Will It Run AI

AMD

Radeon Pro W7900 48GB

Radeon ProWorkstationRDNA 3PCIe 4ROCm
48GB
VRAM
864GB/s
Bandwidth
62TFLOPS
FP16 Compute
496TOPS
INT8 Inference
$3,999 MSRP
VRAM48 GBBandwidth864 GB/sCompute62 TFInference496 TOPSValue1.55 TF/$k
Radeon Pro W7900 48GBCategory AvgAMD Instinct MI210 64GB

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 Radeon Pro W7900 48GB is AMD's flagship RDNA 3 workstation GPU, offering 48 GB of ECC GDDR6 and full ROCm support through the Navi 31 workstation driver stack. At this VRAM capacity, it can run 70B models at FP16 and compete with the NVIDIA RTX 6000 Ada Generation in the workstation AI segment. It is one of the largest VRAM configurations available in an AMD consumer-accessible workstation card.

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)Needs offloadLlama 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)Won't fitWan Video 14B
rocm-supportedworkstation-gradehigh-vramflagship

Especificações

Processamento
FP1662 TFLOPS
INT8496 TOPS
ArquiteturaRDNA 3
Memória
VRAM48 GB
Largura de banda864 GB/s
Geral
FamíliaRadeon Pro
SegmentoWorkstation
InterconexãoPCIe 4
Plataforma de processamentoROCM
MSRP$3,999

Características principais

RDNA 3 architecture (Navi 31 die, fully enabled)48 GB GDDR6 ECC on a 384-bit bus864 GB/s memory bandwidth96 Compute UnitsPCIe Gen 4 x16Full workstation ROCm support — best AMD consumer-accessible option

Para cargas de trabalho de IA

Pontos fortes
  • 48 GB ECC VRAM enables 70B FP16 inference in a single card
  • 864 GB/s bandwidth rivals consumer 7900 XTX for decode throughput
  • Full Navi 31 ROCm support — the same architecture as the consumer 7900 XTX
  • Workstation certification suitable for enterprise and research deployment
Considerações
  • Very expensive ($3,999) — Instinct MI210 64GB is cheaper and better suited for pure AI
  • RDNA 3 ROCm ecosystem still trails NVIDIA in framework completeness
  • 62 TFLOPS FP16 is similar to 7900 XTX — workstation premium is for ECC and support
  • NVIDIA RTX 6000 Ada (48 GB CUDA) outperforms it in most benchmarked AI tasks

Architecture

RDNA 3

RDNA 3 is AMD's chiplet-based GPU architecture, combining a 5nm Graphics Compute Die (GCD) with 6nm Memory Cache Dies (MCDs). It introduces AI accelerators and a new unified compute unit design.

AI Relevance

ROCm support for RDNA 3 is maturing but lags behind NVIDIA's CUDA ecosystem. AI accelerator units provide some inference acceleration, but lack the dedicated Tensor Core equivalent found in NVIDIA GPUs.

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

Conselho de compra

Você deveria comprar Radeon Pro W7900 48GB para IA local?

Excelente escolha para IA local

Roda 29 de 50 modelos principais bem — um ótimo coringa para inferência local.

48.0 GB

VRAM

$3,999

Preço sugerido

$83/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 5 additional models that do not fit on the current setup.

Quer mais margem? AMD Instinct MI210 64GB (64.0 GB VRAM) é o próximo passo.

Recommendations by Workload

Chat

S

Qwen 3.5 35B A3B

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.

Decode 70.4 tok/s · 131K ctx · llama.cppEST.
27.8 GB / 48.0 GB VRAM

Coding

S

Qwen 3.6 27B

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 23.9 tok/s · 262K ctx · llama.cppEST.
23.1 GB / 48.0 GB VRAM

Agentic Coding

S

Qwen 3.6 27B

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 23.9 tok/s · 262K ctx · llama.cppEST.
24.1 GB / 48.0 GB VRAM

Reasoning

S

Qwen 3 32B

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, ollama, lm-studio.

Decode 28.4 tok/s · 93K ctx · llama.cppEST.
29.1 GB / 48.0 GB VRAM

RAG

S

Qwen 3.5 27B

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, ollama, lm-studio.

Decode 33.4 tok/s · 130K ctx · llama.cppEST.
28.5 GB / 48.0 GB VRAM

Full Model Compatibility

AlibabaQwen 3.6 35B A3B
S97
35B31.2 GB65 tok/s82K ctx
+1moe
AlibabaQwen3-Coder 30B A3B Instruct
S96
30.5B25.8 GB77 tok/s256K ctx
moe
AlibabaQwen 3.5 35B A3B
S95
35B28.5 GB70 tok/s131K ctx
moe
AlibabaQwen3-VL 30B A3B Instruct
S95
30B25.5 GB80 tok/s256K ctx
moe
AlibabaQwen 3 30B A3B
S93
30.5B25.8 GB77 tok/s131K ctx
moe
AlibabaQwen 3.5 27B
S92
27B25.3 GB33 tok/s130K ctx
dense
AlibabaQwen 3 32B
S92
32B29.1 GB28 tok/s93K ctx
dense
NVIDIANemotron Cascade 2 30B A3B
S91
30B26.9 GB79 tok/s131K ctx
moe
MistralMagistral Small 2507
S91
24B22.8 GB37 tok/s131K ctx
dense
MistralDevstral Small 2 24B Instruct
S90
24B22.8 GB37 tok/s181K ctx
dense
AlibabaQwen 3.6 27B
S90
27B23.1 GB24 tok/s262K ctx
+1dense
NVIDIANemotron 3 Nano 30B
S90
30B26.4 GB30 tok/s131K ctx
dense
OpenAIGPT-OSS 20B
S90
21B21.0 GB98 tok/s128K ctx
moe
AlibabaQwen 3.5 9B
S89
9B13.4 GB100 tok/s131K ctx
dense
AlibabaQwen 3 14B
S89
14B16.7 GB65 tok/s131K ctx
dense
GoogleGemma 4 31B
S89
30.7B39.1 GB20 tok/s26K ctx
dense
MistralDevstral Small 1.1
S89
24B22.8 GB37 tok/s131K ctx
dense
MicrosoftPhi-4-reasoning-plus 14B
S88
14.7B17.7 GB61 tok/s33K ctx
dense
GoogleGemma 4 26B A4B
S88
25.2B24.7 GB83 tok/s118K ctx
moe
AlibabaQwen 3 8B
S88
8B12.8 GB112 tok/s131K ctx
dense
LG AIEXAONE 4.0 32B
S86
32B29.1 GB28 tok/s93K ctx
dense
AlibabaQwen 3.5 4B
A85
4B10.3 GB56 tok/s131K ctx
dense
MistralMinistral 3 14B
A83
14B16.7 GB64 tok/s221K ctx
multimodal
NVIDIANemotron Nano 8B
A83
8B12.5 GB112 tok/s131K ctx
dense
MicrosoftPhi-4 Mini Reasoning 4B
A81
3.8B9.5 GB53 tok/s131K ctx
dense
AlibabaQwen3-Coder-Next
A79
80B56.0 GB19 tok/s4K ctx
moe
AlibabaQwen 2.5 VL 72B
A76
72B54.5 GB7 tok/s4K ctx
dense
Jina AIJina Embeddings v3
A75
0.57B8.8 GB8 tok/s8K ctx
dense
BAAIBGE M3
A74
0.57B8.0 GB8 tok/s8K ctx
dense
AlibabaQwen 3.5 397B A17B
F0
397B250.7 GB2 tok/s4K ctx
moe
MistralDevstral 2 123B Instruct
F0
123B86.1 GB2 tok/s4K ctx
dense
Moonshot AIKimi K2.5
F0
1000B623.1 GB2 tok/s4K ctx
moe
Moonshot AIKimi K2.6
F0
1000B623.1 GB2 tok/s4K ctx
+1moe
DeepSeekDeepSeek V4 Pro
F0
1600B869.6 GB2 tok/s4K ctx
moe
AlibabaQwen 3.5 122B A10B
F0
122B82.6 GB5 tok/s4K ctx
moe
DeepSeekDeepSeek V4 Flash
F0
284B165.0 GB2 tok/s4K ctx
moe
MistralMistral Small 4 119B
F0
119B83.7 GB5 tok/s4K ctx
moe
CohereCommand A 111B
F0
111B77.3 GB2 tok/s4K ctx
dense
OpenAIGPT-OSS 120B
F0
117B82.0 GB2 tok/s4K ctx
dense
Z.aiGLM-5.1
F0
754B484.7 GB2 tok/s4K ctx
moe
Mistral AIPixtral Large 124B
F0
124B86.7 GB2 tok/s4K ctx
dense
Z.aiGLM-5
F0
744B478.6 GB2 tok/s4K ctx
moe
DeepSeekDeepSeek V3.2
F0
671B415.5 GB2 tok/s4K ctx
moe
AlibabaQwen 3 235B A22B
F0
235B151.9 GB2 tok/s4K ctx
moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B301.4 GB2 tok/s4K ctx
moe
MiniMax M2.7
F0
230B149.8 GB2 tok/s4K ctx
moe
MistralLeanstral 119B A6B
F0
119B87.1 GB4 tok/s4K ctx
moe
DeepSeekDeepSeek Coder V2 236B
F0
236B208.3 GB2 tok/s4K ctx
moe
DeepSeekDeepSeek R1 671B
F0
671B474.6 GB2 tok/s4K ctx
moe
DeepSeekDeepSeek V3.1 671B
F0
671B474.6 GB2 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

Image & Video Generation

Diffusion Model Compatibility

50 of 52 models can generate images or video on your Radeon Pro W7900 48GB

ModelMax ResolutionGen TimeGrade
SD TurboImage512×512900msS
Stable Diffusion 1.5Image512×768~1.7sS
Realistic Vision v5.1Image512×768~1.7sS
DreamShaper 8Image512×768~1.7sS
LCM DreamShaper v7Image512×768500msS
PixArt-SigmaImage1024×1024~6.8sS
FramePack I2VVideo640×480~21.7s/frameS
SDXL TurboImage512×512900msS
SDXL LightningImage1024×1024~2.6sS
Stable Diffusion XL 1.0Image1024×1024~6.8sS
Playground v2.5Image1024×1024~10.2sS
RealVisXL v5.0Image1024×1024~7.7sS
DreamShaper XLImage1024×1024~7.7sS
Juggernaut XL v9Image1024×1024~7.7sS
Animagine XL 3.1Image1024×1024~7.7sS
Pony Diffusion V6 XLImage1024×1024~7.7sS
Animagine XL 4.0Image1024×1024~7.7sS
Illustrious XLImage1024×1024~7.7sS
Wan Video 2.1 1.3BVideo480×832~5s/frameS
Stable Diffusion 3.5 MediumImage1024×1024~11.9sS
Flux.2 Klein 4BImage1024×1024~2sS
LTX Video 2BVideo1280×720~5.9s/frameS
KolorsImage1024×1024~13.6sS
Stable CascadeImage1024×1024~17sS
AuraFlow v0.3Image1536×1536~30.7sS
Stable Diffusion 3.5 LargeImage1024×1024~37.5sS
Stable Diffusion 3.5 Large TurboImage1024×1024~6.8sS
CogVideoX 2BVideo720×480~5.9s/frameS
HunyuanVideoVideo256×256~21.7s/frameS
ChromaImage1024×1024~6.8sS
Z-Image TurboImage1536×1536~7sS
Flux.1 DevImage1024×1024~30.7sS
Flux.1 SchnellImage1024×1024~6sS
LTX Video 13BVideo768×512~12.5s/frameS
Flux.1 Kontext DevImage1024×1024~34.1sS
AnimateDiff v1.5.3Video512×768~3.1s/frameS
Cosmos Diffusion 7BVideo1024×576~9.8s/frameS
CogVideoX 5BVideo720×480~8.5s/frameS
Wan2.2 TI2V 5BVideo832×480~8.5s/frameS
Flux.2 Klein 9BImage1024×1024~3.4sS
Flux.1 Fill DevImage1024×1024~29sS
Mochi 1 PreviewVideo848×480~11.3s/frameS
HunyuanVideo 1.5Video720×1280~10.5s/frameA
Helios 14BVideo832×480~12.9s/frameB
SkyReels V2 14BVideo256×256~12.9s/frameB
Wan Video 2.1 14BVideo256×256~22.1s/frameD
Wan Video 2.2 14BVideo256×256~22.1s/frameD
Qwen ImageImage256×256~18.9sD
Qwen Image EditImage256×256~18.9sD
Flux.2 DevImage256×256~5m 22sD
MAGI-1Video256×256~16s/frameF
HunyuanImage 3.0Image256×256~20.2sF

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

Upgrade from Radeon Pro W7900 48GB

See what you unlock with more powerful hardware

Opções de upgrade

Opções de upgrade

Frequently Asked Questions

What AI models can I run on Radeon Pro W7900 48GB?

Radeon Pro W7900 48GB (48 GB VRAM) can run these top models: Qwen 3.6 35B A3B (score: 97/100), Qwen3-Coder 30B A3B Instruct (score: 96/100), Qwen 3.5 35B A3B (score: 95/100). See the full compatibility list above.

How much VRAM does Radeon Pro W7900 48GB have for AI?

Radeon Pro W7900 48GB has 48 GB of VRAM available for AI model inference. This determines which models and quantization levels you can run locally.

Is Radeon Pro W7900 48GB good for running LLMs locally?

Yes, Radeon Pro W7900 48GB is excellent for running LLMs locally with top compatibility scores above 80/100.

What is the best model for Radeon Pro W7900 48GB for coding?

For coding on Radeon Pro W7900 48GB, we recommend Qwen 3.6 27B. It achieves 23.9 tokens per second with 262K 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 Radeon Pro W7900 48GB?

There are 4 upgrade path(s) from Radeon Pro W7900 48GB: AMD Instinct MI210 64GB, MacBook Pro M3 Max 128GB. Upgrading would unlock larger models and faster inference speeds.

Can Radeon Pro W7900 48GB run Flux for image generation?

Yes, Radeon Pro W7900 48GB with 48 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 Radeon Pro W7900 48GB?

Radeon Pro W7900 48GB (48 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 Radeon Pro W7900 48GB good for AI image generation?

Radeon Pro W7900 48GB is excellent for AI image generation. With 48 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 Radeon Pro W7900 48GB run Qwen 3.5 27B?

Yes, Radeon Pro W7900 48GB with 48 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 Radeon Pro W7900 48GB?

With 48 GB VRAM on Radeon Pro W7900 48GB, 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 Radeon Pro W7900 48GB, does VRAM matter more than bandwidth?

Radeon Pro W7900 48GB has enough memory for many local LLMs, but bandwidth still matters a lot for real speed. Once a model fits, a faster-memory GPU can feel significantly better than a slower setup with similar capacity.

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