AMD · consumer

Radeon RX 6800 XT

Radeon RX 6800 XT has 16 GB of VRAM at 512 GB/s — about 14.88 GiB usable after driver and compositor overhead. 1849 of 2118 indexed models fit at 8K context with f16 KV.

Spec sheet· bandwidth, theoreticalFrom the file· fit from summed bytesPredicted· speed
Memory
16 GB
GDDR6
Bandwidth
512 GB/s
256-bit bus
Tensor FP16
dense
TDP
300 W
$649 MSRP
KV cachef16q8_0q4_0quantizing the KV cache is a ~2× lever on the dominant term at long context
text 1585vision language 161audio asr 39video 15embedding 26image 2audio tts 21

What fits at 8K context

largest quantization that fits, per model · 1849 of 2118 indexed
ModelBest quantParamsWeightsKVTotal in memoryHeadroomtok/s
gemma-2-27b-itIQ3_M27.2B11.60 GiB2.25 GiB14.88 GiB0.00 GiB23±26.5%
magnum-v4-27bIQ3_M27.2B11.60 GiB2.25 GiB14.88 GiB0.00 GiB23±26.5%
Nemotron-Mini-4B-InstructQ8_04.2B12.96 GiB1.00 GiB14.88 GiB0.00 GiB23±26.5%
Skyfall-31B-v4.2-hereticI1-IQ3_XS31.4B12.17 GiB1.69 GiB14.88 GiB0.00 GiB23±26.5%
Skyfall-31B-v4.2I1-IQ3_XS31.4B12.17 GiB1.69 GiB14.88 GiB0.00 GiB23±26.5%
GLM-4-32B-0414-Korean-CultureI1-IQ3_S32.6B13.40 GiB0.48 GiB14.86 GiB0.02 GiB23±26.5%
Qwen3-Coder-REAP-25B-A3BMoEIQ4_NL24.9B13.22 GiB0.75 GiB14.86 GiB0.02 GiB68±37%
Seed-OSS-36B-InstructUD-IQ2_M36.2B11.86 GiB2.00 GiB14.85 GiB0.03 GiB23±26.5%
GLM-Z1-32B-0414Q3_K_S32.6B13.38 GiB0.48 GiB14.85 GiB0.03 GiB23±26.5%
GLM-4-32B-0414Q3_K_S32.6B13.38 GiB0.48 GiB14.85 GiB0.03 GiB23±26.5%
TildeOpen-30B-Instruct-LVI1-IQ3_XS30.7B11.99 GiB1.88 GiB14.85 GiB0.03 GiB23±26.5%
grug-27bQ3_K_M27.4B13.38 GiB0.50 GiB14.84 GiB0.04 GiB23±26.5%
Carnice-V2-27bQ3_K_M27.4B13.38 GiB0.50 GiB14.84 GiB0.04 GiB23±26.5%
Fara1.5-27BQ3_K_M27.4B13.38 GiB0.50 GiB14.84 GiB0.04 GiB23±26.5%
granite-20b-code-instruct-8kQ5_K_L20.1B13.86 GiB0.00 GiB14.84 GiB0.04 GiB23±26.5%
Devstral-Small-2-24B-Instruct-2512Q4_024.0B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Voxtral-Small-24B-2507Q4_024.3B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Transformed-Journey-24BI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Magistry-24B-v1.1I1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Mergedonia-AETHER-24B-v1aI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Mergedonia-AETHER-24B-v1bI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Slimaki-Tavern-24B-v1.3I1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Maginum-Cydoms-24BI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Maginum-Cydoms-24B-absolute-heresyI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Dolphin3.0-R1-Mistral-24BQ4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Dolphin3.0-Mistral-24BQ4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Mistral-Small-3.2-24B-Instruct-2506-ultra-uncensored-hereticI1-Q4_024.0B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Huihui-Mistral-Small-3.2-24B-Instruct-2506-abliterated-llamacppfixedI1-Q4_024.0B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Dans-PersonalityEngine-V1.2.0-24bI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Mistral-Small-3_2-24B-Instruct-2506-antislop.v2I1-Q4_024.0B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Cydonia_VistralQ4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Mistral-Small-3.2-24B-Instruct-2506Q4_024.0B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Dans-PersonalityEngine-V1.3.0-24bI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Devstral-Small-2507Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Goetia-24B-v1.1I1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Devstral-Small-2505Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
MS3.2-PaintedFantasy-v3-24BI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
RP-Spectrum-24BI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
MS3.2-PaintedFantasy-v4.1-24B-ultra-uncensored-heretic-v2I1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Magidonia-24B-v4.3-heretic-v1.2I1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Magidonia-24B-v4.3-absolute-heresyI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
MagiSeek-Pro-V1I1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Magistral-Small-2509Q4_024.0B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Magistral-Small-2507Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Cogidonia-v2-24BI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Magidonia-24B-v4.3I1-Q4_012.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Precog-24B-v1I1-Q4_012.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
experiment024bI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Magidonia-24B-v4.2.0Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Berthier-Mistral-Military-24BI1-Q4_024.0B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
MS-2501-DPE-QwQify-v0.1-24BQ4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Mistral-Small-3.2-24B-Instruct-2506-llamacppfixedI1-Q4_024.0B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Cydonia-24B-v4.3-absolute-heresyI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Cydonia-24B-v4.3-heretic-v2I1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Cydonia-24B-v4.3-hereticI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Cydonia-24B-v4.3-heretic-v4I1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Cydonia-24B-v4.2.0I1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Journeys-End-24BI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
sarvam-mQ4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±26.5%
Dolphin-Mistral-GLM-4.7-Flash-24B-Venice-Edition-Thinking-UncensoredI1-Q4_023.6B12.57 GiB1.25 GiB14.84 GiB0.04 GiB23±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 generation8.45 it/s5.9310.04215
Benchmarked· n=215

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 6800 XT run?
1849 of 2118 indexed open-weight models fit a Radeon RX 6800 XT at 8,192 context with f16 KV cache, the largest being gemma-2-27b-it at IQ3_M. That covers text, vision-language, image, video and speech models.
How much usable memory does a Radeon RX 6800 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 6800 XT fast for local AI?
Its memory bandwidth is 512 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.