Adaptive-K Benchmark Dashboard

Models Validated

36.5%

Avg Compute Savings

52.5%

Max Compute Savings

-0.5%

Max Accuracy Drop

📊 Benchmark Results

Model	Total Params	Experts	K (base → adaptive)	Compute Savings	Status
Mixtral 8x7B	46.7B	8	8 → 3.80	52.5%	✓ Validated
Qwen1.5-MoE	14.3B	60	4 → 2.70	32.4%	✓ Validated
OLMoE 1B-7B	6.9B	64	8 → 6.0 (per-layer)	24.7%	✓ Validated
DeepSeek-V3	671B	256	8 → TBD	Pending	○ Pending
DBRX	132B	16	4 → TBD	~30% est.	~ Estimated

📈 Compute Savings by Model

🎯 K Distribution (Mixtral)

📰 Industry Research

$7M
Avg Enterprise LLM Spend
Source: a16z 2024

2-5x
Budget Growth 2025
Expected YoY increase

96 GW
Datacenter Power 2026
Source: SemiAnalysis

$648/mo
H100 8-GPU Power Cost
@ $0.083/kWh

🧮 ROI Calculator

Daily Token Volume MoE Model Estimated Savings Rate: 35%

Monthly Projection
                        Baseline Cost
                        $1,950
                    
                        With Adaptive-K
                        $1,268
                    
                        Monthly Savings
                        $683
                    
                        Annual Savings
                        $8,190

💡 Come Funziona (in parole semplici)

I modelli AI moderni come DeepSeek-V3 e Mixtral usano una tecnologia chiamata Mixture of Experts (MoE): invece di usare tutto il "cervello" del modello per ogni domanda, attivano solo alcuni "esperti" specializzati.

Il problema? Attivano sempre lo stesso numero di esperti, anche per domande semplici come "Che ore sono?" che non richiedono tutta quella potenza di calcolo.

Adaptive-K risolve questo: analizza la "confidenza" del modello e decide automaticamente quanti esperti attivare. Domanda facile → pochi esperti. Domanda complessa → più esperti.

❌ PRIMA (Standard)

Sempre 8 esperti attivi = costo fisso alto

✅ DOPO (Adaptive-K)

2-8 esperti in base alla difficoltà = risparmio 30-50%

🤖 MoE Models for Profiling

Provider	Model	Params	Experts	Top-K	Price
Together	DeepSeek-V3.1	671B	256	8	$0.60/1M
Together	Qwen3-235B-MoE	235B	128	22	$0.65/1M
Together	Qwen3-Coder-480B	480B	160	35	$2.00/1M
Together	Cogito-109B-MoE	109B	64	8	$0.18/1M
OpenRouter	Mixtral-8x7B	46.7B	8	2	$0.24/1M
DeepSeek	deepseek-chat	671B	256	8	$0.14/1M

🏢 Enterprise Use Cases

Customer Support AI

High volume, many simple queries

Savings: 40-50%

Document Processing

Variable complexity extraction

Savings: 30-40%

Code Generation

High complexity tasks

Savings: 20-30%

Synthetic Data Gen

Massive scale, cost-sensitive

Savings: 45-55%

Ready to reduce your MoE compute costs?

Integrate Adaptive-K routing in minutes with our SDK

Learn More pip install adaptive-k-routing Read Whitepaper

Adaptive-K Routing Benchmarks