BOXX APEXX T4 PRO-X

Products · · Workstation

BOXX APEXX T4 PRO-X

Chips
12 GPU options, from NVIDIA RTX A400 to NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition
VRAM
4, 8, 16, 24, 32, 48 or 96 GB
Released
2025

Product page (opens in a new tab) Full AI report

Configurations

Pick one to see which models it runs. More memory lets larger models fit; bandwidth sets how fast they answer.

Configuration Memory Usable for AI Bandwidth LLMs that run well Launch price
NVIDIA RTX A400 4.0 GB 4.0 GB 96 GB/s 215 of 622 —
NVIDIA RTX A1000 8.0 GB 8.0 GB 192 GB/s 338 of 622 —
NVIDIA RTX 2000 Ada Generation 16.0 GB 16.0 GB 224 GB/s 455 of 622 —
NVIDIA RTX PRO 2000 Blackwell 16.0 GB 16.0 GB 288 GB/s 457 of 622 —
NVIDIA RTX 4500 Ada Generation 24.0 GB 24.0 GB 432 GB/s 466 of 622 —
NVIDIA RTX PRO 4000 Blackwell 24.0 GB 24.0 GB 672 GB/s 466 of 622 —
NVIDIA RTX 5000 Ada Generation 32.0 GB 32.0 GB 576 GB/s 489 of 622 —
NVIDIA RTX PRO 4500 Blackwell 32.0 GB 32.0 GB 896 GB/s 492 of 622 —
NVIDIA RTX 6000 Ada Generation 48.0 GB 48.0 GB 960 GB/s 517 of 622 —
NVIDIA RTX PRO 5000 Blackwell 48GB 48.0 GB 48.0 GB 1,344 GB/s 517 of 622 —
NVIDIA RTX PRO 6000 Blackwell 96.0 GB 96.0 GB 1,792 GB/s 547 of 622 —
NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition 96.0 GB 96.0 GB 1,792 GB/s 547 of 622 —

Specifications 16.0 GB configuration

MakerBOXX
TypeWorkstation
ChipNVIDIA RTX 2000 Ada Generation
Video memory (VRAM)16.0 GB
Usable for AI models16.0 GB
Memory bandwidth224 GB/s
FP16 compute12.0 TFLOPS
NotesWorkstation with NVIDIA RTX professional graphics; each option below is a GPU you can configure. Listed on the NVIDIA Marketplace.
Product pageboxx.com (opens in a new tab)

Best LLMs for the BOXX APEXX T4 PRO-X 16.0 GB

Quality Model Quant Memory Speed Runs
77Great quality (A) · 77 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 26B-A4BGoogle Q3_K_M 14.4 GB 71.8 tok/s Runs welltight fit
73Great quality (A) · 73 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. Raon-1 mini Preview (30B-A4B)KRAFTON Q3_K_M 15.6 GB 65.2 tok/s Runs welltight fit
70Great quality (A) · 70 of 100: how capable the model is at MXFP4, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. gpt-oss 20BOpenAI MXFP4 13.5 GB 64.1 tok/s Runs great
69Good quality (B) · 69 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. Mellum2.1 Thinking (12B-A2.5B)JetBrains Q6_K 11.5 GB 59.8 tok/s Runs great
78Great quality (A) · 78 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 12BGoogle Q4_K_M 9.4 GB 23.0 tok/s Runs well
67Good quality (B) · 67 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Maple Preview (20B-A1B)DeepGrove Q5_K_M 15.9 GB 99.4 tok/s Runs welltight fit
76Great quality (A) · 76 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. K2 Horizon 7BInstitute of Foundation Models Q4_K_M 8.1 GB 30.6 tok/s Runs great
66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. ERNIE 4.5 21B-A3B ThinkingBaidu Q4_K_M 15.2 GB 70.0 tok/s Runs welltight fit
80Great quality (A) · 80 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.8 27BAlibaba Q3_K_M 15.5 GB 12.8 tok/s Runs welltight fit
65Good quality (B) · 65 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. DiffusionGemma 26B-A4B ITGoogle Q3_K_M 14.5 GB 69.0 tok/s Runs welltight fit

Best Image models for the BOXX APEXX T4 PRO-X 16.0 GB

Quality Model Quant Memory Speed Runs
82Great quality (A) · 82 of 100: how capable the model is at FP8, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Z-Image TurboAlibaba (Tongyi) FP8 12.6 GB 9.6 s Runs great
89Excellent quality (A+) · 89 of 100: how capable the model is at FP8, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs FP8 12.4 GB 22 s Runs well
77Great quality (A) · 77 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs Q8 GGUF 10.5 GB 4.9 s Runs great
83Great quality (A) · 83 of 100: how capable the model is at FP8, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-Image TurboBaidu FP8 14.5 GB 12 s Runs welltight fit
83Great quality (A) · 83 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 9BBlack Forest Labs Q8 GGUF 12.3 GB 9.2 s Runs greatencoder in RAM
65Good quality (B) · 65 of 100: how capable the model is at NF4, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. FLUX.1 [schnell]Black Forest Labs NF4 14.4 GB 9.3 s Runs welltight fit

Best Video models for the BOXX APEXX T4 PRO-X 16.0 GB

Quality Model Quant Memory Speed Runs
49Fair quality (C) · 49 of 100: how capable the model is at FP8, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP8 10.8 GB 1.6 min Runs great
44Fair quality (C) · 44 of 100: how capable the model is at FP8, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 2BZhipu AI FP8 11.0 GB 3.8 min Runs great
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. Wan 2.1 T2V 1.3BAlibaba FP8 12.8 GB 15.3 min Slow
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 5BZhipu AI FP8 14.3 GB 11.5 min Runs welltight fit
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 69/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 5B I2VZhipu AI FP8 14.9 GB 11.5 min Runs welltight fit

Best Decision models for the BOXX APEXX T4 PRO-X 16.0 GB

Quality Model Quant Memory Speed Runs
86Excellent quality (A+) · 86 of 100: how capable the model is at F16, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI F16 2.8 GB 49 ms Runs great
84Great quality (A) · 84 of 100: how capable the model is at F16, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI F16 2.8 GB 49 ms Runs great
82Great quality (A) · 82 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. mxbai-rerank-large v2Mixedbread Q8_0 3.1 GB 106 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. FRIDA-DecisionsSber AI F16 2.4 GB 34 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino F16 1.7 GB 22 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 0.6BAlibaba F16 2.8 GB 49 ms Runs great
82Great quality (A) · 82 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking. d1 3BLiquid AI Q8_0 4.7 GB 119 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. zerank-1 smallZeroEntropy Q8_0 3.5 GB 118 ms Runs great

Other products with the NVIDIA RTX 2000 Ada Generation

Spec sources

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

Was this page helpful?