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URL: https://willitrunai.com/gpus/rx-5600-xt-6gb

⇱ AI Models for RX 5600 XT 6GB — What Runs on 6GB VRAM


AMD

RX 5600 XT 6GB

RX 5000ConsumerRDNA 1PCIe 4ROCm

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.

See Full AI Tier List for RX 5600 XT 6GB →

About this GPU for AI

The RX 5600 XT 6GB is an RDNA 1 GPU from 2020 with only 6 GB of GDDR6 VRAM. RDNA 1 has no official ROCm support and ROCm support via community methods is unreliable. AI inference is limited to Vulkan-based backends in llama.cpp. The 6 GB VRAM severely limits model choice — only small 3B-7B models at aggressive quantization fit, making this a very constrained option for local AI work.

Beyond LLMs

AI Capability Matrix

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

CapabilityStatusRepresentative ModelDetail
LLM Chat (7B)Needs offloadLlama 3.1 8B Q4
LLM Coding (30B)Won’t fitQwen 3 30B Q4
no-rocmvulkan-onlylegacyvram-limited

Specifications

Compute
FP1614 TFLOPS
INT829 TOPS
ArchitectureRDNA 1
Memory
VRAM6 GB
Bandwidth288 GB/s
General
FamilyRX 5000
SegmentConsumer
InterconnectPCIe 4
Compute PlatformROCM
MSRP$279

Key Features

RDNA 1 architecture (Navi 10 die)6 GB GDDR6 on a 192-bit bus288 GB/s memory bandwidth36 Compute UnitsPCIe Gen 4 x16No ROCm support — Vulkan inference only

For AI Workloads

Strengths
  • Vulkan backend in llama.cpp works for very small models (1B-3B)
  • PCIe Gen 4 support despite being from 2020
  • Widely available as inexpensive used hardware
Considerations
  • No ROCm support — RDNA 1 is not on any ROCm compatibility list
  • 6 GB VRAM is insufficient for most modern LLMs — even 7B at Q4 barely fits
  • Very low FP16 throughput (14 TFLOPS) means slow inference
  • Not worth purchasing for AI use — better options exist at similar used prices

Architecture

RDNA 1

RDNA 1 is AMD's first RDNA architecture, replacing the GCN design for consumer GPUs. Built on TSMC 7nm, it delivered significant IPC improvements over GCN 5 (Vega).

AI Relevance

Very limited AI inference support. No official ROCm support for consumer RDNA 1 cards. Vulkan-based backends in llama.cpp can work but with poor performance. Not recommended for AI workloads.

Process: TSMC 7nmPlatform: ROCMPrecisions: FP32, FP16

Recommendations by Workload

Chat

A

Gemma 4 E2B

Gemma 4 E2B 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, ollama, lm-studio.

Decode 39.7 tok/s · 42K ctx · llama.cppEST.
4.9 GB / 6.0 GB VRAM

Coding

A

Gemma 4 E2B

Gemma 4 E2B is a specialized fit for Coding. It is a recent-generation family, which helps on current local SOTA workloads. It should run, but memory headroom will be limited. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.

Decode 39.7 tok/s · 42K ctx · llama.cppEST.
5.1 GB / 6.0 GB VRAM

Agentic Coding

A

Full Model Compatibility

👁 Alibaba
Qwen 3.5 4B
S92
4B6.1 GB47 tok/s15K ctx
dense
👁 Microsoft
Phi-4 Mini Reasoning 4B
S89
3.8B5.3 GB53 tok/s24K ctx
dense
👁 Jina AI
Jina Embeddings v3
S86

Just out of reach

Models you could run with an upgrade

High-quality models that need a bit more memory

Image & Video Generation

Diffusion Model Compatibility

18 of 52 models can generate images or video on your RX 5600 XT 6GB

ModelMax ResolutionGen TimeGrade
SD TurboImage512×512~4.3sA
Stable Diffusion 1.5Image512×768~8.6sB
Realistic Vision v5.1Image512×768~8.6sB
DreamShaper 8Image512×768~8.6sB
LCM DreamShaper v7

Upgrade paths

Upgrade from RX 5600 XT 6GB

See what you unlock with more powerful hardware

Upgrade options

Upgrade options

👁 NVIDIA
RTX 3050 8GBNext step up
8 GB VRAM (+2)
B
Unlocks 38 additional models that do not fit on the current setup.Unlocks Qwen 3.5 9B, Qwen 3 8B, Nemotron Nano 8B+35 more · +1% faster avg

Unlocks 38 additional models that do not fit on the current setup.

~$249 MSRP

Radeon RX 7600M 8GBAMD upgrade
8 GB VRAM (+2)
A
Unlocks 38 additional models that do not fit on the current setup.Unlocks Qwen 3.5 9B, Qwen 3 8B, Nemotron Nano 8B+35 more · +30% faster avg

Unlocks 38 additional models that do not fit on the current setup.

Lifts average decode speed across fitting models by about 30%.

RX 7600 XT 16GBBest value
16 GB VRAM (+10)
A
Unlocks 112 additional models that do not fit on the current setup.Unlocks Qwen 3.5 9B, Magistral Small 2507, Devstral Small 2 24B Instruct+109 more · +14% faster avg

Unlocks 112 additional models that do not fit on the current setup.

Lifts average decode speed across fitting models by about 14%.

~$329 MSRP

AMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+282)8000 GB/s (+7712)
B
Unlocks 193 additional models that do not fit on the current setup.Unlocks Qwen3-Coder 30B A3B Instruct, Qwen 3.5 397B A17B, Devstral 2 123B Instruct+190 more · +492% faster avg

Unlocks 193 additional models that do not fit on the current setup.

Lifts average decode speed across fitting models by about 492%.

~$8,000 MSRP

Frequently Asked Questions

Compare with similar

RX 5600 XT 6GB vs RTX 2060 6GBRX 5600 XT 6GB vs RTX 4050 Laptop 6GBRX 5600 XT 6GB vs Intel Arc Pro A40 6GB
Compare this GPUCompare with another GPU →
6GB
VRAM
288GB/s
Bandwidth
14TFLOPS
FP16 Compute
29TOPS
INT8 Inference
$279 MSRP
RX 5600 XT 6GBCategory AvgRTX 3050 8GB
LLM Large (70B)
Won’t fit
Llama 3.1 70B Q4
Image Gen (SDXL)Very constrainedSDXL 1.0 FP16~~34.2s per image
Image Gen (Flux)Won't fitFlux.1 Dev FP16~~2m 34s per image
Image Gen (SD 3.5)Won't fitSD 3.5 Large FP16~~3m 8s per image
Video Short (25f)Won't fitLTX Video 2B~~29.7s/frame
Video Long (100f)Won't fitWan Video 14B~~1m 28s/frame

Gemma 4 E2B

Gemma 4 E2B is a specialized fit for Agentic Coding. It is a recent-generation family, which helps on current local SOTA workloads. It should run, but memory headroom will be limited. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.

Decode 39.7 tok/s · 42K ctx · llama.cppEST.
5.7 GB / 6.0 GB VRAM

Reasoning

A

Gemma 4 E2B

Gemma 4 E2B matches Reasoning and keeps a practical fit profile. It is a recent-generation family, which helps on current local SOTA workloads. It should run, but memory headroom will be limited. Context coverage stays within the requested workload envelope. Known distribution channels: huggingface, ollama, lm-studio.

Decode 39.7 tok/s · 42K ctx · llama.cppEST.
5.1 GB / 6.0 GB VRAM

RAG

A

Ministral 3 3B

Ministral 3 3B is viable for RAG, but is not the most specialized choice. 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.

Decode 42.0 tok/s · 58K ctx · llama.cppEST.
4.8 GB / 6.0 GB VRAM
0.57B4.6 GB8 tok/s8K ctx
dense
👁 BAAI
BGE M3
A84
0.57B3.8 GB8 tok/s8K ctx
dense
👁 Alibaba
Qwen3-Coder 30B A3B Instruct
F0
30.5B21.6 GB3 tok/s4K ctx
moe
👁 Alibaba
Qwen 3.5 397B A17B
F0
397B246.5 GB2 tok/s4K ctx
moe
👁 Mistral
Devstral 2 123B Instruct
F0
123B81.9 GB2 tok/s4K ctx
dense
👁 Moonshot AI
Kimi K2.5
F0
1000B618.9 GB2 tok/s4K ctx
moe
👁 Moonshot AI
Kimi K2.6
F0
1000B618.9 GB2 tok/s4K ctx
+1moe
👁 DeepSeek
DeepSeek V4 Pro
F0
1600B865.4 GB2 tok/s4K ctx
moe
👁 Alibaba
Qwen 3.5 27B
F0
27B21.1 GB2 tok/s4K ctx
dense
👁 Alibaba
Qwen 3.6 27B
F0
27B18.9 GB2 tok/s4K ctx
+1dense
👁 Alibaba
Qwen 3.5 122B A10B
F0
122B78.4 GB2 tok/s4K ctx
moe
👁 Alibaba
Qwen3-VL 30B A3B Instruct
F0
30B21.3 GB4 tok/s4K ctx
moe
👁 Alibaba
Qwen 3.6 35B A3B
F0
35B27.0 GB3 tok/s4K ctx
+1moe
👁 DeepSeek
DeepSeek V4 Flash
F0
284B160.8 GB2 tok/s4K ctx
moe
👁 Alibaba
Qwen 3.5 9B
F0
9B9.2 GB9 tok/s4K ctx
dense
👁 Alibaba
Qwen 3.5 35B A3B
F0
35B24.3 GB3 tok/s4K ctx
moe
👁 Mistral
Magistral Small 2507
F0
24B18.6 GB2 tok/s4K ctx
dense
👁 Mistral
Devstral Small 2 24B Instruct
F0
24B18.6 GB2 tok/s4K ctx
dense
👁 Alibaba
Qwen 3 32B
F0
32B24.9 GB2 tok/s4K ctx
dense
👁 Alibaba
Qwen 3 14B
F0
14B12.5 GB3 tok/s4K ctx
dense
👁 Alibaba
Qwen 3 30B A3B
F0
30.5B21.6 GB3 tok/s4K ctx
moe
👁 Mistral
Mistral Small 4 119B
F0
119B79.5 GB2 tok/s4K ctx
moe
👁 Cohere
Command A 111B
F0
111B73.1 GB2 tok/s4K ctx
dense
👁 Alibaba
Qwen 2.5 VL 72B
F0
72B50.3 GB2 tok/s4K ctx
dense
👁 OpenAI
GPT-OSS 120B
F0
117B77.8 GB2 tok/s4K ctx
dense
👁 NVIDIA
Nemotron 3 Nano 30B
F0
30B22.2 GB2 tok/s4K ctx
dense
👁 Alibaba
Qwen 3 8B
F0
8B8.6 GB12 tok/s4K ctx
dense
👁 Alibaba
Qwen3-Coder-Next
F0
80B51.8 GB2 tok/s4K ctx
moe
👁 Microsoft
Phi-4-reasoning-plus 14B
F0
14.7B13.5 GB3 tok/s4K ctx
dense
👁 Mistral
Devstral Small 1.1
F0
24B18.6 GB2 tok/s4K ctx
dense
👁 Z.ai
GLM-5.1
F0
754B480.5 GB2 tok/s4K ctx
moe
👁 Mistral AI
Pixtral Large 124B
F0
124B82.5 GB2 tok/s4K ctx
dense
👁 Z.ai
GLM-5
F0
744B474.4 GB2 tok/s4K ctx
moe
👁 DeepSeek
DeepSeek V3.2
F0
671B411.3 GB2 tok/s4K ctx
moe
👁 OpenAI
GPT-OSS 20B
F0
21B16.8 GB4 tok/s4K ctx
moe
👁 Alibaba
Qwen 3 235B A22B
F0
235B147.7 GB2 tok/s4K ctx
moe
👁 Alibaba
Qwen3-Coder 480B A35B Instruct
F0
480B297.2 GB2 tok/s4K ctx
moe
👁 NVIDIA
Nemotron Cascade 2 30B A3B
F0
30B22.7 GB4 tok/s4K ctx
moe
👁 Google
Gemma 4 31B
F0
30.7B34.9 GB2 tok/s4K ctx
dense
MiniMax M2.7
F0
230B145.6 GB2 tok/s4K ctx
moe
👁 Mistral
Leanstral 119B A6B
F0
119B82.9 GB2 tok/s4K ctx
moe
👁 DeepSeek
DeepSeek Coder V2 236B
F0
236B204.1 GB2 tok/s4K ctx
moe
👁 DeepSeek
DeepSeek R1 671B
F0
671B470.4 GB2 tok/s4K ctx
moe
👁 DeepSeek
DeepSeek V3.1 671B
F0
671B470.4 GB2 tok/s4K ctx
moe
👁 NVIDIA
Nemotron Nano 8B
F0
8B8.3 GB12 tok/s4K ctx
dense
👁 Mistral
Ministral 3 14B
F0
14B12.5 GB3 tok/s4K ctx
multimodal
👁 LG AI
EXAONE 4.0 32B
F0
32B24.9 GB2 tok/s4K ctx
dense
👁 Google
Gemma 4 26B A4B
F0
25.2B20.5 GB4 tok/s4K ctx
moe
Image
512×768
~2.6s
B
PixArt-SigmaImage256×256~34.2sB
FramePack I2VVideo256×256~1m 3s/frameB
SDXL TurboImage256×256~4.3sD
SDXL LightningImage256×256~12.8sD
Stable Diffusion XL 1.0Image256×256~34.2sD
Playground v2.5Image256×256~51.4sD
RealVisXL v5.0Image256×256~38.5sD
DreamShaper XLImage256×256~38.5sD
Juggernaut XL v9Image256×256~38.5sD
Animagine XL 3.1Image256×256~38.5sD
Pony Diffusion V6 XLImage256×256~38.5sD
Animagine XL 4.0Image256×256~38.5sD
Illustrious XLImage256×256~38.5sD
Wan Video 2.1 1.3BVideo256×256~25s/frameF
Stable Diffusion 3.5 MediumImage256×256~59.9sF
Flux.2 Klein 4BImage256×256~10.3sF
LTX Video 2BVideo256×256~29.7s/frameF
KolorsImage256×256~1m 9sF
Stable CascadeImage256×256~1m 26sF
AuraFlow v0.3Image256×256~2m 34sF
Stable Diffusion 3.5 LargeImage256×256~3m 8sF
Stable Diffusion 3.5 Large TurboImage256×256~34.2sF
CogVideoX 2BVideo256×256~29.7s/frameF
HunyuanVideoVideo256×256~1m 3s/frameF
ChromaImage256×256~34.2sF
Z-Image TurboImage256×256~35.3sF
Flux.1 DevImage256×256~2m 34sF
Flux.1 SchnellImage256×256~30sF
LTX Video 13BVideo256×256~1m 3s/frameF
Flux.1 Kontext DevImage256×256~2m 51sF
AnimateDiff v1.5.3Video512×768~15.6s/frameF
Cosmos Diffusion 7BVideo256×256~49.1s/frameF
CogVideoX 5BVideo256×256~42.9s/frameF
Wan2.2 TI2V 5BVideo256×256~42.9s/frameF
Flux.2 Klein 9BImage256×256~17.1sF
Flux.1 Fill DevImage256×256~2m 26sF
Mochi 1 PreviewVideo256×256~56.6s/frameF
HunyuanVideo 1.5Video256×256~52.5s/frameF
Helios 14BVideo256×256~1m 5s/frameF
SkyReels V2 14BVideo256×256~1m 5s/frameF
Wan Video 2.1 14BVideo256×256~1m 5s/frameF
Wan Video 2.2 14BVideo256×256~1m 5s/frameF
Qwen ImageImage256×256~57.6sF
Qwen Image EditImage256×256~57.6sF
Flux.2 DevImage256×256~27m 0sF
MAGI-1Video256×256~1m 20s/frameF
HunyuanImage 3.0Image256×256~1m 42sF

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 RX 5600 XT 6GB for local AI?

Usable for local AI with limits

Can run 4 of 50 top models, mostly smaller ones. Larger models need heavy quantization or won't fit.

6.0 GB

VRAM

$279

MSRP

$47/GB

Cost per GB VRAM

Best models for this 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 38 additional models that do not fit on the current setup.

Want more headroom? RTX 3050 8GB (8.0 GB VRAM) is the next step up.