AMD · consumer

Radeon RX 6700 XT

Radeon RX 6700 XT has 12 GB of VRAM at 384 GB/s — about 11.16 GiB usable after driver and compositor overhead. 1711 of 2118 indexed models fit at 16K context with q8_0 KV.

Spec sheet· bandwidth, theoreticalFrom the file· fit from summed bytesPredicted· speed
Memory
12 GB
GDDR6
Bandwidth
384 GB/s
192-bit bus
Tensor FP16
dense
TDP
230 W
$479 MSRP
KV cachef16q8_0q4_0quantizing the KV cache is a ~2× lever on the dominant term at long context
text 1467vision language 142audio tts 21video 14audio asr 39image 2embedding 26

What fits at 16K context

largest quantization that fits, per model · 1711 of 2118 indexed
ModelBest quantParamsWeightsKVTotal in memoryHeadroomtok/s
Huihui-Qwen3-Coder-30B-A3B-Instruct-abliteratedMoEI1-IQ2_M30.5B9.47 GiB0.80 GiB11.16 GiB0.00 GiB67±37%
Qwen3-Coder-30B-A3B-Instruct-RTPurboMoEI1-IQ2_M30.5B9.47 GiB0.80 GiB11.16 GiB0.00 GiB67±37%
Nous-Capybara-limarpv3-34BI1-IQ1_M34.4B8.18 GiB1.99 GiB11.15 GiB0.01 GiB24±26.5%
Muse-Glimmer-30BUD-IQ2_XXS29.8B10.01 GiB0.16 GiB11.15 GiB0.01 GiB24±26.5%
glm-4-9b-chat-abliteratedIQ4_XS9.4B4.89 GiB5.31 GiB11.15 GiB0.01 GiB24±26.5%
GLM-4.7-Flash-hereticMoEIQ2_M29.9B9.80 GiB0.44 GiB11.15 GiB0.01 GiB79±37%
dolphin-2.6-mixtral-8x7bMoEI1-IQ1_S46.7B9.15 GiB1.06 GiB11.15 GiB0.01 GiB36±37%
xLAM-8x7b-rMoEIQ1_S46.7B9.15 GiB1.06 GiB11.15 GiB0.01 GiB36±37%
Qwen3.5-40B-RoughHouse-Claude-4.6-Opus-Polar-Deckard-Uncensored-Heretic-ThinkingI1-IQ1_S39.5B9.38 GiB0.80 GiB11.14 GiB0.02 GiB24±26.5%
GLM-4.7-FlashMoEUD-IQ2_XXS31.2B9.79 GiB0.44 GiB11.14 GiB0.02 GiB79±37%
ERNIE-21B-A3B-Thinking-Gemini-3-Pro-High-Reasoning-V2I1-Q3_K_M21.8B9.75 GiB0.46 GiB11.13 GiB0.03 GiB24±26.5%
ERNIE-21B-A3B-Claude-4.5-High-OPUS-ThinkingI1-Q3_K_M21.8B9.75 GiB0.46 GiB11.13 GiB0.03 GiB24±26.5%
ERNIE-4.5-21B-A3B-ThinkingI1-Q3_K_M21.8B9.75 GiB0.46 GiB11.13 GiB0.03 GiB24±26.5%
Bielik-11B-v2.3-InstructQ6_K11.2B8.53 GiB1.66 GiB11.13 GiB0.03 GiB24±26.5%
Darwin-35B-A3B-OpusMoEIQ2_XS36.0B10.06 GiB0.17 GiB11.13 GiB0.03 GiB112±37%
Aurora-Code-1MoEIQ2_XS34.7B10.06 GiB0.17 GiB11.13 GiB0.03 GiB112±37%
grug-35b-v2MoEIQ2_XS35.1B10.06 GiB0.17 GiB11.13 GiB0.03 GiB112±37%
grug-35bMoEIQ2_XS35.1B10.06 GiB0.17 GiB11.13 GiB0.03 GiB112±37%
WorldSim-Opus-3.6-35B-A3BMoEIQ2_XS35.1B10.06 GiB0.17 GiB11.13 GiB0.03 GiB112±37%
Qwen3.6-35B-A3B-AnkoMoEIQ2_XS35.1B10.06 GiB0.17 GiB11.13 GiB0.03 GiB112±37%
KAT-Coder-V2.5-DevMoEIQ2_XS34.7B10.06 GiB0.17 GiB11.13 GiB0.03 GiB112±37%
Ornith-1.0-35BMoEIQ2_XS34.7B10.06 GiB0.17 GiB11.13 GiB0.03 GiB112±37%
Nex-N2-miniMoEIQ2_XS35.1B10.06 GiB0.17 GiB11.13 GiB0.03 GiB112±37%
Qwen3-16B-A3BMoEQ4_116.0B9.43 GiB0.80 GiB11.12 GiB0.04 GiB53±37%
Devstral-Small-2-24B-Instruct-2512UD-IQ3_XXS24.0B8.76 GiB1.33 GiB11.11 GiB0.05 GiB24±26.5%
Mistral-Small-3.2-24B-Instruct-2506UD-IQ3_XXS24.0B8.76 GiB1.33 GiB11.11 GiB0.05 GiB24±26.5%
Devstral-Small-2507UD-IQ3_XXS23.6B8.76 GiB1.33 GiB11.11 GiB0.05 GiB24±26.5%
Devstral-Small-2505UD-IQ3_XXS23.6B8.76 GiB1.33 GiB11.11 GiB0.05 GiB24±26.5%
Magistral-Small-2509UD-IQ3_XXS24.0B8.76 GiB1.33 GiB11.11 GiB0.05 GiB24±26.5%
Magistral-Small-2507UD-IQ3_XXS23.6B8.76 GiB1.33 GiB11.11 GiB0.05 GiB24±26.5%
Mistral-Small-3.1-24B-Instruct-2503UD-IQ3_XXS24.0B8.76 GiB1.33 GiB11.11 GiB0.05 GiB24±26.5%
Magistral-Small-2506UD-IQ3_XXS23.6B8.76 GiB1.33 GiB11.11 GiB0.05 GiB24±26.5%
Qwen3.8-27BUD-IQ2_M27.8B9.61 GiB0.53 GiB11.11 GiB0.05 GiB24±26.5%
InternVL3_5-30B-A3BQ2_K30.8B10.16 GiB0.00 GiB11.10 GiB0.06 GiB24±26.5%
Rocinante-XL-16B-v1IQ4_XS16.1B8.36 GiB1.79 GiB11.10 GiB0.06 GiB24±26.5%
EuroLLM-22B-Instruct-2512IQ3_XXS22.6B8.34 GiB1.79 GiB11.10 GiB0.06 GiB24±26.5%
Snowpiercer-15B-v4-hereticI1-Q4_K_M15.0B8.49 GiB1.66 GiB11.09 GiB0.07 GiB24±26.5%
Snowpiercer-15B-v4Q4_K_M15.0B8.49 GiB1.66 GiB11.09 GiB0.07 GiB24±26.5%
North-Mini-Code-1.0MoEIQ2_M30.5B9.82 GiB0.38 GiB11.09 GiB0.07 GiB81±37%
Phi-3-mini-4k-instructKV unresolvedIQ4_XS3.8B6.99 GiB3.19 GiB11.08 GiB0.08 GiB24±26.5%
GRM-2.6-Plus-0628IQ2_S27.8B9.59 GiB0.53 GiB11.08 GiB0.08 GiB24±26.5%
ThinkingCap-Qwen3.6-27BIQ2_S27.4B9.59 GiB0.53 GiB11.08 GiB0.08 GiB24±26.5%
Tess-4-27BIQ2_S27.8B9.59 GiB0.53 GiB11.08 GiB0.08 GiB24±26.5%
Nemotron-Mini-4B-InstructQ5_K_S4.2B9.10 GiB1.06 GiB11.08 GiB0.08 GiB24±26.5%
Qwen3-42B-A3B-2507-Thinking-Abliterated-uncensored-TOTAL-RECALL-v2-Medium-MASTER-CODERMoEI1-IQ1_M42.4B9.08 GiB1.11 GiB11.08 GiB0.08 GiB59±37%
MythoMax-L2-13bI1-IQ2_XXS13.0B3.50 GiB6.64 GiB11.08 GiB0.08 GiB24±26.5%
Llama3.2-24B-A3B-II-Dark-Champion-INSTRUCT-Heretic-Abliterated-UncensoredMoEIQ4_XS18.0B9.24 GiB0.93 GiB11.08 GiB0.08 GiB51±37%
Qwen3-VL-8B-Instruct-HereticI1-Q4_K_S8.8B8.94 GiB1.20 GiB11.07 GiB0.09 GiB24±26.5%
Apriel-1.6-15b-ThinkerI1-Q4_114.9B8.53 GiB1.59 GiB11.07 GiB0.09 GiB24±26.5%
gemma-4-12BQ6_K_M12.0B9.34 GiB0.78 GiB11.07 GiB0.09 GiB24±26.5%
Llama3.2-30B-A3B-II-Dark-Champion-INSTRUCT-Heretic-Abliterated-UncensoredMoEI1-IQ2_S30.0B8.60 GiB1.56 GiB11.07 GiB0.09 GiB43±37%
Qwen3.6-35B-A3B-REAM-160-ru-agentMoEIQ3_M23.6B9.99 GiB0.17 GiB11.06 GiB0.10 GiB98±37%
UncensoredLM-DeepSeek-R1-Distill-Qwen-14BQ4_K_L14.2B8.58 GiB1.53 GiB11.06 GiB0.10 GiB24±26.5%
medgemma-27b-itI1-Q2_K_S28.8B9.09 GiB0.99 GiB11.06 GiB0.10 GiB24±26.5%
gemma-3-27b-it-abliterated-refined-visionI1-Q2_K_S27.4B9.09 GiB0.99 GiB11.06 GiB0.10 GiB24±26.5%
Nidum-Gemma-3-27B-it-UncensoredI1-Q2_K_S27.4B9.09 GiB0.99 GiB11.06 GiB0.10 GiB24±26.5%
AtomicGPT-gemma3-27bI1-Q2_K_S27.4B9.09 GiB0.99 GiB11.06 GiB0.10 GiB24±26.5%
Unbound-v1.12.0-27BI1-Q2_K_S27.4B9.09 GiB0.99 GiB11.06 GiB0.10 GiB24±26.5%
Mira-v1.12-Ties-27BI1-Q2_K_S27.4B9.09 GiB0.99 GiB11.06 GiB0.10 GiB24±26.5%
Medgamma27BI1-Q2_K_S27.0B9.09 GiB0.99 GiB11.06 GiB0.10 GiB24±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 generation4.87 it/s3.346.76422
Benchmarked· n=422

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 6700 XT run?
1711 of 2118 indexed open-weight models fit a Radeon RX 6700 XT at 16,384 context with q8_0 KV cache, the largest being Huihui-Qwen3-Coder-30B-A3B-Instruct-abliterated at I1-IQ2_M. That covers text, vision-language, image, video and speech models.
How much usable memory does a Radeon RX 6700 XT actually have?
Its nameplate is 12 GB, but about 11.16 GiB is available to a model once driver and compositor overhead is accounted for.
Is a Radeon RX 6700 XT fast for local AI?
Its memory bandwidth is 384 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.