AI Intelligence Platform

The BinghamSmartTablet

A tablet engineered with enough onboard compute to run local AI models without cloud dependency. Work offline. Think on-site.

09:42 BinghamOS 4.1 ●●●● 98%
Active Session
Field AI — Local Inference
Model 1116T // 16th Gen // 1.8 GHZ Octa-Core, Unisoc T7250 Processor // 30 GB RAM // 256 GB STORAGE // 12" AMOLED · 2000x1200 PX // LOCAL AI INFERENCE // 8800 Milliamp Hours // 802.11 a/b/g/n/ac, Bluetooth, Wi-Fi // Video Capture FHD 1080p, HD 720p // Model 1116T // 16th Gen // 1.8 GHZ Octa-Core, Unisoc T7250 Processor // 30 GB RAM // 256 GB STORAGE // 12" AMOLED · 2000x1200 PX // LOCAL AI INFERENCE // 8800 Milliamp Hours // 802.11 a/b/g/n/ac, Bluetooth, Wi-Fi // Video Capture FHD 1080p, HD 720p //
Technical Specifications

Built for the
edge.

Selected for maximum performance in off-grid conditions. No compromise.

Display
12" AMOLED
1200x2000 16:9
60Hz adaptive
IPS Anti-glare
Processor
Octa-Core, Unisoc T7250 Processor
1.8 GHz Proc Mali G57 GPU
Fast Render T7250 Tech
Memory
30 GB LPDDR5X
256 GB UFS 4.0 internal
MicroSDXC up to 2 TB
Unified memory architecture
Battery
8,000 mAh
12 hours standard use
100W fast charge · Solar assist port
Hot-swap modular battery bay
Connectivity
802.11 a/b/g/n/ac, Bluetooth, Wi-Fi
Sub-6GHz & mmWave 5G
Wi-Fi 7 (802.11be) · BT 5.4
USB-C 3.2 · Ethernet adapter · HDMI 2.1
Location
Multi-Band GNSS
GPS Enabled
Cameras
13 MP Main
Rear: FHD 1080p, HD 720p
Front: 8 MP f/2.0
Thermal imaging module (optional)
On-Device Intelligence

Local LLMs.
No signal required.

Architecture allows the Bingham Tablet to run quantized large language models entirely on-device. Your data never leaves the field.

Llama 3.2
Meta · Open Source
On-Device

Meta's flagship open-weight model. The 3B parameter version runs fast and smooth with 4-bit quantization. Excellent general reasoning, code assistance, and document analysis.

Model size: ~2.2 GB (Q4) RAM: ~3 GB
Mistral 7B
Mistral AI · Apache 2.0
On-Device

Outperforms models twice its size. The 7B parameter variant at Q4_K_M quantization delivers near-GPT-3.5 quality in technical domains — ideal for engineering field use.

Model size: ~4.1 GB (Q4) RAM: ~5.5 GB
Phi-3 Mini
Microsoft · MIT License
On-Device

3.8B parameter model with exceptional performance-per-byte. Microsoft trained it on high-quality synthetic data, making it surprisingly capable at logic, math, and structured output.

Model size: ~2.4 GB (Q4) RAM: ~3.2 GB
Gemma 2
Google DeepMind · Gemma ToS
On-Device

Google's 2B and 9B variants run comfortably on this hardware. Gemma 2 excels at instruction-following and multilingual tasks — valuable for international field deployments.

Model size: ~1.4 GB (Q4) RAM: ~2.1 GB
Qwen2.5 7B
Alibaba Cloud · Apache 2.0
On-Device

Top-tier multilingual model with strong code and math capabilities. Qwen2.5 is among the best open-weight 7B models available, covering 29+ languages with strong accuracy.

Model size: ~4.5 GB (Q4) RAM: ~5.8 GB
DeepSeek-R1 1.5B
DeepSeek · MIT License
Quantized

The distilled 1.5B reasoning model fits easily on-device and delivers chain-of-thought reasoning unusually capable for its size. Great for structured problem-solving in the field.

Model size: ~1 GB (Q4) RAM: ~1.8 GB
TinyLlama 1.1B
StatNLP Group · Apache 2.0
Ultra-Fast

Ultra-lightweight model for real-time assistance. When response latency matters most — voice prompts, sensor-triggered alerts, live classification — TinyLlama delivers in milliseconds.

Model size: ~600 MB (Q4) RAM: ~1 GB
Whisper Large v3
OpenAI · MIT License
Speech-to-Text

State-of-the-art offline speech recognition. Runs fully on-device enabling field technicians to dictate notes, query the LLM via voice, or transcribe interviews — in 99 languages, zero network needed.

Model size: ~3.1 GB RAM: ~4 GB
LLaVA-1.6 7B
LLaVA Team · Apache 2.0
Vision+Language

Multimodal model that understands both images and text. Point the tablet camera at equipment, diagrams, or field conditions and ask the AI what it sees — entirely offline, in real time.

Model size: ~4.5 GB (Q4) RAM: ~6 GB
Real-World Applications

Where it
matters most.

Local AI running on a rugged field tablet opens capabilities that were impossible with cloud-dependent tools. Here's how teams are deploying it today.

01
Remote Infrastructure Inspection

Field engineers photograph pipeline welds, structural joints, or electrical panels with the tablet camera. LLaVA-1.6 analyzes the image on-device, flags anomalies, cross-references stored maintenance manuals via RAG, and generates a structured inspection report — even in areas with zero cellular coverage.

Energy · Utilities · Construction
02
Classified & Air-Gapped Operations

Defense and government contractors can now leverage AI assistance inside secure facilities where internet access is prohibited. Running Mistral 7B or Llama 3 locally means zero data exfiltration risk. Analysts get intelligent document summarization, translation, and Q&A with full OPSEC compliance.

Defense · Government · Intelligence
03
Medical Triage in Austere Environments

Emergency medical teams in disaster zones or remote clinics use the tablet paired with Phi-3 Mini fine-tuned on clinical guidelines. Field medics dictate patient symptoms via Whisper, receive differential diagnoses and treatment protocols instantly — when the nearest hospital is hours away and bandwidth is unavailable.

Emergency Medicine · Humanitarian Aid
04
Agricultural & Environmental Monitoring

Agronomists and field scientists photograph soil conditions, plant disease, or water samples. The vision model identifies pest species, nutrient deficiencies, or contaminants with on-screen guidance. Sensor data from attached probes is interpreted and anomalies explained in plain language — without cloud subscription costs per reading.

Agriculture · Environmental Science · Research
05
Multilingual Field Interviews & Documentation

Journalists, aid workers, and researchers use Whisper + Qwen2.5 for live transcription and real-time translation across 29+ languages. Interview a local stakeholder in Swahili, have the AI produce an English summary and key-quote extraction — all stored locally, never uploaded to a third-party server.

Journalism · NGOs · Anthropology
06
Industrial Training & Guided Procedures

Technicians accessing LLMs via voice during maintenance procedures get step-by-step guidance without looking away from the work or touching a screen. TinyLlama handles fast sub-second responses for checklist-style queries, while Mistral handles complex troubleshooting. The system works inside RF-shielded equipment bays where phones are prohibited.

Manufacturing · Oil & Gas · Aerospace MRO