Exxact TensorEX Rackmount Workstation - TWS-154715021

Products · · Workstation

Exxact TensorEX Rackmount Workstation - TWS-154715021

Chips
16 GPU options, from NVIDIA RTX A400 to NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition
VRAM
4, 8, 20, 24, 32, 40, 48, 94 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 4000 SFF Ada Generation 20.0 GB 20.0 GB 280 GB/s 461 of 622 —
NVIDIA RTX 4000 Ada Generation 20.0 GB 20.0 GB 360 GB/s 461 of 622 —
NVIDIA L4 24.0 GB 24.0 GB 300 GB/s 466 of 622 —
NVIDIA RTX PRO 4000 Blackwell 24.0 GB 24.0 GB 672 GB/s 466 of 622 —
NVIDIA RTX 4500 Ada Generation 24.0 GB 24.0 GB 432 GB/s 466 of 622 —
NVIDIA RTX PRO 4500 Blackwell 32.0 GB 32.0 GB 896 GB/s 492 of 622 —
NVIDIA RTX 5000 Ada Generation 32.0 GB 32.0 GB 576 GB/s 489 of 622 —
NVIDIA A800 40GB Active 40.0 GB 40.0 GB 1,555 GB/s 511 of 622 —
NVIDIA L40 48.0 GB 48.0 GB 864 GB/s 516 of 622 —
NVIDIA L40S 48.0 GB 48.0 GB 864 GB/s 516 of 622 —
NVIDIA RTX PRO 5000 Blackwell 48GB 48.0 GB 48.0 GB 1,344 GB/s 517 of 622 —
NVIDIA RTX 6000 Ada Generation 48.0 GB 48.0 GB 960 GB/s 517 of 622 —
NVIDIA H100 NVL 94.0 GB 94.0 GB 3,900 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 24.0 GB configuration

MakerExxact
TypeWorkstation
ChipNVIDIA L4
Video memory (VRAM)24.0 GB
Usable for AI models24.0 GB
Memory bandwidth300 GB/s
FP16 compute30.3 TFLOPS
NotesWorkstation with NVIDIA RTX professional graphics; each option below is a GPU you can configure. Listed on the NVIDIA Marketplace.
Product pagewww.exxactcorp.com (opens in a new tab)

Best LLMs for the Exxact TensorEX Rackmount Workstation - TWS-154715021 24.0 GB

Quality Model Quant Memory Speed Runs
91Excellent quality (A+) · 91 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 95/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 26B-A4BGoogle Q6_K 23.4 GB 54.1 tok/s Runs welltight fit
88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.6 35B-A3BAlibaba Q4_K_M 23.9 GB 86.9 tok/s Runs welltight fit
88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM-V 4.7 35B-A3BOpenBMB Q4_K_M 23.4 GB 86.9 tok/s Runs welltight fit
88Excellent quality (A+) · 88 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 35B-A3BAlibaba Q4_K_M 23.9 GB 86.9 tok/s Runs welltight fit
87Excellent quality (A+) · 87 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Nex N2 Mini (35B-A3B)Nex-AGI Q4_K_M 23.4 GB 86.9 tok/s Runs welltight fit
86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. KAT-Coder V2.5 Dev (35B-A3B)Kuaishou Q4_K_M 23.1 GB 86.9 tok/s Runs welltight fit
86Excellent quality (A+) · 86 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Sage-A1.5 35B-A3BInternScience Q4_K_M 23.9 GB 86.9 tok/s Runs welltight fit
83Great quality (A) · 83 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Raon-1 mini Preview (30B-A4B)KRAFTON Q4_K_M 19.4 GB 66.5 tok/s Runs great
85Excellent quality (A+) · 85 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 35B-A3BDeepReinforce Q4_K_M 23.9 GB 86.9 tok/s Runs welltight fit
84Great quality (A) · 84 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Apodex 1.1 Mini (35B-A3B)Apodex Q4_K_M 23.9 GB 86.9 tok/s Runs welltight fit

Best Image models for the Exxact TensorEX Rackmount Workstation - TWS-154715021 24.0 GB

Quality Model Quant Memory Speed Runs
90Excellent quality (A+) · 90 of 100: how capable the model is at FP8, whatever it runs on. Match score 95/100 (quality, fit, speed and memory use) sets the ranking. Krea 2 TurboKrea FP8 20.2 GB 8.2 s Runs great
84Great quality (A) · 84 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-Image TurboBaidu Q8 GGUF 15.0 GB 7.8 s Runs great
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. FLUX.2 [klein] 9BBlack Forest Labs FP8 19.9 GB 3.4 s Runs great
89Excellent quality (A+) · 89 of 100: how capable the model is at FP8, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs FP8 12.4 GB 11 s Runs great
78Great quality (A) · 78 of 100: how capable the model is at FP16, whatever it runs on. Match score 90/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs FP16 18.1 GB 2.1 s Runs great
83Great quality (A) · 83 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. Z-Image TurboAlibaba (Tongyi) Q8 GGUF 13.0 GB 6.1 s Runs great

Best Video models for the Exxact TensorEX Rackmount Workstation - TWS-154715021 24.0 GB

Quality Model Quant Memory Speed Runs
86Excellent quality (A+) · 86 of 100: how capable the model is at FP8, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. LTX-2.5 (22B, video + audio)Lightricks FP8 19.7 GB 3.8 min Runs greatCPU offload
83Great quality (A) · 83 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. Bernini-R A14B (video generation + editing)ByteDance FP8 20.3 GB 24.1 min Slowencoder in RAM
50Fair quality (C) · 50 of 100: how capable the model is at FP16, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP16 17.5 GB 53 s Runs great
45Fair quality (C) · 45 of 100: how capable the model is at FP16, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 2BZhipu AI FP16 17.5 GB 2.1 min Runs great
72Great quality (A) · 72 of 100: how capable the model is at FP8, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. FramePack I2V (HunyuanVideo 13B)lllyasviel FP8 19.6 GB 13.4 min Slowencoder in RAM

Best Decision models for the Exxact TensorEX Rackmount Workstation - TWS-154715021 24.0 GB

Quality Model Quant Memory Speed Runs
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 94/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 4BAlibaba Q8_0 6.4 GB 120 ms Runs great
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 3.2 GB 25 ms Runs great
88Excellent quality (A+) · 88 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. zerank-2ZeroEntropy Q8_0 6.4 GB 120 ms Runs great
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Intern-Decision 4BShanghai AI Lab Q8_0 6.7 GB 81 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 3.2 GB 25 ms Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Shieldstral 1.0 3BMistral AI Q8_0 6.1 GB 115 ms Runs great
82Great quality (A) · 82 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. d1 3BLiquid AI F16 8.1 GB 77 ms Runs great
82Great quality (A) · 82 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. mxbai-rerank-large v2Mixedbread F16 4.9 GB 58 ms Runs great

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.

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