Open-weight model specialization & efficiency
Huyawo Solutions specializes in fine-tuning and quantizing open-weight language models for companies that need higher task-specific performance at substantially lower inference cost.
Illustrative example. Every engagement is evaluated against the client’s actual workload and success criteria.
No permanent dependency on Huyawo required.
Commercial engagements
Fixed-fee, fixed-scope work built around measurable task performance, deployment constraints, and economic outcomes.
01
Determine whether replacing, specializing, or compressing your current model is technically and economically worth doing. Includes baseline analysis, open-weight candidates, data readiness, deployment constraints, projected economics, and a documented go/no-go recommendation.
02
Test whether a smaller open-weight model can beat your current model on the task you actually care about. We baseline, prepare data, fine-tune, evaluate, analyze errors, and deliver the specialized model or adapters with reproducible evidence.
03
Find the lowest-cost production configuration that preserves the quality your workload actually requires. We evaluate precision, memory, latency, throughput, task quality, runtime behavior, and hardware fit as one quality/cost frontier.
04
Replace an oversized proprietary model with a specialized, efficient open-weight model without sacrificing the task performance that matters. Fine-tuning, evaluation, quantization, model economics, and deployment analysis are combined in one engagement.
Our operating thesis
It is the smallest model that reliably clears the required performance bar. Proprietary frontier models can be useful baselines; they do not have to remain the permanent destination.
When the technical and economic case supports it, we evaluate whether a specialized open-weight model can replace permanent dependence on a proprietary API.
Before reaching for a larger model, we test how far the right smaller model can go once it is specialized for the real task.
Generic leaderboards do not define success. Your actual workload, acceptance criteria, failure cases, and economics do.
The Huyawo Efficiency Standard
Every recommendation is judged across the dimensions that determine whether a model is actually production-efficient.
Does the model solve the real task better?
What is the smallest model that clears the bar?
How much VRAM or RAM does it require?
What are the response-time characteristics?
How much production workload can it sustain?
What does the workload actually cost to run?
How much control does your team retain?
Quality / cost frontier
We optimize for the lowest-cost configuration that preserves the quality that matters.
| Configuration | Task Quality | VRAM | Throughput | Relative Cost |
|---|---|---|---|---|
| BF16 | 94.1 | 48 GB | 1.00× | 1.00 |
| FP8 | 94.0 | 27 GB | 1.42× | 0.67 |
| INT8 | 93.9 | 25 GB | 1.51× | 0.61 |
| INT4 | 93.2 | 15 GB | 2.11× | 0.38 |
How we work
Step 01
Step 02
Step 03
Every engagement ends in evidence
A standardized technical handoff that records what was tested, what changed, where the model still fails, and which production configuration the evidence supports.
Huyawo Eval
Huyawo Eval is open-source model evaluation tooling currently in development.
Our engagements are built around reproducible evaluation against the workload that actually matters. Huyawo Eval is the evaluation infrastructure being developed around that philosophy, a credibility engine and methodology amplifier, not a fifth consulting offer.
Commercial terms
Fixed fee. Fixed scope. Explicit success criteria. GPU/cloud compute is scoped separately or included up to a clearly defined ceiling.
Retainers are for continuous model improvement, including evaluation, retraining, re-quantization, new checkpoints, runtimes, hardware, and deployment configurations, not general support or staff augmentation.
Project inquiry
Share the current model, use case, production context, and primary constraint. We will review the details and follow up with the most relevant next step.
contact@antoniovfranco.com