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Intel
Operating mode
Use this to bias workload recommendations toward responsiveness, background autonomy, lighter serving, or multi-GPU scale-out.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
The Arc Pro A40 6GB is Intel's entry workstation GPU based on the Alchemist architecture, targeting small-form-factor workstations and professional visualization on a budget. With only 6 GB of GDDR6 its AI inference capability is limited to 3B models at FP16 or 7B at Q4 with possible CPU offloading. The workstation-certified driver stack improves stability compared to consumer Arc, but the low VRAM makes it a marginal choice for LLM workloads beyond light experimentation.
Beyond LLMs
What AI tasks this GPU can handle — from text generation to image and video creation.
| Capability | Status | Representative Model | Detail |
|---|---|---|---|
| LLM Chat (7B) | Needs offload | Llama 3.1 8B Q4 | — |
| LLM Coding (30B) | Won’t fit | Qwen 3 30B Q4 | — |
| LLM Large (70B) | Won’t fit | Llama 3.1 70B Q4 | — |
| Image Gen (SDXL) | Very constrained | SDXL 1.0 FP16 | ~~50.9s per image |
| Image Gen (Flux) | Won't fit | Flux.1 Dev FP16 | ~~3m 49s per image |
| Image Gen (SD 3.5) | Won't fit | SD 3.5 Large FP16 | ~~4m 40s per image |
| Video Short (25f) | Won't fit | LTX Video 2B | ~~44.2s/frame |
| Video Long (100f) | Won't fit | Wan Video 14B | ~~2m 10s/frame |
Architecture
Alchemist is Intel's first discrete GPU architecture under the Arc brand, using Xe-HPG cores manufactured on TSMC's N6 process. It features XMX (Xe Matrix Extensions) engines for AI acceleration.
AI Relevance
XMX engines provide some AI inference acceleration via oneAPI/SYCL. However, the software ecosystem for LLM inference on Intel Arc is still developing, with limited runtime support compared to CUDA.
Buying advice
Usable for local AI with limits
Can run 4 of 50 top models, mostly smaller ones. Larger models need heavy quantization or won't fit.
6.0 GB
VRAM
$249
MSRP
$42/GB
Cost per GB VRAM
Best models for this GPU
What will limit you first
The raw memory story may look fine, but the software ecosystem is still a constraint here.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Runtime ecosystem is narrower than CUDA
Intel GPUs can look attractive on memory per dollar, but local AI tooling, kernels, and model coverage are still broader and easier on CUDA today.
Best upgrade itinerary
Prefer CUDA if you want the path of least resistance
If your goal is maximum runtime coverage, easier troubleshooting, and better support for new local AI releases, CUDA is usually still the safer upgrade path.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Unlocks 38 additional models that do not fit on the current setup.
Want more headroom? RTX 3050 8GB (8.0 GB VRAM) is the next step up.
Chat
SThis model is a direct match for chat. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama.
Coding
AThis model is a direct match for coding. It belongs to a current frontier family for local AI. It should run, but memory headroom will be limited. Known channels: huggingface, ollama, lm-studio.
Agentic Coding
AThis model is still usable for agentic-coding, but it is not the most specialized pick. It belongs to a current frontier family for local AI. It should run, but memory headroom will be limited. Known channels: huggingface, ollama, lm-studio.
Reasoning
AThis model is a direct match for reasoning. It belongs to a current frontier family for local AI. It should run, but memory headroom will be limited. Known channels: huggingface, ollama, lm-studio.
RAG
BThis model is a direct match for rag. It sits in the middle of the current model mix. It is likely to require compromise or offload. Known channels: huggingface, ollama.
Just out of reach
High-quality models that need a bit more memory
Image & Video Generation
18 of 52 models can generate images or video on your Intel Arc Pro A40 6GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | ~6.4s | A |
| Stable Diffusion 1.5Image | 512×768 | ~12.7s | B |
| Realistic Vision v5.1Image | 512×768 | ~12.7s | B |
| DreamShaper 8Image | 512×768 | ~12.7s | B |
| LCM DreamShaper v7Image | 512×768 | ~3.8s | B |
| PixArt-SigmaImage | 256×256 | ~50.9s | B |
| FramePack I2VVideo | 256×256 | ~1m 33s/frame | B |
| SDXL TurboImage | 256×256 | ~6.4s | D |
| SDXL LightningImage | 256×256 | ~19.1s | D |
| Stable Diffusion XL 1.0Image | 256×256 | ~50.9s | D |
| Playground v2.5Image | 256×256 | ~1m 16s | D |
| RealVisXL v5.0Image | 256×256 | ~57.2s | D |
| DreamShaper XLImage | 256×256 | ~57.2s | D |
| Juggernaut XL v9Image | 256×256 | ~57.2s | D |
| Animagine XL 3.1Image | 256×256 | ~57.2s | D |
| Pony Diffusion V6 XLImage | 256×256 | ~57.2s | D |
| Animagine XL 4.0Image | 256×256 | ~57.2s | D |
| Illustrious XLImage | 256×256 | ~57.2s | D |
| Wan Video 2.1 1.3BVideo | 256×256 | ~37.2s/frame | F |
| Stable Diffusion 3.5 MediumImage | 256×256 | ~1m 29s | F |
| Flux.2 Klein 4BImage | 256×256 | ~15.3s | F |
| LTX Video 2BVideo | 256×256 | ~44.2s/frame | F |
| KolorsImage | 256×256 | ~1m 42s | F |
| Stable CascadeImage | 256×256 | ~2m 7s | F |
| AuraFlow v0.3Image | 256×256 | ~3m 49s | F |
| Stable Diffusion 3.5 LargeImage | 256×256 | ~4m 40s | F |
| Stable Diffusion 3.5 Large TurboImage | 256×256 | ~50.9s | F |
| CogVideoX 2BVideo | 256×256 | ~44.2s/frame | F |
| HunyuanVideoVideo | 256×256 | ~1m 33s/frame | F |
| ChromaImage | 256×256 | ~50.9s | F |
| Z-Image TurboImage | 256×256 | ~52.5s | F |
| Flux.1 DevImage | 256×256 | ~3m 49s | F |
| Flux.1 SchnellImage | 256×256 | ~44.5s | F |
| LTX Video 13BVideo | 256×256 | ~1m 33s/frame | F |
| Flux.1 Kontext DevImage | 256×256 | ~4m 14s | F |
| AnimateDiff v1.5.3Video | 512×768 | ~23.2s/frame | F |
| Cosmos Diffusion 7BVideo | 256×256 | ~1m 13s/frame | F |
| CogVideoX 5BVideo | 256×256 | ~1m 4s/frame | F |
| Wan2.2 TI2V 5BVideo | 256×256 | ~1m 4s/frame | F |
| Flux.2 Klein 9BImage | 256×256 | ~25.4s | F |
| Flux.1 Fill DevImage | 256×256 | ~3m 36s | F |
| Mochi 1 PreviewVideo | 256×256 | ~1m 24s/frame | F |
| HunyuanVideo 1.5Video | 256×256 | ~1m 18s/frame | F |
| Helios 14BVideo | 256×256 | ~1m 36s/frame | F |
| SkyReels V2 14BVideo | 256×256 | ~1m 36s/frame | F |
| Wan Video 2.1 14BVideo | 256×256 | ~1m 36s/frame | F |
| Wan Video 2.2 14BVideo | 256×256 | ~1m 36s/frame | F |
| Qwen ImageImage | 256×256 | ~1m 26s | F |
| Qwen Image EditImage | 256×256 | ~1m 26s | F |
| Flux.2 DevImage | 256×256 | ~40m 7s | F |
| MAGI-1Video | 256×256 | ~1m 59s/frame | F |
| HunyuanImage 3.0Image | 256×256 | ~2m 31s | F |
Image models estimated at 1024×1024 (28 steps, FP16). Video models estimated at 768×512 (25 frames, 30 steps, FP16). Actual performance varies with runtime and system load.
Upgrade paths
See what you unlock with more powerful hardware
Upgrade options
Unlocks 38 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 29%.
~$249 MSRP
Unlocks 38 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 25%.
Unlocks 112 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 46%.
~$329 MSRP
Unlocks 193 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 659%.
~$8,000 MSRP
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