AMD
AMD Instinct MI250X 128GB
InstinctDatacenterCDNA 2OAMROCm
Operating mode
Choose the operating mode for this hardware
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.
About this GPU for AI
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 Full ROCm support makes it a production-ready platform for LLM inference, though it has been superseded by the MI300X for new deployments.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
AI Capability Matrix
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) |
rocm-supporteddatacenter-gradehigh-bandwidthhigh-vram
Specifications
Compute
FP16383 TFLOPS
INT8766 TOPS
ArchitectureCDNA 2
Memory
VRAM128 GB
Bandwidth3200 GB/s
General
FamilyInstinct
SegmentDatacenter
InterconnectOAM
Compute PlatformROCM
MSRP$15,000
Key Features
CDNA 2 architecture (dual-die GCD, OAM form factor, fully enabled)128 GB HBM2e across two dies3.2 TB/s aggregate memory bandwidth440 Compute Units with second-generation Matrix CoresAMD Infinity Fabric + xGMI interconnect for multi-card scalingFull ROCm support — production LLM inference platform
For AI Workloads
Strengths
- 128 GB HBM2e for 70B FP16 and 405B Q4 inference
- 383 TFLOPS FP16 is higher than MI250 — better for compute-bound workloads
- 3.2 TB/s bandwidth delivers fast generation for large model sizes
- Mature ROCm support — widely deployed and well-tested in production
Considerations
- OAM requires specialized server/OCP rack infrastructure
- MI300X offers 1307 TFLOPS — over 3x more compute at reduced cost per TFLOP
- CDNA 2 lacks INT8/FP8 hardware acceleration in CDNA 3+
- Legacy product — AMD is phasing it out in favor of MI300 series
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.
Process: TSMC 6nmPlatform: ROCMPrecisions: FP64, FP32, TF32, FP16, BF16, INT8
Recommendations by Workload
Qwen 3.5 122B A10B matches Chat and keeps a practical fit profile. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, lm-studio.
Decode 100.3 tok/s · 131K ctx · llama.cppEST.
Qwen3-Coder-Next is a specialized fit for Coding. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.
Decode 105.7 tok/s · 256K ctx · llama.cppEST.
Just out of reach
Models you could run with an upgrade
High-quality models that need a bit more memory
397BTier 100Needs ~257.3 GB
Also runs on 2× your GPU via Infinity Fabric — 38 tok/s
1000BTier 100Needs ~627.4 GB
1000BTier 100Needs ~627.4 GB
1600BTier 100Needs ~876.6 GB
284BTier 98Needs ~172.4 GB
Also runs on 2× your GPU via Infinity Fabric — 91 tok/s
Image & Video Generation
Diffusion Model Compatibility
52 of 52 models can generate images or video on your AMD Instinct MI250X 128GB
Multi-GPU scaling
AMD Instinct MI250X 128GB — Up to 4× via Infinity Fabric
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
Upgrade from AMD Instinct MI250X 128GB
See what you unlock with more powerful hardware
Upgrade options
Upgrade options
4× AMD Instinct MI250X 128GBMulti-GPU
4 × 128 GB = 512 GB effectivevia Infinity Fabric (800 GB/s)
AUnlocks 20 additional models that do not fit on the current setup.Unlocks Qwen 3.5 397B A17B, DeepSeek V4 Flash, GLM-5.1+17 more · +62% faster avg
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
141 GB VRAM (+13)4800 GB/s (+1600)
BUnlocks 2 additional models that do not fit on the current setup.Unlocks Qwen 3 235B A22B, MiniMax M2.7+22% faster avg
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
180 GB VRAM (+52)8000 GB/s (+4800)
BUnlocks 8 additional models that do not fit on the current setup.Unlocks DeepSeek V4 Flash, Qwen 3 235B A22B, MiniMax M2.7+5 more · +49% faster avg
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
AMD Instinct MI325X 256GBAMD upgrade
256 GB VRAM (+128)6000 GB/s (+2800)
BUnlocks 12 additional models that do not fit on the current setup.Unlocks Qwen 3.5 397B A17B, DeepSeek V4 Flash, Qwen 3 235B A22B+9 more · +24% faster avg
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
AMD Instinct MI350X 288GBBest value
288 GB VRAM (+160)8000 GB/s (+4800)
BUnlocks 13 additional models that do not fit on the current setup.Unlocks Qwen 3.5 397B A17B, DeepSeek V4 Flash, Qwen 3 235B A22B+10 more · +40% faster avg
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
Frequently Asked Questions
AMD Instinct MI250X 128GBCategory AvgNVIDIA H200 141GB
| 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 |
S
Devstral 2 123B Instruct is a specialized fit for Agentic Coding. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, lm-studio.
Decode 36.2 tok/s · 117K ctx · llama.cppEST.
Devstral 2 123B Instruct matches Reasoning and keeps a practical fit profile. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, lm-studio.
Decode 36.2 tok/s · 117K ctx · llama.cppEST.
Qwen 3.5 122B A10B matches RAG and keeps a practical fit profile. It is a recent-generation family, which helps on current local SOTA workloads. It fits natively with comfortable headroom. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, lm-studio.
Decode 100.3 tok/s · 131K ctx · llama.cppEST.
97
123B94.1 GB36 tok/s117K ctx
Image
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.
Buying advice
Should you buy AMD Instinct MI250X 128GB for local AI?
Excellent choice for local AI
Runs 36 of 50 top models well — a strong all-rounder for local inference.
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.