Products · LattePanda · Board
LattePanda Sigma
- Chip
- Intel Core i5-1340P
- Unified memory
- 16 or 32 GB
- Launch price
- $579–$629
- Released
- 2023
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 i5-1340P | 16.0 GB | 8.0 GB | 102 GB/s | 307 of 622 | $579 |
| Intel Core i5-1340P | 32.0 GB | 16.0 GB | 102 GB/s | 376 of 622 | $629 |
Specifications 16.0 GB configuration
| Maker | LattePanda |
|---|---|
| Type | Board |
| Chip | LattePanda Sigma (16 GB) |
| Unified memory | 16.0 GB |
| Usable for AI models | 8.0 GB |
| Memory bandwidth | 102 GB/s |
| FP16 compute | 3.7 TFLOPS |
| Notes | Core i5-1340P with LPDDR5-6400. Launch prices for the board alone; kits with a 500 GB SSD and Wi-Fi were $648 (16 GB) and $698 (32 GB). The newer Sigma 2 uses a Core Ultra X7 358H. |
| Product page | www.lattepanda.com (opens in a new tab) |
Best LLMs for the LattePanda Sigma 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 80/100 (quality, fit, speed and memory use) sets the ranking. | K2 Horizon 7B | Q4_K_M | 7.9 GB | 10.7 tok/s | Runs welltight fit |
| 66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. | Nemotron 3.5 Bolt E4B | Q4_K_M | 6.3 GB | 21.3 tok/s | Runs well |
| 59Good quality (B) · 59 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. | Ling 3.0 Tiny (8B-A1.3B) | Q6_K | 7.9 GB | 43.3 tok/s | Runs welltight fit |
| 58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. | Mellum2.1 Thinking (12B-A2.5B) | Q3_K_M | 7.3 GB | 42.8 tok/s | Runs welltight fit |
| 64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. | Nanbeige4.2 3B | Q4_K_M | 5.3 GB | 23.0 tok/s | Runs well |
| 64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. | Gemma 4 E4B | Q4_K_M | 6.3 GB | 21.3 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 79/100 (quality, fit, speed and memory use) sets the ranking. | MiMo V2.6 Distill Qwen 9B | Q4_K_M | 7.2 GB | 10.2 tok/s | Runs welltight fit |
| 58Good quality (B) · 58 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. | Gemma 4 E2B | Q4_K_M | 4.4 GB | 41.7 tok/s | Runs great |
| 70Great quality (A) · 70 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. | TMax 9B | Q4_K_M | 7.0 GB | 10.7 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 78/100 (quality, fit, speed and memory use) sets the ranking. | Gemma 4 12B | Q3_K_M | 7.8 GB | 10.4 tok/s | Runs welltight fit |
Best Image models for the LattePanda Sigma 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 80/100 (quality, fit, speed and memory use) sets the ranking. | FLUX.2 [klein] 4B | FP8 | 6.2 GB | 17 s | Runs wellencoder unloaded after use |
| 52Fair quality (C) · 52 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. | SDXL-Lightning (4-step) | FP8 | 5.6 GB | 12 s | Runs great |
| 84Great quality (A) · 84 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. | FLUX 3 Image Klein | Q4 GGUF | 5.7 GB | 2.2 min | Slowencoder unloaded after use |
| 78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. | Z-Image Turbo | Q4 GGUF | 6.1 GB | 58 s | Slowencoder unloaded after use |
| 56Good quality (B) · 56 of 100: how capable the model is at FP8, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. | DreamShaper XL v2 Turbo | FP8 | 5.6 GB | 22 s | Runs well |
| 79Great quality (A) · 79 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. | ERNIE-Image Turbo | Q4 GGUF | 7.4 GB | 75 s | Slowtight fit · encoder unloaded after use |
Best Video models for the LattePanda Sigma 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 66/100 (quality, fit, speed and memory use) sets the ranking. | LTX-Video 2B | FP8 | 6.1 GB | 7.3 min | Runs wellencoder unloaded after use |
| 35Basic quality (D) · 35 of 100: how capable the model is at FP16, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. | AnimateDiff v3 (SD 1.5) | FP16 | 4.7 GB | 6.2 min | Runs well |
| 44Fair quality (C) · 44 of 100: how capable the model is at FP8, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. | CogVideoX 2B | FP8 | 6.2 GB | 17.5 min | Slowencoder unloaded after use |
| 53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. | Wan 2.1 T2V 1.3B | FP8 | 7.1 GB | 69.9 min | Very slowtight fit · encoder unloaded after use |
| 53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 54/100 (quality, fit, speed and memory use) sets the ranking. | CogVideoX 5B | FP8 | 5.9 GB | 64.9 min | Very slowCPU offload |
Best Decision models for the LattePanda Sigma 16.0 GB
| Quality | Model | Quant | Memory | Speed | Runs |
|---|---|---|---|---|---|
| 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 Decide | F16 | 1.7 GB | 81 ms | Runs great |
| 86Excellent quality (A+) · 86 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. | Jina Reranker v3.5 | Q8_0 | 2.1 GB | 167 ms | Runs well |
| 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. | FRIDA-Decisions | Q8_0 | 1.7 GB | 116 ms | Runs great |
| 84Great quality (A) · 84 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. | Jina Reranker v3 | Q8_0 | 2.1 GB | 167 ms | Runs well |
| 76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. | Llama Prompt Guard 2 86M | F16 | 1.2 GB | 92 ms | Runs great |
| 74Great quality (A) · 74 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. | GLiClass ModernBERT Large v3 | F16 | 1.5 GB | 67 ms | Runs great |
| 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 Filter | F16 | 3.8 GB | 12 ms | Runs great |
| 80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 87/100 (quality, fit, speed and memory use) sets the ranking. | Qwen3 Reranker 0.6B | Q8_0 | 2.1 GB | 167 ms | Runs well |
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.