EMR AI Assistant uses Credits as the unified billing unit. Usage is calculated by converting actual Token consumption into Credits based on model-specific multipliers. The default model is qwen3.7-max. You can also select other supported models.
Key concepts
Credit is the unified billing unit for EMR AI Assistant.
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1 Credit = 1,000 Tokens, based on the input Tokens of the default model qwen3.7-max (input multiplier = 1).
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Different models and Token types (input / cached input / output) have different unit costs, each represented by a multiplier relative to the baseline.
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Formula: Credits consumed = (actual Tokens ÷ 1,000) × model multiplier
Multiplier table
Actual prices are subject to the product purchase page.
|
Model |
Token tier |
Input multiplier |
Output multiplier |
Cached input multiplier |
|
qwen3.7-max (default) |
0<Token≤1M |
1 |
3 |
0.2 |
|
qwen3.7-plus |
0<Token≤256K |
0.1667 |
0.6667 |
0.0333 |
|
256K<Token≤1M |
0.5 |
2 |
0.1 |
|
|
glm-5.2 |
0<Token≤1M |
0.6667 |
2.3333 |
0.1333 |
|
deepseek-v4-pro |
0<Token≤1M |
1 |
2 |
0.2 |
Credit unit price
1 Credit = USD 0.00198
Billing example
The following example illustrates how Credit-based billing is calculated for EMR AI Assistant.
|
Billing conditions |
Credit consumption |
|
Input Credits = (500,000 ÷ 1,000) × 1 = 500 Output Credits = (200,000 ÷ 1,000) × 3 = 600 Total = 1,100 Credits Cost = 1,100 × 0.00198 = USD 2.178 |