Intel · workstation

Arc Pro B50 16GB

Arc Pro B50 16GB has 16 GB of VRAM at 224 GB/s — about 14.88 GiB usable after driver and compositor overhead. 1815 of 2118 indexed models fit at 16K context with f16 KV.

Spec sheet· bandwidth, theoreticalFrom the file· fit from summed bytesPredicted· speed
Memory
16 GB
GDDR6
Bandwidth
224 GB/s
128-bit bus
Tensor FP16
85 TF
dense
TDP
70 W
$349 MSRP
Context4K8K16K32K64K128K
KV cachef16q8_0q4_0quantizing the KV cache is a ~2× lever on the dominant term at long context
vision language 159text 1553video 15audio asr 39image 2audio tts 21embedding 26

What fits at 16K context

largest quantization that fits, per model · 1815 of 2118 indexed
ModelBest quantParamsWeights●KV●Total in memory◐Headroom◐tok/s◐
Apriel-1.6-15b-ThinkerI1-Q6_K14.9B11.03 GiB3.00 GiB14.88 GiB0.00 GiB9±30%
Salience-1.5-FlashMoEI1-IQ3_M31.1B12.59 GiB1.50 GiB14.88 GiB0.00 GiB23±37%
Huihui-Qwen3-VL-30B-A3B-Instruct-abliteratedMoEI1-IQ3_M31.1B12.59 GiB1.50 GiB14.88 GiB0.00 GiB23±37%
Qwen3-30B-A3B-Gemini-Pro-High-Reasoning-2507-ABLITERATED-UNCENSOREDMoEI1-IQ3_M30.5B12.59 GiB1.50 GiB14.88 GiB0.00 GiB23±37%
MiroThinker-v1.0-30BMoEI1-IQ3_M30.5B12.59 GiB1.50 GiB14.88 GiB0.00 GiB23±37%
Qwen3-30B-A3B-YOYO-V5MoEI1-IQ3_M30.5B12.59 GiB1.50 GiB14.88 GiB0.00 GiB23±37%
Qwen3-30B-A3B-Thinking-2507-Claude-4.5-Sonnet-High-Reasoning-DistillMoEI1-IQ3_M30.5B12.59 GiB1.50 GiB14.88 GiB0.00 GiB23±37%
Huihui-Qwen3-30B-A3B-Thinking-2507-abliteratedMoEI1-IQ3_M30.5B12.59 GiB1.50 GiB14.88 GiB0.00 GiB23±37%
Huihui-Qwen3-30B-A3B-Instruct-2507-abliteratedMoEI1-IQ3_M30.5B12.59 GiB1.50 GiB14.88 GiB0.00 GiB23±37%
Qwen3-30B-A3B-abliterated-eroticMoEI1-IQ3_M30.5B12.59 GiB1.50 GiB14.88 GiB0.00 GiB23±37%
Huihui-Qwen3-Coder-30B-A3B-Instruct-abliteratedMoEI1-IQ3_M30.5B12.59 GiB1.50 GiB14.88 GiB0.00 GiB23±37%
Qwen3-Coder-30B-A3B-Instruct-RTPurboMoEI1-IQ3_M30.5B12.59 GiB1.50 GiB14.88 GiB0.00 GiB23±37%
Goetia-26B-A4B-v1.4MoEI1-Q3_K_L26.0B13.17 GiB0.92 GiB14.88 GiB0.00 GiB9±30%
G4-Moonlight-Dusk-26B-A4B-hereticMoEI1-Q3_K_L26.5B13.17 GiB0.92 GiB14.88 GiB0.00 GiB9±30%
Pantheon-Reasoning-26B-A4B-1.1-hereticMoEI1-Q3_K_L26.5B13.17 GiB0.92 GiB14.88 GiB0.00 GiB9±30%
G4-Moonlight-Dusk-26B-A4BMoEI1-Q3_K_L26.5B13.17 GiB0.92 GiB14.88 GiB0.00 GiB9±30%
Chimera-X-26B-A4BMoEI1-Q3_K_L26.5B13.17 GiB0.92 GiB14.88 GiB0.00 GiB9±30%
Pantheon-Reasoning-26B-A4B-1.1MoEI1-Q3_K_L26.5B13.17 GiB0.92 GiB14.88 GiB0.00 GiB9±30%
Gemma-4-26B-A4B-StyleTune-V2MoEI1-Q3_K_L26.5B13.17 GiB0.92 GiB14.88 GiB0.00 GiB9±30%
Gemma-4-26B-A4B-StyleTuneMoEI1-Q3_K_L26.5B13.17 GiB0.92 GiB14.88 GiB0.00 GiB9±30%
gemma-4-26b-a4b-heretic-styletune-v2-headMoEI1-Q3_K_L25.8B13.17 GiB0.92 GiB14.88 GiB0.00 GiB9±30%
Qwen3-Coder-REAP-25B-A3BMoEIQ4_XS24.9B12.57 GiB1.50 GiB14.87 GiB0.01 GiB22±37%
Huihui-GLM-4.7-Flash-abliterated-57BMoEI1-IQ1_M57.3B11.93 GiB2.09 GiB14.86 GiB0.02 GiB20±37%
Rocinante-XL-16B-v1I1-Q5_K_M16.1B10.63 GiB3.38 GiB14.85 GiB0.03 GiB9±30%
Le-Chaton-Slim-23BMoEI1-Q4_K_S23.3B12.42 GiB1.63 GiB14.85 GiB0.03 GiB15±37%
Laguna-XS-2.1MoEIQ3_XXS33.4B13.30 GiB0.74 GiB14.85 GiB0.03 GiB34±37%
Llama3.2-30B-A3B-II-Dark-Champion-INSTRUCT-Heretic-Abliterated-UncensoredMoEI1-IQ3_XXS30.0B11.09 GiB2.94 GiB14.84 GiB0.04 GiB14±37%
Pantheon-Reasoning-27BQ3_K_S27.8B12.98 GiB1.00 GiB14.84 GiB0.04 GiB9±30%
Qwen3.5-27BQ3_K_S27.8B12.98 GiB1.00 GiB14.84 GiB0.04 GiB9±30%
OpenAI-gpt-oss-20B-Claude-4.5-Opus-Heretic-UncensoredMoEI1-Q4_K_S20.9B13.65 GiB0.39 GiB14.83 GiB0.05 GiB24±37%
gpt-oss-20b-uncensoredMoEI1-Q4_K_S20.9B13.65 GiB0.39 GiB14.83 GiB0.05 GiB24±37%
gpt-oss-safeguard-20bMoEI1-Q4_K_S21.5B13.65 GiB0.39 GiB14.83 GiB0.05 GiB24±37%
Huihui-gpt-oss-20b-BF16-abliterated-v2MoEI1-Q4_K_S20.9B13.65 GiB0.39 GiB14.83 GiB0.05 GiB24±37%
metatune-gpt20b-R1.09MoEI1-Q4_K_S21.5B13.65 GiB0.39 GiB14.83 GiB0.05 GiB24±37%
gpt-oss-20b-DerestrictedMoEQ4_K_S20.9B13.65 GiB0.39 GiB14.83 GiB0.05 GiB24±37%
Qwen3.5-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-ThinkingI1-IQ2_M39.5B12.46 GiB1.50 GiB14.82 GiB0.06 GiB9±30%
Qwen3-42B-A3B-2507-Thinking-Abliterated-uncensored-TOTAL-RECALL-v2-Medium-MASTER-CODERMoEI1-IQ2_S42.4B11.93 GiB2.09 GiB14.82 GiB0.06 GiB20±37%
Aurora-Code-1MoEI1-Q3_K_M34.7B13.70 GiB0.31 GiB14.82 GiB0.06 GiB42±37%
codegeex4-all-9bIQ3_XXS9.4B3.97 GiB10.00 GiB14.81 GiB0.07 GiB9±30%
diffusiongemma-26B-A4B-it-HERETIC-UncensoredMoEIQ4_XS25.8B13.11 GiB0.92 GiB14.81 GiB0.07 GiB9±30%
Llama-3.2-8X3B-MOE-Dark-Champion-Instruct-uncensored-abliterated-18.4BMoEQ5_K_M18.4B12.25 GiB1.75 GiB14.81 GiB0.07 GiB13±37%
GRM-2.6-Plus-0628IQ3_M27.8B12.95 GiB1.00 GiB14.81 GiB0.07 GiB9±30%
ThinkingCap-Qwen3.6-27BIQ3_M27.4B12.95 GiB1.00 GiB14.81 GiB0.07 GiB9±30%
Tess-4-27BIQ3_M27.8B12.95 GiB1.00 GiB14.81 GiB0.07 GiB9±30%
glm-4-9b-chatIQ3_XXS9.4B3.97 GiB10.00 GiB14.81 GiB0.07 GiB9±30%
Wan2.2-S2V-14BQ5_K_M16.3B13.97 GiB0.00 GiB14.81 GiB0.07 GiB9±30%
Goetia-26B-A4B-v1.3-Absolute-Heretic-ARAMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
G4-MeroMero-26B-A4B-it-uncensored-hereticMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
EVE-26b-XENO-HATMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
Gemma-4-26B-A4B-Animus-V14.1-FFT-hereticMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
G4-MeroMero-26B-A4BMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
Huihui-gemma-4-26B-A4B-it-qat-q4_0-unquantized-abliteratedMoEIQ4_XS26.5B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
G4-Dark-Soul-26B-A4BMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
gemma-4-26B-A4B-it-SOMPOA-heresyMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
gemma-4-26B-A4B-it-heretic-ara-v2MoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
gemma-4-26B-A4B-Heretic-StableMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
gemma-4-26B-A4B-it-Uncensored-MAXMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
gemma-4-26B-A4B-it-ultra-uncensored-hereticMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
gemma-4-26B-A4B-it-uncensored-hereticMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
gemma-4-26B-A4B-it-ara-abliteratedMoEIQ4_XS25.8B13.10 GiB0.92 GiB14.80 GiB0.08 GiB9±30%
●From the file◐Predictedwhat 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.

Questions people ask

What AI models can a Arc Pro B50 16GB run?
1815 of 2118 indexed open-weight models fit a Arc Pro B50 16GB at 16,384 context with f16 KV cache, the largest being Apriel-1.6-15b-Thinker at I1-Q6_K. That covers text, vision-language, image, video and speech models.
How much usable memory does a Arc Pro B50 16GB 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 Arc Pro B50 16GB fast for local AI?
Its memory bandwidth is 224 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.