AAEON UP UP Squared Pro 7000

Products · · Board

AAEON UP UP Squared Pro 7000

Chip
Intel Core i3-N305
Unified memory
4, 8 or 16 GB
Released
2023

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
Intel Core i3-N305 · N50 4.0 GB 2.0 GB 38 GB/s 65 of 622 —
Intel Core i3-N305 8.0 GB 4.0 GB 38 GB/s 146 of 622 —
Intel Core i3-N305 · Core i3-N305 16.0 GB 8.0 GB 38 GB/s 163 of 622 —

Specifications 16.0 GB configuration

MakerAAEON UP
TypeBoard
ChipUP Squared Pro 7000 (16 GB) · Core i3-N305
Unified memory16.0 GB
Usable for AI models8.0 GB
Memory bandwidth38 GB/s
FP16 compute1.3 TFLOPS
NotesIntel Alder Lake-N (Core i3-N305, Atom x7425E, N97 or N50) with onboard LPDDR5 and two 2.5 GbE ports. The 16 GB version comes with the Core i3-N305.
Product pageup-board.org (opens in a new tab)

Best LLMs for the AAEON UP UP Squared Pro 7000 16.0 GB

Quality Model Quant Memory Speed Runs
76Great quality (A) · 76 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. K2 Horizon 7BInstitute of Foundation Models Q4_K_M 7.9 GB 4.0 tok/s Slowtight fit
57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. Ling 3.0 Tiny (8B-A1.3B)Ant Group (inclusionAI) Q4_K_M 6.3 GB 25.3 tok/s Runs well
74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. MiMo V2.6 Distill Qwen 9BXiaomi Q4_K_M 7.2 GB 3.8 tok/s Slowtight fit
74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. SenseNova Loop 9B PreviewSenseTime Q4_K_M 7.6 GB 3.7 tok/s Slowtight fit
73Great quality (A) · 73 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 9BDeepReinforce Q4_K_M 7.4 GB 3.7 tok/s Slowtight fit
72Great quality (A) · 72 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 9BAlibaba Q4_K_M 7.4 GB 3.7 tok/s Slowtight fit
71Great quality (A) · 71 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.0 9BDeepReinforce Q4_K_M 7.4 GB 3.7 tok/s Slowtight fit
71Great quality (A) · 71 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. TMax 9BAi2 Q5_K_M 7.9 GB 3.3 tok/s Slowtight fit
58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. Mellum2.1 Thinking (12B-A2.5B)JetBrains Q3_K_M 7.3 GB 17.6 tok/s Runs welltight fit
69Good quality (B) · 69 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 12BGoogle Q3_K_M 7.8 GB 3.9 tok/s Slowtight fit

Best Image models for the AAEON UP UP Squared Pro 7000 16.0 GB

Quality Model Quant Memory Speed Runs
76Great quality (A) · 76 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. FLUX.2 [klein] 4BBlack Forest Labs FP8 6.2 GB 39 s Runs wellencoder unloaded after use
84Great quality (A) · 84 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs Q4 GGUF 5.7 GB 4.9 min Very slowencoder unloaded after use
78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. Z-Image TurboAlibaba (Tongyi) Q4 GGUF 6.1 GB 2.2 min Slowencoder unloaded after use
52Fair quality (C) · 52 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. SDXL-Lightning (4-step)ByteDance FP8 5.6 GB 26 s Runs well
56Good quality (B) · 56 of 100: how capable the model is at FP8, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. DreamShaper XL v2 TurboLykon FP8 5.6 GB 48 s Slow
79Great quality (A) · 79 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-Image TurboBaidu Q4 GGUF 7.4 GB 2.8 min Very slowtight fit · encoder unloaded after use

Best Video models for the AAEON UP UP Squared Pro 7000 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 63/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP8 6.1 GB 16.1 min Slowencoder unloaded after use
35Basic quality (D) · 35 of 100: how capable the model is at FP16, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. AnimateDiff v3 (SD 1.5)Shanghai AI Lab FP16 4.7 GB 13.7 min Slow
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. Wan 2.1 T2V 1.3BAlibaba FP8 7.1 GB 2.6 h Very slowtight fit · encoder unloaded after use
44Fair quality (C) · 44 of 100: how capable the model is at FP8, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 2BZhipu AI FP8 6.2 GB 38.7 min Slowencoder unloaded after use
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 5BZhipu AI FP8 5.9 GB 2.4 h Very slowCPU offload

Best Decision models for the AAEON UP UP Squared Pro 7000 16.0 GB

Quality Model Quant Memory Speed Runs
78Great quality (A) · 78 of 100: how capable the model is at F16, whatever it runs on. Match score 88/100 (quality, fit, speed and memory use) sets the ranking. OpenAI Privacy FilterOpenAI F16 3.8 GB 27 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino Q8_0 1.2 GB 198 ms Runs well
68Good quality (B) · 68 of 100: how capable the model is at F16, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Llama Prompt Guard 2 22MMeta F16 0.8 GB 69 ms Runs great
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI Q8_0 2.1 GB 473 ms Slow
74Great quality (A) · 74 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. GLiClass ModernBERT Large v3Knowledgator Q8_0 1.1 GB 162 ms Runs well
70Great quality (A) · 70 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. GTE Reranker ModernBERT BaseAlibaba Q8_0 0.8 GB 123 ms Runs great
66Good quality (B) · 66 of 100: how capable the model is at F16, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. GLiClass Base v3Knowledgator F16 1.0 GB 90 ms Runs great
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI Q8_0 2.1 GB 473 ms Slow

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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