Vital-Med Tiny is a Qwen3.5-2B based GGUF model fine-tuned for offline healthcare and wellness guidance in African low-resource contexts.
The selected model is intended for CPU-only llama.cpp inference on ordinary laptops. It was built for the Africa Deep Tech Challenge 2026 Laptop LLM track.
Files
File
Description
vital-med-Q4_K_M.gguf
Selected GGUF submission artifact
Intended Use
Vital-Med Tiny provides educational health-information and wellness guidance:
symptom triage framing
red-flag reminders
malaria-aware patient education
child fever and dehydration guidance
blood-pressure and wellness coaching
desk-worker hydration and ergonomics
It is not a doctor, diagnostic system, or emergency service.
Runtime
llama-cli -m vital-med-Q4_K_M.gguf -p "My 3-year-old in Lagos has had fever for 2 days and is drinking poorly. What should I do now?"
If your llama.cpp build supports chat mode:
llama-cli -m vital-med-Q4_K_M.gguf -cnv
Model Details
Field
Value
Base
Qwen3.5-2B
Fine-tuning
bf16 LoRA SFT
Runtime
llama.cpp
Format
GGUF
Quantization
Q4_K_M
Primary language
English
Domain
Healthcare / medical guidance / wellness
Local Profiler Results
Measured on participant laptop with adtc-profiler 0.1.0:
Metric
Result
Generation throughput
10.41 tokens/s
First-token latency
13.24 s
Peak RSS
2.01 GB
Steady RSS
1.93 GB
arc_easy proxy
0.68 acc_norm, 50 samples
Thermal throttling
No
The model stays comfortably under the ADTC 7 GB RAM ceiling.
Model Selection
Three post-training candidates were evaluated:
Candidate
Decision
Original SFT Q4_K_M
Selected
Correction SFT
Rejected
Tiny DPO pass
Rejected
The correction and DPO runs were rejected because they improved isolated cases while reducing overall response quality.
Vital-Med Tiny is for educational guidance only. It may hallucinate, omit important red flags, or give incomplete advice. It should not replace clinicians, emergency care, or national medical guidelines.
The model was designed to avoid definitive diagnosis and to recommend professional care when symptoms may be serious. Users should seek qualified medical care for severe, persistent, or worsening symptoms.
Citation
If you discuss this model, cite it as:
Vital-Med Tiny, Africa Deep Tech Challenge 2026 Laptop LLM submission by Eddy Ejembi.
