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AMD Radeon RX 6900 XT

AMD · 16GBGDDR6 · Can run 81 models

BuyAmazon
ManufacturerAMD
VRAM16 GB
Memory TypeGDDR6
ArchitectureRDNA 2
Stream Procs5,120
Bandwidth512 GB/s
TDP300W
MSRP$999
ReleasedDec 8, 2020

AI Notes

The RX 6900 XT is AMD's top RDNA 2 card with 16GB VRAM and 512 GB/s bandwidth. It matches the RX 6800 XT in memory capacity with higher compute performance. Can run 13B models comfortably and attempt larger models with quantization. Good value on the used market with mature ROCm support.

Compatible Models

ModelParametersBest QuantVRAM UsedFitEst. Speed
Qwen 3 0.6B600MQ4_K_M2.5 GBRuns~205 tok/s
Qwen 3.5 0.8B800MQ4_K_M1.5 GBRuns~341 tok/s
Gemma 3 1B1BQ8_02 GBRuns~256 tok/s
Llama 3.2 1B1BQ8_03 GBRuns~171 tok/s
DeepSeek R1 1.5B1.5BQ8_03 GBRuns~171 tok/s
SmolLM2 1.7B1.7BQ8_02.7 GBRuns~190 tok/s
Gemma 2 2B2BQ8_04 GBRuns~128 tok/s
Gemma 3n E2B2BQ4_K_M3.3 GBRuns~155 tok/s
Gemma 4 E2B2BQ4_K_M4 GBRuns~128 tok/s
Qwen 3.5 2B2BQ4_K_M3 GBRuns~171 tok/s
Llama 3.2 3B3BQ8_05 GBRuns~102 tok/s
StarCoder2 3B3BQ4_K_M3.5 GBRuns~146 tok/s
Phi-3 Mini 3.8B3.8BQ8_05.8 GBRuns~88 tok/s
Phi-4 Mini 3.8B3.8BQ4_K_M4.5 GBRuns~114 tok/s
Gemma 3 4B4BQ4_K_M5 GBRuns~102 tok/s
Gemma 3n E4B4BQ4_K_M4.5 GBRuns~114 tok/s
Gemma 4 E4B4BQ4_K_M6 GBRuns~85 tok/s
Qwen 3 4B4BQ4_K_M4.5 GBRuns~114 tok/s
Qwen 3.5 4B4BQ4_K_M4.5 GBRuns~114 tok/s
Yi 1.5 6B6BQ4_K_M5 GBRuns~102 tok/s
Codestral Mamba 7B7BQ4_K_M6.9 GBRuns~74 tok/s
DeepSeek R1 7B7BQ8_09 GBRuns~57 tok/s
Falcon 3 7B7BQ4_K_M6.8 GBRuns~75 tok/s
InternLM 2.5 7B7BQ4_K_M5.5 GBRuns~93 tok/s
Mistral 7B7BQ8_09 GBRuns~57 tok/s
OpenChat 3.5 7B7BQ4_K_M6.9 GBRuns~74 tok/s
Qwen 2.5 7B7BQ8_09 GBRuns~57 tok/s
Qwen 2.5 Coder 7B7BQ8_09 GBRuns~57 tok/s
Qwen 2.5 VL 7B7BQ4_K_M7 GBRuns~73 tok/s
StarCoder2 7B7BQ4_K_M5.5 GBRuns~93 tok/s
WizardLM 2 7B7BQ4_K_M6.9 GBRuns~74 tok/s
Aya Expanse 8B8BQ4_K_M6.5 GBRuns~79 tok/s
Cogito 8B8BQ4_K_M7.5 GBRuns~68 tok/s
DeepSeek R1 8B8BQ4_K_M7.5 GBRuns~68 tok/s
Dolphin 3 8B8BQ4_K_M6 GBRuns~85 tok/s
Granite 3.3 8B8BQ8_010 GBRuns~51 tok/s
Llama 3.1 8B8BQ8_010 GBRuns~51 tok/s
Nemotron 3 Nano 8B8BQ4_K_M7.5 GBRuns~68 tok/s
Nous Hermes 2 8B8BQ4_K_M6 GBRuns~85 tok/s
Qwen 3 8B8BQ4_K_M7.5 GBRuns~68 tok/s
Gemma 2 9B9BQ8_011 GBRuns~47 tok/s
Qwen 3.5 9B9BQ4_K_M7.5 GBRuns~68 tok/s
Yi 1.5 9B9BQ4_K_M6.5 GBRuns~79 tok/s
Yi Coder 9B9BQ4_K_M8 GBRuns~64 tok/s
Falcon 3 10B10BQ4_K_M8.5 GBRuns~60 tok/s
Llama 3.2 Vision 11B11BQ4_K_M8.5 GBRuns~60 tok/s
Gemma 3 12B12BQ4_K_M10.5 GBRuns~49 tok/s
Mistral Nemo 12B12BQ4_K_M9.5 GBRuns~54 tok/s
DeepSeek R1 14B14BQ4_K_M9.9 GBRuns~52 tok/s
Phi-4 14B14BQ4_K_M9.9 GBRuns~52 tok/s
Phi-4 Reasoning 14B14BQ4_K_M11 GBRuns~47 tok/s
Qwen 2.5 14B14BQ4_K_M9.9 GBRuns~52 tok/s
Qwen 2.5 Coder 14B14BQ4_K_M12 GBRuns~43 tok/s
Qwen 3 14B14BQ4_K_M12 GBRuns~43 tok/s
InternLM 2.5 20B20BQ4_K_M12 GBRuns~43 tok/s
Qwen 3.5 35B A3B35BQ4_K_M12 GBRuns~43 tok/s
gpt-oss 20B21BMXFP415 GBRuns (tight)~34 tok/s
Codestral 22B22BQ4_K_M14.7 GBRuns (tight)~35 tok/s
StarCoder2 15B15BQ8_017 GBCPU Offload~9 tok/s
Devstral 24B24BQ4_K_M17 GBCPU Offload~9 tok/s
Magistral Small 24B24BQ4_K_M17 GBCPU Offload~9 tok/s
Mistral Small 3.1 24B24BQ4_K_M18 GBCPU Offload~8 tok/s
Gemma 4 26B26BQ4_K_M20 GBCPU Offload~8 tok/s
Gemma 2 27B27BQ4_K_M17.7 GBCPU Offload~9 tok/s
Gemma 3 27B27BQ4_K_M20 GBCPU Offload~8 tok/s
Qwen 3.5 27B27BQ4_K_M19 GBCPU Offload~8 tok/s
Qwen 3.6 27B27BQ4_K_M20 GBCPU Offload~8 tok/s
Qwen 3 30B-A3B (MoE)30BQ4_K_M22 GBCPU Offload~7 tok/s
Gemma 4 31B31BQ4_K_M22 GBCPU Offload~7 tok/s
Aya Expanse 32B32BQ4_K_M22 GBCPU Offload~7 tok/s
Cogito 32B32BQ4_K_M21.5 GBCPU Offload~7 tok/s
DeepSeek R1 32B32BQ4_K_M20.7 GBCPU Offload~8 tok/s
Qwen 2.5 32B32BQ4_K_M20.7 GBCPU Offload~8 tok/s
Qwen 2.5 Coder 32B32BQ4_K_M23 GBCPU Offload~7 tok/s
Qwen 3 32B32BQ4_K_M23 GBCPU Offload~7 tok/s
QwQ 32B32BQ4_K_M21.5 GBCPU Offload~7 tok/s
Laguna XS 2.133BQ4_K_M22 GBCPU Offload~7 tok/s
WizardCoder 33B33BQ4_K_M22 GBCPU Offload~7 tok/s
Nous Hermes 2 34B34BQ4_K_M19 GBCPU Offload~8 tok/s
Yi 1.5 34B34BQ4_K_M21 GBCPU Offload~7 tok/s
Command R 35B35BQ4_K_M22.5 GBCPU Offload~7 tok/s
33 model(s) are too large for this hardware.