EcoTrain API RaaS Pricing

Pay for measured compute savings

EcoTrain API uses a RaaS billing model. Service fees are calculated from verified compute-cost savings: service fee = compute cost saved × revenue-share ratio.

  • Charged by verified savings
  • Settled after training completion
  • Detailed usage records
  • Monthly reconciliation supported

Billing formula

Prices are valid until 11:59 PM on September 30, 2026.

Compute cost saved = GPU-hours saved × GPU-hour unit priceService fee = compute cost saved × revenue-share ratio
Transparent billingPay for savingsNo extra fee without savings

Edition comparison

Compare EcoTrain services and benefits

EcoTrain Basic refreshes 400 GPU-hours and 30 tasks each calendar month. EcoTrain Pro student benefits grant the same quota once after verification, valid for 30 days without monthly refresh. All three options support acceleration and API keys.

FeatureBasicEcoTrainFreeStudent benefitsEcoTrain ProStudent planProfessionalEcoTrain ProRecommended
Core capabilities
ProductEcoTrainEcoTrain ProEcoTrain Pro
Best forIndividualsVerified studentsIndividuals, teams, and enterprises
Training accelerationIncludedIncludedIncluded
API KeyIncludedIncludedIncluded
Early stoppingNot includedIncludedIncluded
GPU-hour savingsNot includedIncludedIncluded
Quota and billing
Free quota / billing400 GPU-hours · 30 tasks each calendar monthOne-time grant of 400 GPU-hours and 30 tasks after verificationNo free quota; pay for measured savings
Refresh and validityRefreshes every calendar monthValid for 30 days; does not refresh monthlyAvailable while account balance remains
Concurrent tasksUp to 2 concurrent free-quota tasksUp to 2 concurrent student-benefit tasksScheduled by available capacity, without free-quota concurrency limits
Commercial and production useNo additional commitmentNon-commercial study and research onlyIncluded
Account and management
Enterprise workspace and rolesNot includedNot includedIncluded
Usage and task detailsBasic detailsStudent benefit detailsComplete billing and usage details
ProfessionalEcoTrain Pro
Recommended

Core capabilities

Product
EcoTrain Pro
Best for
Individuals, teams, and enterprises
Training acceleration
Included
API Key
Included
Early stopping
Included
GPU-hour savings
Included

Quota and billing

Free quota / billing
No free quota; pay for measured savings
Refresh and validity
Available while account balance remains
Concurrent tasks
Scheduled by available capacity, without free-quota concurrency limits
Commercial and production use
Included

Account and management

Enterprise workspace and roles
Included
Usage and task details
Complete billing and usage details

Billing formula

Billing formula

EcoTrain API uses a RaaS billing model. Service fees are calculated from verified compute-cost savings: service fee = compute cost saved × revenue-share ratio.

Settled after training
01

Compute savings

GPU-hours saved × unit price

Calculates the verified compute cost saved by a training task.

02

Service fee

Compute cost saved × revenue-share ratio

The share ratio follows the task's measured saving tier.

03

Balance deduction

Deducted from recharge or bonus balance

Final fees are settled after the training task completes.

EcoPhase share

Savings-based revenue share

The revenue-share ratio is determined by each training task's verified compute-cost savings.

Low impact

0% to 20%

EcoPhase share

20%

High impact

40% to 99%

EcoPhase share

30%

Example calculation

Billing example

If a training task was expected to cost CNY 10,000 and finishes at CNY 7,000 after EcoTrain acceleration, the task saves 30% in compute costs. EcoPhase charges 25% of the saved compute cost: (10,000 - 7,000) × 25% = CNY 750.

10000 - 7000 = 3000
3000 × 25% = 750
Original training cost
CNY 10,000
Accelerated cost
CNY 7,000
Saved cost
CNY 3,000
Saving ratio
30%
Revenue-share ratio
25%
Service fee
CNY 750

The customer keeps the remaining compute savings after the service fee, so the model stays tied to verified cost reduction.

Price categories

GPU-hour unit prices

Prices are in CNY per GPU-hour and are used to calculate saved compute cost.

CategoryCompute typeUnit price (CNY/GPU-hour)
Domestic acceleratorsAscend 910B22.08
Domestic acceleratorsZhenwu 810E3.75
Domestic acceleratorsMoore Threads MTT S40001.40
NVIDIA consumerNVIDIA GTX 1080 Ti0.48
NVIDIA consumerNVIDIA RTX 2080Ti0.70
NVIDIA consumerNVIDIA RTX 30800.70
NVIDIA consumerNVIDIA RTX 3080 Ti0.81
NVIDIA consumerNVIDIA RTX 30900.85
NVIDIA consumerNVIDIA 4090D1.25
NVIDIA consumerNVIDIA 40901.25
NVIDIA consumerNVIDIA 5090D2.08
NVIDIA consumerNVIDIA 50902.08
NVIDIA data centerNVIDIA V1000.90
NVIDIA data centerNVIDIA A8003.80
NVIDIA data centerNVIDIA A100-40G2.11
NVIDIA data centerNVIDIA A1004.80
NVIDIA data centerNVIDIA H205.50
NVIDIA data centerNVIDIA H8008.12
NVIDIA data centerNVIDIA H1009.20
NVIDIA data centerNVIDIA H20010.60
NVIDIA data centerNVIDIA B20015.32
NVIDIA data centerNVIDIA GB20071.50
NVIDIA data centerNVIDIA B30017.84
NVIDIA data centerNVIDIA A301.05
NVIDIA data centerNVIDIA A402.05
NVIDIA data centerNVIDIA L202.73
NVIDIA data centerNVIDIA L402.73
NVIDIA professionalNVIDIA RTX PRO 60005.27
NVIDIA professionalNVIDIA RTX A40000.72
NVIDIA professionalNVIDIA RTX A50001.53
NVIDIA professionalNVIDIA RTX A60002.25

Settlement

Settlement and payment

EcoTrain uses prepaid balance. Recharge funds are used for acceleration service consumption.

Payment and settlement

Prepaid balance is used for acceleration services. Service fee = compute cost saved × revenue-share ratio, deducted from the recharge or bonus balance.

Savings-based deduction

Service fee = compute cost saved × revenue-share ratio. Fees are deducted from the recharge or bonus balance.

Bonuses and reminders

A single recharge above CNY 5,000 receives CNY 800 acceleration coupon credit. A single recharge from CNY 2,000 to CNY 5,000 receives CNY 200 acceleration coupon credit. A reminder is shown when the balance falls below CNY 500.

Additional notes

Rules for recharge, refunds, reconciliation, and invoices.

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EcoTrain API Pricing and Billing - EcoPhase.AI