Add Model Price

Purpose

Guide for adding new LLM model pricing entries to Langfuse's default model prices configuration. This enables accurate cost tracking across different model providers and deployment platforms.

When to Use This Skill

Automatically activates when:

Adding a new model to the pricing database
Updating model pricing information
Working with
```
default-model-prices.json
```
Creating model matchPattern regex
Configuring pricingTiers or tiered pricing
Adding prices for Claude, OpenAI, Anthropic, Google, Gemini, AWS Bedrock, Azure, or Vertex AI models

Quick Start Checklist

Gather model info: Fetch official pricing from provider documentation URL
Generate UUID: Run
```
uuidgen
```
for the model entry ID (use lowercase)
Create matchPattern: Regex covering all provider formats
Define pricingTiers: At minimum, one default tier with standard prices

Add pricing entry: Insert into

/worker/src/constants/default-model-prices.json

Add to LLM types: Add model to
```
/packages/shared/src/server/llm/types.ts
```
(for playground/LLM-as-judge)
Validate JSON: Run
```
jq . default-model-prices.json
```
to verify syntax

File Location

Target File:

/worker/src/constants/default-model-prices.json

This JSON file contains an array of model pricing definitions used for cost calculation.

Data Structure

Complete Model Entry Schema

json

{
  "id": "uuid-generated-with-uuidgen",
  "modelName": "model-name-identifier",
  "matchPattern": "(?i)^regex-pattern$",
  "createdAt": "ISO-8601-timestamp",
  "updatedAt": "ISO-8601-timestamp",
  "tokenizerConfig": null,
  "tokenizerId": "claude|openai|null",
  "pricingTiers": [
    {
      "id": "model-uuid_tier_default",
      "name": "Standard",
      "isDefault": true,
      "priority": 0,
      "conditions": [],
      "prices": {
        "input": 0.000005,
        "output": 0.000025
      }
    }
  ]
}

Required Fields

Field	Type	Description
`id`	string	Unique UUID (use `uuidgen` command, lowercase)
`modelName`	string	Primary model identifier
`matchPattern`	string	Regex for matching model names
`createdAt`	string	ISO-8601 timestamp
`updatedAt`	string	ISO-8601 timestamp
`pricingTiers`	array	At least one pricing tier

Optional Fields

Field	Type	Default	Description
`tokenizerId`	string	null	"claude", "openai", or null
`tokenizerConfig`	object	null	Custom tokenizer settings

Pricing Tier Structure

Default Tier (Required)

Every model must have exactly one default tier:

json

{
  "id": "{model-id}_tier_default",
  "name": "Standard",
  "isDefault": true,
  "priority": 0,
  "conditions": [],
  "prices": { }
}

Rules for Default Tier:

```
isDefault
```
: Must be
```
true
```
```
priority
```
: Must be
```
0
```
```
conditions
```
: Must be empty array
```
[]
```

Additional Tiers (Optional)

For usage-based pricing (e.g., large context pricing):

json

{
  "id": "uuid-for-tier",
  "name": "Large Context (>200K)",
  "isDefault": false,
  "priority": 1,
  "conditions": [
    {
      "usageDetailPattern": "(input|prompt|cached)",
      "operator": "gt",
      "value": 200000,
      "caseSensitive": false
    }
  ],
  "prices": { }
}

Condition Operators:

gt

gte

lt

lte

eq

neq

Gathering Pricing Information

IMPORTANT: Always fetch pricing from official provider documentation. Never use heuristics or assumptions.

Official Pricing Sources

Provider	URL
Anthropic Claude	https://platform.claude.com/docs/en/about-claude/pricing
OpenAI	https://openai.com/api/pricing/
Google Gemini	https://ai.google.dev/pricing
AWS Bedrock	https://aws.amazon.com/bedrock/pricing/
Azure OpenAI	https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/

Required Information to Gather

Base input token price (per MTok)
Output token price (per MTok)
Cache write price (if caching supported)
Cache read price (if caching supported)
Long context pricing (if different tiers exist)
Model ID formats for all platforms (API, Bedrock, Vertex)

Price Conversion

Prices in the JSON are per token, not per million tokens.

Provider Pricing	JSON Value	Calculation
$5 / MTok	`5e-6`	$5 / 1,000,000
$25 / MTok	`25e-6`	$25 / 1,000,000
$0.50 / MTok	`0.5e-6`	$0.50 / 1,000,000
$6.25 / MTok	`6.25e-6`	$6.25 / 1,000,000

Formula:

price_per_token = price_per_mtok / 1_000_000

price_per_mtok * 1e-6

Common Price Keys by Provider

Anthropic Claude Models

json

{
  "input": <base_input_price>,
  "input_tokens": <base_input_price>,
  "output": <output_price>,
  "output_tokens": <output_price>,
  "cache_creation_input_tokens": <cache_write_price>,
  "input_cache_creation": <cache_write_price>,
  "cache_read_input_tokens": <cache_read_price>,
  "input_cache_read": <cache_read_price>
}

OpenAI Models

json

{
  "input": <input_price>,
  "input_cached_tokens": <cached_input_price>,
  "input_cache_read": <cached_input_price>,
  "output": <output_price>
}

Google Gemini Models

json

{
  "input": <input_price>,
  "input_modality_1": <input_price>,
  "prompt_token_count": <input_price>,
  "promptTokenCount": <input_price>,
  "input_cached_tokens": <cached_price>,
  "cached_content_token_count": <cached_price>,
  "output": <output_price>,
  "output_modality_1": <output_price>,
  "candidates_token_count": <output_price>,
  "candidatesTokenCount": <output_price>
}

Match Pattern Examples

Anthropic Claude (API + Bedrock + Vertex)

regex

(?i)^(anthropic\/)?(claude-opus-4-6|(eu\\.|us\\.|apac\\.)?anthropic\\.claude-opus-4-6-v1(:0)?|claude-opus-4-6)$

Matches:

```
claude-opus-4-6
```
(direct API)
```
anthropic/claude-opus-4-6
```
(with prefix)
```
anthropic.claude-opus-4-6-v1:0
```
(AWS Bedrock)
```
us.anthropic.claude-opus-4-6-v1:0
```
(regional Bedrock)
```
claude-opus-4-6
```
(GCP Vertex)

With Version Date

regex

(?i)^(anthropic\/)?(claude-opus-4-5-20251101|(eu\\.|us\\.|apac\\.)?anthropic\\.claude-opus-4-5-20251101-v1:0|claude-opus-4-5@20251101)$

OpenAI

regex

(?i)^(openai\/)?(gpt-4o)$

Google Gemini

regex

(?i)^(google\/)?(gemini-2.5-pro)$

Pattern Components

Component	Purpose	Example
`(?i)`	Case insensitive	Matches GPT-4o and gpt-4o
`^...$`	Full string match	Prevents partial matches
`(provider\/)?`	Optional provider prefix	`openai/gpt-4o`
`(eu\.\	us\.\	apac\.)?`
`(:0)?`	Optional version suffix	Bedrock model versions
`@date`	Vertex AI format	`claude-3-5-sonnet@20240620`

Step-by-Step: Adding a New Model

Step 1: Fetch Official Pricing

Use WebFetch to get pricing from official documentation:

WebFetch URL: https://platform.claude.com/docs/en/about-claude/pricing
Prompt: Extract pricing for [model name] including input, output, cache write, cache read prices per MTok

Step 2: Generate UUID

bash

uuidgen
# Output: 13458BC0-1C20-44C2-8753-172F54B67647
# Convert to lowercase: 13458bc0-1c20-44c2-8753-172f54b67647

Step 3: Create the Entry

Example for a model with $5 input, $25 output, $6.25 cache write, $0.50 cache read:

json

{
  "id": "13458bc0-1c20-44c2-8753-172f54b67647",
  "modelName": "claude-opus-4-6",
  "matchPattern": "(?i)^(anthropic\/)?(claude-opus-4-6|(eu\\.|us\\.|apac\\.)?anthropic\\.claude-opus-4-6-v1(:0)?|claude-opus-4-6)$",
  "createdAt": "2026-02-09T00:00:00.000Z",
  "updatedAt": "2026-02-09T00:00:00.000Z",
  "tokenizerConfig": null,
  "tokenizerId": "claude",
  "pricingTiers": [
    {
      "id": "13458bc0-1c20-44c2-8753-172f54b67647_tier_default",
      "name": "Standard",
      "isDefault": true,
      "priority": 0,
      "conditions": [],
      "prices": {
        "input": 5e-6,
        "input_tokens": 5e-6,
        "output": 25e-6,
        "output_tokens": 25e-6,
        "cache_creation_input_tokens": 6.25e-6,
        "input_cache_creation": 6.25e-6,
        "cache_read_input_tokens": 0.5e-6,
        "input_cache_read": 0.5e-6
      }
    }
  ]
}

Step 4: Insert Entry

Add the entry to the JSON array in

/worker/src/constants/default-model-prices.json

Placement: Insert near related models (e.g., other Claude models together).

Step 5: Add to LLM Types (for Playground & LLM-as-Judge)

To make the model available in the Langfuse playground and for LLM-as-a-judge evaluations, add it to the appropriate model array in

/packages/shared/src/server/llm/types.ts

File:

/packages/shared/src/server/llm/types.ts

Model Arrays by Provider:

```
anthropicModels
```
- Anthropic Claude models
```
openAIModels
```
- OpenAI GPT models
```
vertexAIModels
```
- Google Vertex AI models
```
googleAIStudioModels
```
- Google AI Studio models

IMPORTANT: Do NOT add new models as the first entry in the array. The first entry is used as the default model for test LLM API calls, and newer models may not be available to all users yet.

Example for Anthropic:

typescript

export const anthropicModels = [
  "claude-sonnet-4-5-20250929",  // Keep existing first entry
  "claude-haiku-4-5-20251001",
  "claude-opus-4-6",              // Add new model here (not first!)
  "claude-opus-4-5-20251101",
  // ... rest of models
] as const;

Step 6: Validate

bash

# Check JSON syntax
jq . /path/to/default-model-prices.json > /dev/null && echo "Valid JSON"

# Verify entry exists
jq '.[] | select(.modelName == "claude-opus-4-6")' /path/to/default-model-prices.json

Multi-Tier Pricing Example

For models with long context pricing (e.g., different rates above 200K tokens):

json

{
  "id": "uuid-here",
  "modelName": "model-name",
  "matchPattern": "...",
  "pricingTiers": [
    {
      "id": "uuid-here_tier_default",
      "name": "Standard",
      "isDefault": true,
      "priority": 0,
      "conditions": [],
      "prices": {
        "input": 5e-6,
        "output": 25e-6
      }
    },
    {
      "id": "uuid-for-large-context-tier",
      "name": "Large Context (>200K)",
      "isDefault": false,
      "priority": 1,
      "conditions": [
        {
          "usageDetailPattern": "(input|prompt|cached)",
          "operator": "gt",
          "value": 200000,
          "caseSensitive": false
        }
      ],
      "prices": {
        "input": 10e-6,
        "output": 37.5e-6
      }
    }
  ]
}

Validation Rules

The system validates pricing tiers with these rules:

Exactly one default tier with
```
isDefault: true
```
Default tier must have
```
priority: 0
```
and empty
```
conditions: []
```
Non-default tiers must have
```
priority > 0
```
and at least one condition
All priorities must be unique within a model
All tier names must be unique within a model
Each tier must have at least one price
All tiers must have identical usage type keys
Regex patterns must be valid and safe (no catastrophic backtracking)

Common Mistakes

Using heuristics instead of official pricing:

json

// Wrong - assuming cache is 1.25x input
"cache_creation_input_tokens": input_price * 1.25

// Correct - use exact value from official docs
"cache_creation_input_tokens": 6.25e-6

Incorrect Price Format:

json

// Wrong - using MTok price directly
"input": 5

// Correct - price per token
"input": 5e-6

Missing Tier ID Suffix:

json

// Wrong
"id": "some-uuid"

// Correct for default tier
"id": "model-uuid_tier_default"

Invalid Regex Escaping:

json

// Wrong - unescaped dots
"matchPattern": "anthropic.claude"

// Correct - escaped dots
"matchPattern": "anthropic\\.claude"

Testing Model Matching

After adding a model, test that the regex matches expected inputs:

javascript

const pattern = new RegExp(matchPattern);
console.log(pattern.test("claude-opus-4-6")); // true
console.log(pattern.test("anthropic/claude-opus-4-6")); // true
console.log(pattern.test("anthropic.claude-opus-4-6-v1:0")); // true
console.log(pattern.test("us.anthropic.claude-opus-4-6-v1:0")); // true

Reference: Existing Model Entries

Look at these existing entries as templates:

Model Type	Example Entry	Notes
Anthropic Claude	`claude-opus-4-5-20251101`	Full multi-provider pattern
OpenAI GPT	`gpt-4o`	Simple pattern
Google Gemini	`gemini-2.5-pro`	Multi-tier with large context

Related Files

Pricing JSON:

/worker/src/constants/default-model-prices.json

LLM Types:
```
/packages/shared/src/server/llm/types.ts
```
(model arrays for playground/LLM-as-judge)

Validation:

/packages/shared/src/server/pricing-tiers/validation.ts

Matcher:

/packages/shared/src/server/pricing-tiers/matcher.ts

Tests:

/web/src/__tests__/async/model-pricing-tiers.servertest.ts

Skill Status: COMPLETE Line Count: ~340 lines

add-model-price

NPX Install

Tags

SKILL.md Content

Add Model Price

Purpose

When to Use This Skill

Quick Start Checklist

File Location

Data Structure

Complete Model Entry Schema

Required Fields

Optional Fields

Pricing Tier Structure

Default Tier (Required)

Additional Tiers (Optional)

Gathering Pricing Information

Official Pricing Sources

Required Information to Gather

Price Conversion

Common Price Keys by Provider

Anthropic Claude Models

OpenAI Models

Google Gemini Models

Match Pattern Examples

Anthropic Claude (API + Bedrock + Vertex)

With Version Date

OpenAI

Google Gemini

Pattern Components

Step-by-Step: Adding a New Model

Step 1: Fetch Official Pricing

Step 2: Generate UUID

Step 3: Create the Entry

Step 4: Insert Entry

Step 5: Add to LLM Types (for Playground & LLM-as-Judge)

Step 6: Validate

Multi-Tier Pricing Example

Validation Rules

Common Mistakes

Testing Model Matching

Reference: Existing Model Entries

Related Files