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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 AMD Instinct MI250X 128GB is the higher-tier CDNA 2 OAM accelerator, featuring the same 128 GB HBM2e as the MI250 but with higher compute throughput (383 vs 362 TFLOPS FP16). It was AMD's primary competitor to the NVIDIA A100 80GB and was widely deployed in HPC clusters. Full ROCm support makes it a production-ready platform for LLM inference, though it has been superseded by the MI300X for new deployments.
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) | Runs natively | Llama 3.1 8B Q4 | — |
| LLM Coding (30B) | Runs natively | Qwen 3 30B Q4 | — |
| LLM Large (70B) | Runs natively | Llama 3.1 70B Q4 | — |
| Image Gen (SDXL) | Runs natively | SDXL 1.0 FP16 | ~800ms per image |
| Image Gen (Flux) | Runs natively | Flux.1 Dev FP16 | ~~3.8s per image |
| Image Gen (SD 3.5) | Runs natively | SD 3.5 Large FP16 | ~~4.6s per image |
| Video Short (25f) | Runs natively | LTX Video 2B | ~700ms/frame |
| Video Long (100f) | Runs natively | Wan Video 14B | ~~2.1s/frame |
Architecture
CDNA 2 powers the Instinct MI210 and MI250/MI250X accelerators. It introduced multi-die packaging with up to 128 GB HBM2e and Infinity Fabric for die-to-die communication.
AI Relevance
With up to 128 GB HBM2e memory and strong ROCm support, CDNA 2 GPUs can host large language models. The MI250X was used in the Frontier exascale supercomputer and supports major AI frameworks.
Buying advice
Excellent choice for local AI
Runs 36 of 50 top models well — a strong all-rounder for local inference.
128.0 GB
VRAM
$15,000
MSRP
$117/GB
Cost per GB VRAM
Best models for this 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 2 additional models that do not fit on the current setup.
Want more headroom? NVIDIA H200 141GB (141.0 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, 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
SThis 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, 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, lm-studio.
RAG
SThis model is a direct match for rag. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, lm-studio.
Just out of reach
High-quality models that need a bit more memory
Image & Video Generation
52 of 52 models can generate images or video on your AMD Instinct MI250X 128GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | 100ms | S |
| Stable Diffusion 1.5Image | 512×768 | 200ms | S |
| Realistic Vision v5.1Image | 512×768 | 200ms | S |
| DreamShaper 8Image | 512×768 | 200ms | S |
| LCM DreamShaper v7Image | 512×768 | 100ms | S |
| PixArt-SigmaImage | 1024×1024 | 800ms | S |
| FramePack I2VVideo | 1280×720 | ~1.5s/frame | S |
| SDXL TurboImage | 512×512 | 100ms | S |
| SDXL LightningImage | 1024×1024 | 300ms | S |
| Stable Diffusion XL 1.0Image | 1024×1024 | 800ms | S |
| Playground v2.5Image | 1024×1024 | ~1.3s | S |
| RealVisXL v5.0Image | 1024×1024 | 900ms | S |
| DreamShaper XLImage | 1024×1024 | 900ms | S |
| Juggernaut XL v9Image | 1024×1024 | 900ms | S |
| Animagine XL 3.1Image | 1024×1024 | 900ms | S |
| Pony Diffusion V6 XLImage | 1024×1024 | 900ms | S |
| Animagine XL 4.0Image | 1024×1024 | 900ms | S |
| Illustrious XLImage | 1024×1024 | 900ms | S |
| Wan Video 2.1 1.3BVideo | 480×832 | 600ms/frame | S |
| Stable Diffusion 3.5 MediumImage | 1024×1024 | ~1.5s | S |
| Flux.2 Klein 4BImage | 1024×1024 | 300ms | S |
| LTX Video 2BVideo | 1280×720 | 700ms/frame | S |
| KolorsImage | 1024×1024 | ~1.7s | S |
| Stable CascadeImage | 1024×1024 | ~2.1s | S |
| AuraFlow v0.3Image | 1536×1536 | ~3.8s | S |
| Stable Diffusion 3.5 LargeImage | 1024×1024 | ~4.6s | S |
| Stable Diffusion 3.5 Large TurboImage | 1024×1024 | 800ms | S |
| CogVideoX 2BVideo | 720×480 | 700ms/frame | S |
| HunyuanVideoVideo | 720×1280 | ~1.5s/frame | S |
| ChromaImage | 1024×1024 | 800ms | S |
| Z-Image TurboImage | 1536×1536 | 900ms | S |
| Flux.1 DevImage | 1024×1024 | ~3.8s | S |
| Flux.1 SchnellImage | 1024×1024 | 700ms | S |
| LTX Video 13BVideo | 1280×720 | ~1.5s/frame | S |
| Flux.1 Kontext DevImage | 1024×1024 | ~4.2s | S |
| AnimateDiff v1.5.3Video | 512×768 | 400ms/frame | S |
| Cosmos Diffusion 7BVideo | 1024×576 | ~1.2s/frame | S |
| CogVideoX 5BVideo | 720×480 | ~1s/frame | S |
| Wan2.2 TI2V 5BVideo | 832×480 | ~1s/frame | S |
| Flux.2 Klein 9BImage | 1024×1024 | 400ms | S |
| Flux.1 Fill DevImage | 1024×1024 | ~3.5s | S |
| Mochi 1 PreviewVideo | 848×480 | ~1.4s/frame | S |
| HunyuanVideo 1.5Video | 720×1280 | ~1.3s/frame | S |
| Helios 14BVideo | 1280×720 | ~1.6s/frame | S |
| SkyReels V2 14BVideo | 1280×720 | ~1.6s/frame | S |
| Wan Video 2.1 14BVideo | 720×1280 | ~1.6s/frame | S |
| Wan Video 2.2 14BVideo | 720×1280 | ~1.6s/frame | S |
| Qwen ImageImage | 1024×1024 | ~1.4s | S |
| Qwen Image EditImage | 1024×1024 | ~1.4s | S |
| Flux.2 DevImage | 1024×1024 | ~39.5s | S |
| MAGI-1Video | 1280×720 | ~2s/frame | S |
| HunyuanImage 3.0Image | 256×256 | ~2.5s | D |
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.
Multi-GPU scaling
Scale out with multiple GPUs for larger models. Infinity Fabric provides 800 GB/s inter-GPU bandwidth with 15% overhead.
| Config | Effective memory | Models that fit | Est. bandwidth |
|---|---|---|---|
| 1× AMD | 128 GB | 351/374 | 3,200 GB/s |
| 2× AMD | 256 GB | 363/374 | 5,440 GB/s |
| 4× AMD | 512 GB | 371/374 | 10,880 GB/s |
Model counts use default quantization at coding workload settings. Multi-GPU scaling factor: 0.85× per additional GPU.
Upgrade paths
See what you unlock with more powerful hardware
Upgrade options
Unlocks 20 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 62%.
Infinity Fabric gives this scale-out path a cleaner inter-GPU story than PCIe-only builds.
~$15,000 MSRP
Unlocks 2 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 22%.
~$30,000 MSRP
Unlocks 8 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 49%.
~$30,000 MSRP
Unlocks 12 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 24%.
~$20,000 MSRP
Unlocks 13 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 40%.
~$8,000 MSRP
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