Chat
SQwen 3.5 4B
This 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, lm-studio.
AMD
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 RX 9060 8GB is an entry-level RDNA 4 card, AMD's newest consumer architecture as of 2025. RDNA 4 is expected to have ROCm support but the ecosystem is still early — driver stability and framework compatibility should be verified before assuming production-ready AI use. Its 8 GB of GDDR6 VRAM limits it to smaller models, but the RDNA 4 architecture brings improved compute efficiency over RDNA 3.
Beyond LLMs
What AI tasks this GPU can handle — from text generation to image and video creation.
| Capability | Status | Representative Model |
|---|---|---|
| LLM Chat (7B) | Runs natively | 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) | Runs with sequential offload | SDXL 1.0 FP16 |
| Image Gen (Flux) | Won't fit | Flux.1 Dev FP16 |
| Image Gen (SD 3.5) | Won't fit | SD 3.5 Large FP16 |
| Video Short (25f) | Won't fit | LTX Video 2B |
| Video Long (100f) | Won't fit | Wan Video 14B |
Architecture
RDNA 4 is AMD's latest GPU architecture built on TSMC 4nm. It focuses on efficiency and ray tracing improvements with enhanced AI processing capabilities.
AI Relevance
Improved ROCm support and new AI accelerators with FP8 support bring AMD closer to competitive AI inference performance. The focus on efficiency makes RDNA 4 GPUs attractive for power-constrained deployments.
Conselho de compra
Utilizável para IA local com limitações
Pode rodar 7 de 50 modelos principais, principalmente os menores. Modelos maiores precisam de quantização forte ou não cabem.
8.0 GB
VRAM
$249
Preço sugerido
$31/GB
Custo por GB de VRAM
Melhores modelos para esta GPU
What will limit you first
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
Best upgrade itinerary
Unlocks 33 additional models that do not fit on the current setup.
Quer mais margem? RTX 3080 10GB (10.0 GB VRAM) é o próximo passo.
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, lm-studio.
Coding
SThis model is a direct match for coding. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. 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 fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.
Reasoning
SThis model is a direct match for reasoning. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama.
RAG
AThis model is a direct match for rag. It sits in the middle of the current model mix. It fits natively with comfortable headroom. Known channels: huggingface, ollama.
Quase ao alcance
Modelos de alta qualidade que precisam de um pouco mais de memória
Image & Video Generation
21 of 52 models can generate images or video on your RX 9060 8GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | ~1.1s | S |
| Stable Diffusion 1.5Image | 512×768 | ~2.2s | S |
| Realistic Vision v5.1Image | 512×768 | ~2.2s | S |
| DreamShaper 8Image | 512×768 | ~2.2s | S |
| LCM DreamShaper v7Image | 512×768 | 700ms | S |
| PixArt-SigmaImage | 256×256 | ~8.8s | S |
| FramePack I2VVideo | 256×256 | ~16.1s/frame | A |
| SDXL TurboImage | 256×256 | ~2.9s | A |
| SDXL LightningImage | 256×256 | ~8.8s | B |
| Stable Diffusion XL 1.0Image | 256×256 | ~23.3s | B |
| Playground v2.5Image | 256×256 | ~13.2s | B |
| RealVisXL v5.0Image | 256×256 | ~26.3s | B |
| DreamShaper XLImage | 256×256 | ~26.3s | B |
| Juggernaut XL v9Image | 256×256 | ~26.3s | B |
| Animagine XL 3.1Image | 256×256 | ~26.3s | B |
| Pony Diffusion V6 XLImage | 256×256 | ~26.3s | B |
| Animagine XL 4.0Image | 256×256 | ~26.3s | B |
| Illustrious XLImage | 256×256 | ~26.3s | B |
| Wan Video 2.1 1.3BVideo | 256×256 | ~6.4s/frame | D |
| Stable Diffusion 3.5 MediumImage | 256×256 | ~15.4s | D |
| Flux.2 Klein 4BImage | 256×256 | ~2.6s | D |
| LTX Video 2BVideo | 256×256 | ~7.6s/frame | F |
| KolorsImage | 256×256 | ~17.6s | F |
| Stable CascadeImage | 256×256 | ~22s | F |
| AuraFlow v0.3Image | 256×256 | ~39.6s | F |
| Stable Diffusion 3.5 LargeImage | 256×256 | ~48.4s | F |
| Stable Diffusion 3.5 Large TurboImage | 256×256 | ~8.8s | F |
| CogVideoX 2BVideo | 256×256 | ~7.6s/frame | F |
| HunyuanVideoVideo | 256×256 | ~16.1s/frame | F |
| ChromaImage | 256×256 | ~8.8s | F |
| Z-Image TurboImage | 256×256 | ~9.1s | F |
| Flux.1 DevImage | 256×256 | ~39.6s | F |
| Flux.1 SchnellImage | 256×256 | ~7.7s | F |
| LTX Video 13BVideo | 256×256 | ~16.1s/frame | F |
| Flux.1 Kontext DevImage | 256×256 | ~44s | F |
| AnimateDiff v1.5.3Video | 512×768 | ~4s/frame | F |
| Cosmos Diffusion 7BVideo | 256×256 | ~12.6s/frame | F |
| CogVideoX 5BVideo | 256×256 | ~11s/frame | F |
| Wan2.2 TI2V 5BVideo | 256×256 | ~11s/frame | F |
| Flux.2 Klein 9BImage | 256×256 | ~4.4s | F |
| Flux.1 Fill DevImage | 256×256 | ~37.4s | F |
| Mochi 1 PreviewVideo | 256×256 | ~14.5s/frame | F |
| HunyuanVideo 1.5Video | 256×256 | ~13.5s/frame | F |
| Helios 14BVideo | 256×256 | ~16.6s/frame | F |
| SkyReels V2 14BVideo | 256×256 | ~16.6s/frame | F |
| Wan Video 2.1 14BVideo | 256×256 | ~16.6s/frame | F |
| Wan Video 2.2 14BVideo | 256×256 | ~16.6s/frame | F |
| Qwen ImageImage | 256×256 | ~14.8s | F |
| Qwen Image EditImage | 256×256 | ~14.8s | F |
| Flux.2 DevImage | 256×256 | ~6m 56s | F |
| MAGI-1Video | 256×256 | ~20.6s/frame | F |
| HunyuanImage 3.0Image | 256×256 | ~26.1s | 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
Opções de upgrade
Unlocks 33 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 75%.
~$699 MSRP
Unlocks 37 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 27%.
~$449 MSRP
Unlocks 74 additional models that do not fit on the current setup.
~$329 MSRP
Unlocks 155 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 335%.
~$8,000 MSRP
RX 9060 8GB (8 GB VRAM) can run these top models: Qwen 3.5 4B (score: 95/100), Phi-4 Mini Reasoning 4B (score: 92/100), Jina Embeddings v3 (score: 84/100). See the full compatibility list above.
RX 9060 8GB has 8 GB of VRAM available for AI model inference. This determines which models and quantization levels you can run locally.
Yes, RX 9060 8GB is excellent for running LLMs locally with top compatibility scores above 80/100.
For coding on RX 9060 8GB, we recommend Qwen 3.5 4B. It achieves 56.0 tokens per second with 28K context window. This model is a direct match for coding. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.
There are 4 upgrade path(s) from RX 9060 8GB: RTX 3080 10GB, RX 7700 XT 12GB. Upgrading would unlock larger models and faster inference speeds.
Flux.1 Dev requires around 24 GB of usable memory at FP16. With 8 GB, RX 9060 8GB cannot run Flux natively. Consider quantized GGUF variants or the smaller Schnell model with aggressive offloading.
RX 9060 8GB (8 GB VRAM) can handle various AI generation tasks beyond LLMs. For image generation, SDXL and Stable Diffusion 3.5 run well. For video, video generation is limited by available memory. Check the AI Capability Matrix above for detailed compatibility.
RX 9060 8GB can handle basic AI image generation with SDXL and SD 1.5. With 8 GB of usable memory, larger models like Flux will need quantization or offloading. Best suited for standard resolution (512-1024px) generation.
Qwen 3.5 27B does not fit on RX 9060 8GB with 8 GB. However, Qwen 3.5 9B at Q4 (5.5 GB) or Q5 (6.5 GB) runs well on your GPU. The 4B variant fits at Q8 for near-lossless quality.
With 8 GB on RX 9060 8GB, use Q4_K_M for 8B models and Q4_K_M with tight context for 14B models. Q5_K_M is a good middle ground when the model fits. For the best quality-to-size ratio, Q4_K_M is the most popular choice.
On RX 9060 8GB, capacity is usually the first gate: if the model does not fit, bandwidth does not matter. But once a model fits, memory bandwidth is what largely determines tokens per second. In practice, you want enough memory to fit the model plus headroom, then as much bandwidth as your budget allows.
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