Will It Run AI

AMD

AMD Instinct MI300X 192GB

InstinctDatacenterCDNA 3OAMROCm
192GB
VRAM
5.3kGB/s
Bandwidth
1.3kTFLOPS
FP16 Compute
2.6kTOPS
INT8 Inference
$15,000 MSRP
VRAM192 GBBandwidth5.3k GB/sCompute1.3k TFInference2.6k TOPSValue8.71 TF/$k
AMD Instinct MI300X 192GBCategory AvgAMD Instinct MI325X 256GB

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

O AMD Instinct MI300X 192GB é a GPU de aceleração discreta CDNA 3 principal da AMD para inferência e treinamento de LLM em escala. Com 192 GB de memória HBM3 e 5,3 TB/s de largura de banda, supera a NVIDIA H100 80GB em capacidade de memória bruta e largura de banda. Os 1307 TFLOPS FP16, suporte FP8 e a maturidade do ROCm tornam-no o principal produto de IA para data centers da AMD e a principal alternativa à NVIDIA.

Beyond LLMs

AI Capability Matrix

What AI tasks this GPU can handle — from text generation to image and video creation.

CapabilityStatusRepresentative Model
LLM Chat (7B)Runs nativelyLlama 3.1 8B Q4
LLM Coding (30B)Runs nativelyQwen 3 30B Q4
LLM Large (70B)Runs nativelyLlama 3.1 70B Q4
Image Gen (SDXL)Runs nativelySDXL 1.0 FP16
Image Gen (Flux)Runs nativelyFlux.1 Dev FP16
Image Gen (SD 3.5)Runs nativelySD 3.5 Large FP16
Video Short (25f)Runs nativelyLTX Video 2B
Video Long (100f)Runs nativelyWan Video 14B
rocm-supporteddatacenter-gradehigh-bandwidthhigh-vramflagship

Especificações

Processamento
FP161307 TFLOPS
INT82614 TOPS
ArquiteturaCDNA 3
Memória
VRAM192 GB
Largura de banda5300 GB/s
Geral
FamíliaInstinct
SegmentoDatacenter
InterconexãoOAM
Plataforma de processamentoROCM
MSRP$15,000

Características principais

CDNA 3 architecture (8 × GCD chiplets, OAM form factor)192 GB HBM3 across 8 stacks5.3 TB/s memory bandwidth304 Compute Units with third-generation Matrix Cores (FP8/BF16/FP16)AMD Infinity Fabric xGMI multi-card interconnectFull ROCm support — AMD's premier AI inference platform

Para cargas de trabalho de IA

Pontos fortes
  • 192 GB HBM3 enables inference of 405B FP16 models in a single card
  • 5.3 TB/s bandwidth far exceeds H100 SXM (3.35 TB/s) for decode throughput
  • FP8 matrix cores enable efficient quantized inference at scale
  • Mature ROCm support — vLLM, PyTorch ROCm, and SGLang all production-ready
Considerações
  • OAM form factor requires specialized server infrastructure
  • ROCm software maturity still lags CUDA for cutting-edge research workloads
  • Training performance typically behind H100 despite similar inference throughput
  • Very high cost — primarily justified for large-scale production inference

Architecture

CDNA 3

CDNA 3 powers the Instinct MI300X (GPU-only, 192 GB HBM3) and MI300A (APU with integrated CPU). It features advanced packaging with up to 12 chiplets and native FP8 support for AI inference.

AI Relevance

The MI300X with 192 GB HBM3 can hold even the largest open-weight models (70B+ at full precision) entirely in GPU memory. FP8 support and mature ROCm stack make it a serious competitor to NVIDIA H100 for AI inference.

Process: TSMC 5nm + 6nmPlatform: ROCMPrecisions: FP64, FP32, TF32, FP16, BF16, FP8, INT8

Conselho de compra

Você deveria comprar AMD Instinct MI300X 192GB para IA local?

Excelente escolha para IA local

Roda 40 de 50 modelos principais bem — um ótimo coringa para inferência local.

192.0 GB

VRAM

$15,000

Preço sugerido

$78/GB

Custo por GB de VRAM

Melhores modelos para esta GPU

What will limit you first

This setup is broadly balanced for this model.

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.

Best upgrade itinerary

Buy headroom, not only minimum fit

A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

Unlocks 4 additional models that do not fit on the current setup.

Quer mais margem? AMD Instinct MI325X 256GB (256.0 GB VRAM) é o próximo passo.

Recommendations by Workload

Chat

S

Mistral Small 4 119B

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, lm-studio.

Decode 180.2 tok/s · 256K ctx · llama.cppEST.
95.4 GB / 192.0 GB VRAM

Coding

S

Devstral 2 123B Instruct

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, lm-studio.

Decode 59.9 tok/s · 256K ctx · llama.cppEST.
100.5 GB / 192.0 GB VRAM

Agentic Coding

S

Devstral 2 123B Instruct

This 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.

Decode 59.9 tok/s · 256K ctx · llama.cppEST.
105.9 GB / 192.0 GB VRAM

Reasoning

S

Devstral 2 123B Instruct

This 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.

Decode 59.9 tok/s · 256K ctx · llama.cppEST.
100.5 GB / 192.0 GB VRAM

RAG

S

Qwen 3.5 122B A10B

This 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.

Decode 166.2 tok/s · 131K ctx · llama.cppEST.
99.4 GB / 192.0 GB VRAM

Full Model Compatibility

DeepSeekDeepSeek V4 Flash
S96
284B179.4 GB89 tok/s169K ctx
moe
AlibabaQwen 3.5 122B A10B
S95
122B97.0 GB166 tok/s131K ctx
moe
MistralDevstral 2 123B Instruct
S95
123B100.5 GB60 tok/s256K ctx
dense
MistralMistral Small 4 119B
S93
119B98.1 GB180 tok/s256K ctx
moe
AlibabaQwen 3 235B A22B
S92
235B166.3 GB84 tok/s131K ctx
moe
OpenAIGPT-OSS 120B
S92
117B96.4 GB63 tok/s131K ctx
dense
CohereCommand A 111B
S92
111B91.7 GB67 tok/s262K ctx
dense
Mistral AIPixtral Large 124B
S91
124B101.1 GB59 tok/s131K ctx
dense
MiniMax M2.7
S90
230B164.2 GB96 tok/s134K ctx
moe
AlibabaQwen 2.5 VL 72B
S90
72B68.9 GB102 tok/s33K ctx
dense
AlibabaQwen3-Coder-Next
S90
80B70.4 GB279 tok/s256K ctx
moe
AlibabaQwen3-Coder 30B A3B Instruct
S89
30.5B40.2 GB625 tok/s256K ctx
moe
AlibabaQwen 3.6 35B A3B
S89
35B45.6 GB525 tok/s262K ctx
+1moe
MistralLeanstral 119B A6B
S89
119B101.5 GB166 tok/s181K ctx
moe
AlibabaQwen 3.5 27B
S89
27B39.7 GB271 tok/s131K ctx
dense
AlibabaQwen3-VL 30B A3B Instruct
S89
30B39.9 GB647 tok/s256K ctx
moe
AlibabaQwen 3.6 27B
S89
27B37.5 GB169 tok/s262K ctx
+1dense
AlibabaQwen 3.5 35B A3B
S88
35B42.9 GB571 tok/s131K ctx
moe
AlibabaQwen 3 32B
S88
32B43.5 GB230 tok/s131K ctx
dense
MistralMagistral Small 2507
S87
24B37.2 GB304 tok/s131K ctx
dense
MistralDevstral Small 2 24B Instruct
S87
24B37.2 GB304 tok/s256K ctx
dense
AlibabaQwen 3 30B A3B
S87
30.5B40.2 GB625 tok/s131K ctx
moe
AlibabaQwen 3.5 9B
S87
9B27.8 GB126 tok/s131K ctx
dense
NVIDIANemotron 3 Nano 30B
S87
30B40.8 GB243 tok/s131K ctx
dense
AlibabaQwen 3 14B
S86
14B31.1 GB196 tok/s131K ctx
dense
MistralDevstral Small 1.1
S86
24B37.2 GB304 tok/s131K ctx
dense
MicrosoftPhi-4-reasoning-plus 14B
S85
14.7B32.1 GB206 tok/s33K ctx
dense
AlibabaQwen 3 8B
A85
8B27.2 GB112 tok/s131K ctx
dense
GoogleGemma 4 31B
A85
30.7B53.5 GB144 tok/s167K ctx
dense
OpenAIGPT-OSS 20B
A84
21B35.4 GB794 tok/s128K ctx
moe
NVIDIANemotron Cascade 2 30B A3B
A84
30B41.3 GB639 tok/s262K ctx
moe
AlibabaQwen 3.5 4B
A83
4B24.7 GB56 tok/s131K ctx
dense
LG AIEXAONE 4.0 32B
A82
32B43.5 GB229 tok/s131K ctx
dense
GoogleGemma 4 26B A4B
A81
25.2B39.1 GB671 tok/s256K ctx
moe
MistralMinistral 3 14B
A80
14B31.1 GB196 tok/s262K ctx
multimodal
NVIDIANemotron Nano 8B
A80
8B26.9 GB112 tok/s131K ctx
dense
MicrosoftPhi-4 Mini Reasoning 4B
A80
3.8B23.9 GB53 tok/s131K ctx
dense
DeepSeekDeepSeek Coder V2 236B
A77
236B222.7 GB43 tok/s8K ctx
moe
Jina AIJina Embeddings v3
A74
0.57B23.2 GB8 tok/s8K ctx
dense
BAAIBGE M3
A73
0.57B22.4 GB8 tok/s8K ctx
dense
AlibabaQwen 3.5 397B A17B
F0
397B265.1 GB21 tok/s4K ctx
moe
Moonshot AIKimi K2.5
F0
1000B637.5 GB3 tok/s4K ctx
moe
Moonshot AIKimi K2.6
F0
1000B637.5 GB3 tok/s4K ctx
+1moe
DeepSeekDeepSeek V4 Pro
F0
1600B884.0 GB3 tok/s4K ctx
moe
Z.aiGLM-5.1
F0
754B499.1 GB4 tok/s4K ctx
moe
Z.aiGLM-5
F0
744B493.0 GB4 tok/s4K ctx
moe
DeepSeekDeepSeek V3.2
F0
671B429.9 GB5 tok/s4K ctx
moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B315.8 GB11 tok/s4K ctx
moe
DeepSeekDeepSeek R1 671B
F0
671B489.0 GB4 tok/s4K ctx
moe
DeepSeekDeepSeek V3.1 671B
F0
671B489.0 GB4 tok/s4K ctx
moe

Quase ao alcance

Modelos que você poderia rodar com um upgrade

Modelos de alta qualidade que precisam de um pouco mais de memória

1000BNível 100Precisa de ~633.8 GB
Também roda em 4× sua GPU via Infinity Fabric 79 tok/s
1000BNível 100Precisa de ~633.8 GB
Também roda em 4× sua GPU via Infinity Fabric 79 tok/s
1600BNível 100Precisa de ~883.0 GB
Também roda em 8× sua GPU via Infinity Fabric 116 tok/s
754BNível 92Precisa de ~489.6 GB
Também roda em 4× sua GPU via Infinity Fabric 92 tok/s

Image & Video Generation

Diffusion Model Compatibility

52 of 52 models can generate images or video on your AMD Instinct MI300X 192GB

ModelMax ResolutionGen TimeGrade
SD TurboImage512×5120msS
Stable Diffusion 1.5Image512×768100msS
Realistic Vision v5.1Image512×768100msS
DreamShaper 8Image512×768100msS
LCM DreamShaper v7Image512×7680msS
PixArt-SigmaImage1024×1024200msS
FramePack I2VVideo1280×720400ms/frameS
SDXL TurboImage512×5120msS
SDXL LightningImage1024×1024100msS
Stable Diffusion XL 1.0Image1024×1024200msS
Playground v2.5Image1024×1024400msS
RealVisXL v5.0Image1024×1024300msS
DreamShaper XLImage1024×1024300msS
Juggernaut XL v9Image1024×1024300msS
Animagine XL 3.1Image1024×1024300msS
Pony Diffusion V6 XLImage1024×1024300msS
Animagine XL 4.0Image1024×1024300msS
Illustrious XLImage1024×1024300msS
Wan Video 2.1 1.3BVideo480×832200ms/frameS
Stable Diffusion 3.5 MediumImage1024×1024400msS
Flux.2 Klein 4BImage1024×1024100msS
LTX Video 2BVideo1280×720200ms/frameS
KolorsImage1024×1024500msS
Stable CascadeImage1024×1024600msS
AuraFlow v0.3Image1536×1536~1.1sS
Stable Diffusion 3.5 LargeImage1024×1024~1.3sS
Stable Diffusion 3.5 Large TurboImage1024×1024200msS
CogVideoX 2BVideo720×480200ms/frameS
HunyuanVideoVideo720×1280400ms/frameS
ChromaImage1024×1024200msS
Z-Image TurboImage1536×1536300msS
Flux.1 DevImage1024×1024~1.1sS
Flux.1 SchnellImage1024×1024200msS
LTX Video 13BVideo1280×720400ms/frameS
Flux.1 Kontext DevImage1024×1024~1.2sS
AnimateDiff v1.5.3Video512×768100ms/frameS
Cosmos Diffusion 7BVideo1024×576400ms/frameS
CogVideoX 5BVideo720×480300ms/frameS
Wan2.2 TI2V 5BVideo832×480300ms/frameS
Flux.2 Klein 9BImage1024×1024100msS
Flux.1 Fill DevImage1024×1024~1sS
Mochi 1 PreviewVideo848×480400ms/frameS
HunyuanVideo 1.5Video720×1280400ms/frameS
Helios 14BVideo1280×720500ms/frameS
SkyReels V2 14BVideo1280×720500ms/frameS
Wan Video 2.1 14BVideo720×1280500ms/frameS
Wan Video 2.2 14BVideo720×1280500ms/frameS
Qwen ImageImage1024×1024400msS
Qwen Image EditImage1024×1024400msS
Flux.2 DevImage1024×1024~11.6sS
MAGI-1Video1280×720600ms/frameS
HunyuanImage 3.0Image1024×1024700msB

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

AMD Instinct MI300X 192GB — Up to 8× via Infinity Fabric

Scale out with multiple GPUs for larger models. Infinity Fabric provides 896 GB/s inter-GPU bandwidth with 12% overhead.

ConfigEffective memoryModels that fitEst. bandwidth
AMD192 GB359/3745,300 GB/s
AMD384 GB366/3749,328 GB/s
AMD768 GB373/37418,656 GB/s
AMD1536 GB374/37437,312 GB/s

Model counts use default quantization at coding workload settings. Multi-GPU scaling factor: 0.88× per additional GPU.

Upgrade paths

Upgrade from AMD Instinct MI300X 192GB

See what you unlock with more powerful hardware

Opções de upgrade

Opções de upgrade

Frequently Asked Questions

What AI models can I run on AMD Instinct MI300X 192GB?

AMD Instinct MI300X 192GB (192 GB VRAM) can run these top models: DeepSeek V4 Flash (score: 96/100), Qwen 3.5 122B A10B (score: 95/100), Devstral 2 123B Instruct (score: 95/100). See the full compatibility list above.

How much VRAM does AMD Instinct MI300X 192GB have for AI?

AMD Instinct MI300X 192GB has 192 GB of VRAM available for AI model inference. This determines which models and quantization levels you can run locally.

Is AMD Instinct MI300X 192GB good for running LLMs locally?

Yes, AMD Instinct MI300X 192GB is excellent for running LLMs locally with top compatibility scores above 80/100.

What is the best model for AMD Instinct MI300X 192GB for coding?

For coding on AMD Instinct MI300X 192GB, we recommend Devstral 2 123B Instruct. It achieves 59.9 tokens per second with 256K 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, lm-studio.

Should I upgrade from AMD Instinct MI300X 192GB?

There are 3 upgrade path(s) from AMD Instinct MI300X 192GB: AMD Instinct MI300X 192GB, AMD Instinct MI325X 256GB. Upgrading would unlock larger models and faster inference speeds.

Can AMD Instinct MI300X 192GB run Flux for image generation?

Yes, AMD Instinct MI300X 192GB with 192 GB of usable memory can run Flux.1 Dev at FP16 natively. Flux is a 12B parameter diffusion transformer that produces high-quality images. You can also run the Schnell variant for faster generation.

What image and video AI models can I run on AMD Instinct MI300X 192GB?

AMD Instinct MI300X 192GB (192 GB VRAM) can handle various AI generation tasks beyond LLMs. For image generation, SDXL and Stable Diffusion 3.5 run well. Flux.1 Dev also runs natively for state-of-the-art image quality. For video, LTX Video 2.3 can generate short clips. Check the AI Capability Matrix above for detailed compatibility.

Is AMD Instinct MI300X 192GB good for AI image generation?

AMD Instinct MI300X 192GB is excellent for AI image generation. With 192 GB of usable memory, it runs all major diffusion models including Flux.1, SDXL, and Stable Diffusion 3.5 at full precision. You can generate high-resolution images quickly and even handle video generation models.

Can AMD Instinct MI300X 192GB run Qwen 3.5 27B?

Yes, AMD Instinct MI300X 192GB with 192 GB of usable memory can run Qwen 3.5 27B at Q8 (near-lossless, ~28.9 GB) or even FP16 (~55.4 GB) depending on your context needs. This setup provides an excellent experience with this model. Use Ollama or vLLM for best results.

What is the best quantization for AI models on AMD Instinct MI300X 192GB?

With 192 GB VRAM on AMD Instinct MI300X 192GB, use Q8_0 for most models — it is near-lossless and you have the memory for it. For 70B+ models, Q6_K offers excellent quality. Reserve Q4_K_M for 100B+ models or when you need maximum context length.

For local LLMs on AMD Instinct MI300X 192GB, does VRAM matter more than bandwidth?

AMD Instinct MI300X 192GB already has strong memory bandwidth, so the next limit is often memory capacity and context headroom rather than raw decode speed. For local LLMs, fit first and bandwidth second is the right mental model.

How does multi-GPU scale for AI inference on AMD Instinct MI300X 192GB?

AMD Instinct MI300X 192GB supports up to 8× GPU scaling via Infinity Fabric at 896 GB/s. With 8× GPUs, you get 1536 GB effective memory with a 0.88× scaling factor per GPU. This enables running models like Qwen 3.5 397B A17B and Kimi K2.5 that don't fit on a single card.

Is Infinity Fabric required for multi-GPU AMD Instinct MI300X 192GB inference?

Infinity Fabric is recommended for AMD Instinct MI300X 192GB multi-GPU inference, providing 896 GB/s interconnect bandwidth with only 12% scaling overhead. PCIe-only setups work but have higher overhead (~25%) due to limited inter-GPU bandwidth.

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