s | Qwen3.5 9B, 51.3 t/s |
| GeForce GTX 1080 Ti | $150 used | 11 GB | 484 GB/s | Qwen3.5 9B, 40.3 t/s |
| GeForce RTX 3060 Ti | $230 used | 8 GB | 448 GB/s | Qwen3.5 9B, 54.8 t/s |
| Radeon RX 6700 XT | $250 used | 12 GB | 384 GB/s | Gemma 4 12B Instruct, 22.9 t/s |
Every model, scored on this device
Each row uses the highest-quality quantization that both fits and stays conversational. Speed is a single-stream estimate at 8k context.
| Model | Params | Verdict | Download | Memory used | Speed | Max context |
|---|---|---|---|---|---|---|
| Qwen3.5 9B Qwen | 9.65B | Just fits | Q5_K_M | 6.42 GB | 48.3 t/s | 32k |
| Gemma 4 E4B Instruct Gemma | 8B | Just fits | Q6_K | 6.61 GB | 46.5 t/s | 32k |
| Qwen2.5 VL 7B Instruct Qwen | 8.29B | Just fits | Q6_K | 6.74 GB | 45.8 t/s | 16k |
| Qwen3 8B Qwen | 8.19B | Just fits | Q5_K_M | 6.54 GB | 47.4 t/s | 8k |
| Qwen2.5 7B Instruct Qwen | 7.62B | Just fits | Q6_K | 6.23 GB | 49.8 t/s | 16k |
| Llama 3.1 8B Instruct Llama | 8.03B | Just fits | Q6_K | 7.14 GB | 43.2 t/s | 8k |
| Gemma 4 12B Instruct Gemma | 11.96B | Just fits | Q3_K_M | 7.16 GB | 43.1 t/s | 8k |
| Granite 4.1 8B Granite | 8.79B | Just fits | Q4_K_M | 6.6 GB | 47 t/s | 8k |
| Qwen2.5 Coder 7B Instruct Qwen | 7.62B | Just fits | Q6_K | 6.23 GB | 49.8 t/s | 16k |
| Internlm3 8B Instruct InternLM | 8.8B | Just fits | Q6_K | 7.1 GB | 43.5 t/s | 8k |
| Mistral 7B Instruct V0.3 Mistral | 7.25B | Just fits | Q6_K | 6.84 GB | 45.2 t/s | 8k |
| Gemma 4 E2B Instruct Gemma | 5.12B | Runs great | Q8_0 | 5.44 GB | 56.8 t/s | 128k |
| Qwen3.5 4B Qwen | 4.66B | Runs great | Q8_0 | 5.27 GB | 59.3 t/s | 64k |
| Gemma 3 12B Instruct Gemma | 12.19B | Just fits | Q3_K_M | 6.76 GB | 45.7 t/s | 8k |
| Mistral 7B Instruct V0.2 Mistral | 7.24B | Just fits | Q6_K | 6.83 GB | 45.2 t/s | 8k |
| OLMo 3 7B Instruct OLMo | 7.3B | Just fits | Q4_K_M | 6.78 GB | 45.6 t/s | 8k |
| Gemma 2 9B Instruct Gemma | 9.24B | Just fits | IQ4_XS | 6.93 GB | 44.5 t/s | 8k |
| Qwen3 14B Qwen | 14.77B | Fits only at 2 to 3 bits | IQ3_XXS ! | 6.67 GB | 46.7 t/s | 8k |
| Mistral Nemo Instruct 2407 Mistral | 12.25B | Just fits | Q3_K_M | 6.96 GB | 44.6 t/s | 8k |
| Qwen2.5 14B Instruct Qwen | 14.77B | Fits only at 2 to 3 bits | IQ3_XXS ! | 6.92 GB | 44.9 t/s | 8k |
| LFM2.5 8B A1B Liquid | 8.47B (1.57B active) | Just fits | Q6_K | 6.9 GB | 130.5 t/s | 32k |
| Qwen2.5 Coder 14B Instruct Qwen | 14.77B | Fits only at 2 to 3 bits | IQ3_XXS ! | 6.92 GB | 44.9 t/s | 8k |
| Qwen3 4B Qwen | 4.02B | Runs great | Q8_0 | 5.46 GB | 57 t/s | 16k |
| Phi 4 Phi | 14.66B | Fits only at 2 to 3 bits | IQ3_XXS ! | 7.04 GB | 44.1 t/s | 8k |
| Gemma 3 4B Instruct Gemma | 4.3B | Runs great | Q8_0 | 4.91 GB | 63.9 t/s | 64k |
| Phi 4 Mini Instruct Phi | 3.84B | Runs great | Q8_0 | 5.17 GB | 60.6 t/s | 16k |
| Granite 4.1 3B Granite | 3.4B | Runs great | Q8_0 | 4.34 GB | 72.9 t/s | 32k |
| Qwen2.5 3B Instruct Qwen | 3.09B | Runs great | Q8_0 | 3.68 GB | 87.1 t/s | 32k |
| Phi 3 Mini 4k Instruct Phi | 3.82B | Runs great | Q8_0 | 4.8 GB | 65.6 t/s | 4k |
| DeepSeek Coder 7B Instruct V1.5 DeepSeek | 6.91B | Just fits | Q3_K_M | 7.11 GB | 43.4 t/s | 4k |
Show the other 56 models
| Llama 3.2 3B Instruct | 3.21B | Runs great | Q8_0 | 4.42 GB | 71.8 t/s | 32k |
| LFM2.5 2.6B | 2.7B | Runs great | Q8_0 | 3.14 GB | 104 t/s | 128k |
| Qwen3.5 2B | 2.27B | Runs great | Q8_0 | 2.7 GB | 123.3 t/s | 256k |
| Gemma 2 2B Instruct | 2.61B | Runs great | Q8_0 | 3.54 GB | 91.1 t/s | 8k |
| Starcoder2 3B | 3.03B | Runs great | Q8_0 | 3.34 GB | 98.1 t/s | 16k |
| Qwen3 1.7B | 2.03B | Runs great | Q8_0 | 3.22 GB | 100.9 t/s | 32k |
| DeepSeek Coder 6.7B Instruct | 6.74B | Fits only at 2 to 3 bits | IQ3_XXS | 6.76 GB | 45.8 t/s | 8k |
| Mistral Small 24B Instruct 2501 | 23.57B | Fits only at 2 to 3 bits | IQ2_XXS | 7.18 GB | 43.1 t/s | 8k |
| DeepSeek R1 Distill Qwen 1.5B | 1.78B | Runs great | Q8_0 | 2.07 GB | 166.3 t/s | 128k |
| Qwen2.5 1.5B Instruct | 1.54B | Runs great | Q8_0 | 2.06 GB | 166.9 t/s | 32k |
| SmolLM2 1.7B | 1.71B | Runs great | Q8_0 | 3.53 GB | 91.1 t/s | 8k |
| OLMo 2 0425 1B | 1.48B | Runs great | Q8_0 | 2.6 GB | 128.6 t/s | 4k |
| Llama 3.2 1B Instruct | 1.24B | Runs great | Q8_0 | 1.82 GB | 196.9 t/s | 128k |
| LFM2.5 1.2B Instruct | 1.17B | Runs great | Q8_0 | 1.46 GB | 260 t/s | 64k |
| Gemma 3 1B Instruct | 1B | Runs great | Q8_0 | 1.35 GB | 280 t/s | 32k |
| Qwen3.5 0.8B | 0.87B | Runs great | Q8_0 | 1.28 GB | 299 t/s | 256k |
| Qwen3 0.6B | 0.75B | Runs great | Q8_0 | 1.92 GB | 179.9 t/s | 32k |
| Qwen2.5 0.5B Instruct | 0.49B | Runs great | Q8_0 | 0.88 GB | 502.7 t/s | 32k |
| LFM2.5 350M | 0.35B | Runs great | Q8_0 | 0.68 GB | 778.4 t/s | 64k |
| DeepSeek Coder V2 Lite Instruct | 15.71B | Partial offload | n/a | 9.29 GB | 65.7 t/s | n/a |
| Qwen3.5 35B A3B | 35.95B | Partial offload | n/a | 20.48 GB | 48.4 t/s | n/a |
| GPT OSS 20B | 20.91B | Partial offload | n/a | 11.55 GB | 36 t/s | n/a |
| Qwen3 Coder Next | 79.67B | Partial offload | n/a | 45.22 GB | 31.7 t/s | n/a |
| Gemma 4 26B A4B Instruct | 25.81B | Partial offload | n/a | 15.7 GB | 31.3 t/s | n/a |
| Qwen3 Next 80B A3B Instruct | 81.32B | Partial offload | n/a | 46.15 GB | 31.2 t/s | n/a |
| GLM 4.7 Flash | 31.22B | Partial offload | n/a | 18.13 GB | 30.9 t/s | n/a |
| Qwen3 30B A3B | 30.53B | Partial offload | n/a | 18.08 GB | 30.1 t/s | n/a |
| Qwen3 Coder 30B A3B Instruct | 30.53B | Partial offload | n/a | 18.08 GB | 30.1 t/s | n/a |
| GPT OSS 120B | 116.83B | Partial offload | n/a | 59.4 GB | 16.2 t/s | n/a |
| Qwen3.5 122B A10B | 125.09B | Partial offload | n/a | 70.61 GB | 12.3 t/s | n/a |
| Phi 3.5 MoE Instruct | 41.87B | Partial offload | n/a | 24.87 GB | 11.3 t/s | n/a |
| GLM 4.5 Air | 110.47B | Partial offload | n/a | 63.61 GB | 6.8 t/s | n/a |
| MiniMax M2.5 | 228.7B | Partial offload | n/a | 130.56 GB | 6.6 t/s | n/a |
| MiniMax M2.7 | 228.69B | Partial offload | n/a | 130.55 GB | 6.6 t/s | n/a |
| Mixtral 8x7B Instruct V0.1 | 46.7B | Partial offload | n/a | 27.59 GB | 5.3 t/s | n/a |
| Codestral 22B V0.1 | 22.25B | Partial offload | n/a | 14.62 GB | 3.6 t/s | n/a |
| Qwen3 235B A22B | 235.09B | Partial offload | n/a | 133.71 GB | 3.4 t/s | n/a |
| Qwen3.5 27B | 27.78B | Partial offload | n/a | 15.99 GB | 3.1 t/s | n/a |
| Gemma 3 27B Instruct | 27.43B | Partial offload | n/a | 16.96 GB | 2.8 t/s | n/a |
| Granite 4.1 30B | 28.87B | Partial offload | n/a | 18.64 GB | 2.4 t/s | n/a |
| Qwen3 32B | 32.76B | Partial offload | n/a | 20.42 GB | 2.1 t/s | n/a |
| Qwen2.5 32B Instruct | 32.76B | Partial offload | n/a | 20.42 GB | 2.1 t/s | n/a |
| Qwen2.5 Coder 32B Instruct | 32.76B | Partial offload | n/a | 20.42 GB | 2.1 t/s | n/a |
| MiniMax M3 | 427.04B | Partial offload | n/a | 240.84 GB | 2 t/s | n/a |
| Gemma 4 31B Instruct | 31.27B | Partial offload | n/a | 21.31 GB | 2 t/s | n/a |
| GLM 5.1 | 753.86B | Partial offload | n/a | 424.51 GB | 1.5 t/s | n/a |
| DeepSeek V3.2 | 685.4B | Partial offload | n/a | 385.91 GB | 1.4 t/s | n/a |
| DeepSeek R1 | 684.53B | Partial offload | n/a | 385.42 GB | 1.4 t/s | n/a |
| GLM 4.5 | 358.34B | Partial offload | n/a | 204.37 GB | 1.4 t/s | n/a |
| GLM 5.2 | 753.33B | Partial offload | n/a | 424.21 GB | 1 t/s | n/a |
| Qwen2.5 VL 72B Instruct | 73.41B | Partial offload | n/a | 43.62 GB | 0.8 t/s | n/a |
| Qwen2.5 72B Instruct | 72.71B | Partial offload | n/a | 43.22 GB | 0.8 t/s | n/a |
| Llama 3.3 70B Instruct | 70.55B | Partial offload | n/a | 42.12 GB | 0.8 t/s | n/a |
| Llama 3 3 Nemotron Super 49B V1 | 49.87B | Partial offload | n/a | 47.99 GB | 0.7 t/s | n/a |
| Kimi K2.6 | 1026.88B | Will not run | n/a | 577.78 GB | 1.3 t/s | n/a |
| Kimi K2 Instruct | 1026.41B | Will not run | n/a | 577.52 GB | 1.3 t/s | n/a |
What it will not run
2 of the 86 architectures we track are out of reach here, even at 2-bit precision. Another 35 run by splitting the model between the card and system RAM, which works but drops generation to single digits for most dense models.
If you want more headroom
The next steps up in memory, in order. More memory changes which models load at all; more bandwidth changes how fast they answer, so the two are worth weighing separately.
| Device | Memory | Bandwidth | Models that fit | |
|---|---|---|---|---|
| GeForce RTX 3080 10GB | 10 GB | 760 GB/s | 53 | Check price |
| Arc B570 | 10 GB | 380 GB/s | 53 | Check price |
| GeForce RTX 2080 Ti | 11 GB | 616 GB/s | 57 | Check price |
| GeForce GTX 1080 Ti | 11 GB | 484 GB/s | 57 | Check price |
Price links go to an Amazon search for the model name and are affiliate links: if you buy through one, we earn a commission at no cost to you. We do not take payment for placement, and the ordering above is by memory capacity alone.
Other devices with 8 GB
Same capacity, different speed. Once a model fits, bandwidth is what separates these.
Questions people ask about an Arc A750
How much VRAM does an Arc A750 have?
The Arc A750 has 8 GB of VRAM, of which roughly 7.2 GB is available to a model once the operating system takes its share.
Can an Arc A750 run a 70B model?
Only partially. About 48 of 48 layers fit on the card and the rest run on the CPU, which brings generation down to roughly 31.7 tokens per second.
What is the best local model for an Arc A750?
Qwen3.5 9B at Q5_K_M is the strongest all-round fit: 6.42 GB used, around 48.3 tokens per second at 8k context.