AMD · consumer

Radeon RX 9070 XT

Radeon RX 9070 XT has 16 GB of VRAM at 640 GB/s — about 14.88 GiB usable after driver and compositor overhead. 854 of 2118 indexed models fit at 128K context with f16 KV.

Spec sheet· bandwidth, theoreticalFrom the file· fit from summed bytesPredicted· speed
Memory
16 GB
GDDR6
Bandwidth
640 GB/s
256-bit bus
Tensor FP16
dense
TDP
304 W
$599 MSRP
KV cachef16q8_0q4_0quantizing the KV cache is a ~2× lever on the dominant term at long context
text 665vision language 101audio asr 35video 15audio tts 18embedding 19image 1

What fits at 128K context

largest quantization that fits, per model · 854 of 2118 indexed
ModelBest quantParamsWeightsKVTotal in memoryHeadroomtok/s
Kimi-Linear-48B-A3B-InstructMoEIQ1_M49.1B10.17 GiB3.80 GiB14.88 GiB0.00 GiB29±26.5%
GLM-4.7-Flash-REAP-23B-A3B-absolute-heresyMoEI1-Q2_K_S23.0B7.36 GiB6.61 GiB14.88 GiB0.00 GiB30±37%
Ministral-3-3B-Instruct-2512UD-IQ1_M3.8B0.95 GiB13.00 GiB14.86 GiB0.02 GiB29±26.5%
Ministral-3-3B-Reasoning-2512UD-IQ1_M4.3B0.95 GiB13.00 GiB14.86 GiB0.02 GiB29±26.5%
gpt-oss-20bMoEQ2_K_L21.5B10.95 GiB3.02 GiB14.86 GiB0.02 GiB45±37%
gpt-oss-safeguard-20bMoEQ2_K_L21.5B10.95 GiB3.02 GiB14.86 GiB0.02 GiB45±37%
ERNIE-21B-A3B-Thinking-Gemini-3-Pro-High-Reasoning-V2I1-Q2_K_S21.8B6.94 GiB7.00 GiB14.86 GiB0.02 GiB29±26.5%
ERNIE-21B-A3B-Claude-4.5-High-OPUS-ThinkingI1-Q2_K_S21.8B6.94 GiB7.00 GiB14.86 GiB0.02 GiB29±26.5%
ERNIE-4.5-21B-A3B-ThinkingI1-Q2_K_S21.8B6.94 GiB7.00 GiB14.86 GiB0.02 GiB29±26.5%
Ling-liteMoEIQ3_XXS16.8B6.96 GiB7.00 GiB14.85 GiB0.03 GiB28±37%
Felldude-Uncensored-Ministral3-3B-bf16I1-IQ1_M3.8B0.93 GiB13.00 GiB14.84 GiB0.04 GiB29±26.5%
Amaretto-3BI1-IQ1_M4.3B0.93 GiB13.00 GiB14.84 GiB0.04 GiB29±26.5%
Goetia-26B-A4B-v1.3-Absolute-Heretic-ARAMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
Frank-26B-A4BMoEI1-IQ2_XXS26.5B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
G4-MeroMero-26B-A4B-it-uncensored-hereticMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
EVE-26b-XENO-HATMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
Gemma-4-26B-A4B-Animus-V14.1-FFT-hereticMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-it-qat-q4_0-unquantized-hereticMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
Huihui-gemma-4-26B-A4B-it-qat-q4_0-unquantized-abliteratedMoEI1-IQ2_XXS26.5B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
G4-MeroMero-26B-A4BMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
G4-Dark-Soul-26B-A4BMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-it-local-abliterated-sota-internal-t34MoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-it-SOMPOA-heresyMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-it-hereticMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-it-abliterixMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-it-heretic-ara-v2MoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
Gemma-4-26B-A4B-it-heretic-antislopMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-it-Claude-Opus-Distill-v2MoEI1-IQ2_XXS26.5B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-Heretic-StableMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-it-Uncensored-MAXMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-it-ultra-uncensored-hereticMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-it-ara-abliteratedMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
Huihui-gemma-4-26B-A4B-it-abliteratedMoEI1-IQ2_XXS26.5B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
Gemma-4-26B-A4B-AbliteratedMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma4-26b-fiction-bf16MoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
gemma-4-26B-A4B-it-heretic-araMoEI1-IQ2_XXS25.8B8.66 GiB5.29 GiB14.84 GiB0.04 GiB29±26.5%
granite-20b-code-instruct-8kQ5_K_L20.1B13.86 GiB0.00 GiB14.84 GiB0.04 GiB29±26.5%
Ling-mini-2.0MoEQ4_K_S16.3B8.94 GiB5.00 GiB14.83 GiB0.05 GiB39±37%
Huihui-gpt-oss-20b-BF16-abliteratedMoEQ5_K_M20.9B10.92 GiB3.02 GiB14.83 GiB0.05 GiB45±37%
gemma-4-12BIQ3_M12.0B5.41 GiB8.47 GiB14.83 GiB0.05 GiB29±26.5%
granite-speech-4.1-2b-plusBF162.1B3.94 GiB10.00 GiB14.82 GiB0.06 GiB29±26.5%
Qwen3-15B-A2B-BaseMoEIQ4_XS15.6B7.91 GiB6.00 GiB14.81 GiB0.07 GiB33±37%
DeepSeek-V2-Lite-ChatMoEQ5_015.7B10.10 GiB3.80 GiB14.80 GiB0.08 GiB42±37%
granite-4.0-h-tinyMoEBF166.9B12.94 GiB1.00 GiB14.80 GiB0.08 GiB73±37%
granite-4.0-h-tiny-baseMoEBF166.9B12.94 GiB1.00 GiB14.80 GiB0.08 GiB73±37%
EVA-Yi-1.5-9B-32K-V1I1-IQ1_S8.8B1.88 GiB12.00 GiB14.80 GiB0.08 GiB29±26.5%
Yi-Coder-9B-ChatIQ1_S8.8B1.88 GiB12.00 GiB14.80 GiB0.08 GiB29±26.5%
Qwen3.5-21B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-ThinkingI1-Q2_K21.3B7.82 GiB6.00 GiB14.79 GiB0.09 GiB29±26.5%
Qwen3.6-21B-IQ-Ultra-Heretic-Uncensored-ThinkingI1-Q2_K21.3B7.82 GiB6.00 GiB14.79 GiB0.09 GiB29±26.5%
Laguna-XS-2.1MoEIQ2_XXS33.4B8.76 GiB5.12 GiB14.78 GiB0.10 GiB38±37%
North-Mini-Code-1.0MoEQ2_K30.5B10.33 GiB3.57 GiB14.77 GiB0.11 GiB46±37%
granite-20b-code-base-8kI1-Q5_K_M20.1B13.79 GiB0.00 GiB14.77 GiB0.11 GiB29±26.5%
granite-34b-code-base-8kI1-IQ3_S33.7B13.79 GiB0.00 GiB14.77 GiB0.11 GiB29±26.5%
gemma-4-A4B-98e-v6-coder-itMoEIQ3_XS20.5B8.58 GiB5.29 GiB14.76 GiB0.12 GiB29±26.5%
Qwen3.5-27B-Engineer-Deckard-GeminiI1-IQ1_S27.7B5.80 GiB8.00 GiB14.76 GiB0.12 GiB29±26.5%
Qwen3.5-27B-HERETIC-Polaris-Advanced-Thinking-Alpha-uncensoredI1-IQ1_S27.4B5.80 GiB8.00 GiB14.76 GiB0.12 GiB29±26.5%
Qwen3.5-27B-Deckard-PKD-Heretic-Uncensored-ThinkingI1-IQ1_S27.4B5.80 GiB8.00 GiB14.76 GiB0.12 GiB29±26.5%
Huihui-Qwen3.5-27B-abliteratedI1-IQ1_S27.8B5.80 GiB8.00 GiB14.76 GiB0.12 GiB29±26.5%
Qwen3.5-27B-Unredacted-MAXI1-IQ1_S27.4B5.80 GiB8.00 GiB14.76 GiB0.12 GiB29±26.5%
Qwen3.5-27B-hereticI1-IQ1_S27.4B5.80 GiB8.00 GiB14.76 GiB0.12 GiB29±26.5%
From the filePredictedwhat these mean

Speed is modeled, not measured: decode is memory-bandwidth bound, so tokens per second is bytes read per token against achievable bandwidth. Mixture-of-experts models carry a wider band because only the routed experts are read each step, and few have been measured publicly.

Measured on this card

third-party benchmarks, aggregated
WorkloadMedianMiddle 50%Runs
Image generation5.76 it/s2.5411.88118
Prompt processing4275.83 tok/s3591.414809.8730
Text generation95.24 tok/s86.48108.0130
Benchmarked· n=118

Aggregated from community-submitted runs, so the spread is wide by nature — it covers different models, resolutions, step counts and settings, not one controlled configuration. Read the middle 50% rather than the median alone. These figures are reproduced with attribution from vladmandic-sd-data-benchmark, which publishes no licence — so we display and link rather than redistribute them.

Questions people ask

What AI models can a Radeon RX 9070 XT run?
854 of 2118 indexed open-weight models fit a Radeon RX 9070 XT at 131,072 context with f16 KV cache, the largest being Kimi-Linear-48B-A3B-Instruct at IQ1_M. That covers text, vision-language, image, video and speech models.
How much usable memory does a Radeon RX 9070 XT actually have?
Its nameplate is 16 GB, but about 14.88 GiB is available to a model once driver and compositor overhead is accounted for.
Is a Radeon RX 9070 XT fast for local AI?
Its memory bandwidth is 640 GB/s, and that figure — not teraflops — is what governs token generation speed. Capacity decides what you can run; bandwidth decides how fast it runs.