Quantitative Superiority on Sub-4B & 8B Architectures
Verify empirical latency benchmarks, 8,192-token financial reasoning precision, and real-world Total Cost of Ownership (TCO) savings vs. cloud frontier foundation models. Zero advertising clutter.
Interactive TCO & ROI Economics Calculator
Calculate enterprise savings when migrating financial document extraction from cloud APIs to self-hosted Ambiakshi SLM.
By running quantized 4-bit / 16-bit LoRA SLM weights in an air-gapped on-premise environment, you eliminate variable per-token API billing while maintaining 100% data sovereignty.
Head-to-Head Quantitative Benchmark Matrix
Empirical evaluation across task-specific accuracy, early-exit latency, throughput, and air-gapped compliance.
| Evaluation Dimension | Ambiakshi SLM Foundry | Competitor / Frontier Baseline | Architectural Advantage |
|---|---|---|---|
Intermediate Layer-24 Logit Rerank Latency | 0.24ms - 38.0ms | 185.0ms - 420.0ms ColBERTv2 / Cross-Encoder | 4.8x - 12x Faster TTFT |
SEC 10-K Balance Sheet & Covenant Accuracy | 94.2% | 89.1% OpenAI GPT-4o (Zero-Shot) | +5.1% Higher Precision |
Generation Throughput (RTX 4090 / A10G) | 118.5 tokens/sec | 42.0 tokens/sec 70B Cloud Endpoints | 2.8x Higher Concurrency |
Context Window Fidelity (Needle-in-Haystack) | 99.4% at 8,192 tokens | 91.2% (Context Degradation) FinBERT / Baseline RAG | Zero Sequence Truncation |
Numerical Scale Confusion Rate (M vs B) | 0.2% (Strict FP16 Logic) | 4.8% (Scale Hallucination) Standard Frontier Models | 24x Hallucination Reduction |
Data Privacy & Cloud Egress Risk | 0% (100% On-Premise Air-Gap) | High (Cloud API Transmission) Proprietary Cloud APIs | FINRA 24-09 & SEC 17a-4 Compliant |
JSON Schema Determinism & Adherence | 99.8% | 93.4% GPT-4o JSON Mode | +6.4% Deterministic Syntax |
Interactive Live Prompt Testing Sandbox
Test 8,192-token context reasoning, intermediate layer logit scoring, and observe real-time token count metrics.
Model Weights & Quantized GGUF Distribution
Download open-weight checkpoints or run instantly via Ollama, vLLM, and llama.cpp under Apache 2.0 commercial licensing.
Q4_K_M Medium Quant
Ultra-fast 4-bit quantized GGUF. Runs at 118+ tk/s on Apple Silicon Metal or single PCIe 16GB GPUs.
Q8_0 8-Bit Quantized
Near-lossless 8-bit integer quantization preserving full financial numerical scale precision and debt covenant extraction.
FP16 PyTorch / SafeTensors
Raw 16-bit floating point weights for vLLM, Hugging Face TGI, and continued enterprise LoRA adaptation.
Need Bespoke Domain SLMs or Air-Gapped VPC Deployments?
Partner with AMBIAKSHI TECHNOLOGY LLC for proprietary dataset curation, 16-bit LoRA / DPO alignment, and zero-egress VPC deployment on your private infrastructure.