TokenMeter

LLM model metadata catalog and cost calculator for .NET.

Provides context windows, pricing, capability flags (vision, audio, reasoning, tool calling, prompt caching), and thinking/reasoning format metadata for 12+ providers including OpenAI, Anthropic, Google, xAI, Mistral, DeepSeek, and more.

Packages

Package	Description
TokenMeter	Full model catalog + cost calculation

Installation

dotnet add package TokenMeter

Quick Start

Model Lookup

// Find a model by ID or alias
var model = ModelCatalog.FindModel("claude-sonnet-4-6");

Console.WriteLine(model?.ContextWindow);          // 1000000
Console.WriteLine(model?.ReasoningMode);           // Optional
Console.WriteLine(model?.ThinkingFormat);          // Block
Console.WriteLine(model?.PromptCachingMode);       // Explicit
Console.WriteLine(model?.ToolCallingFormat);       // Anthropic
Console.WriteLine(model?.SupportsMcpToolUse);      // True

Note — fuzzy matching: FindModel resolves aliases in 4 passes (exact → alias exact → prefix → contains) to absorb cloud-specific ID variants (Bedrock/Vertex prefixes, date suffixes). Local/self-hosted deployment names that embed a public model name (e.g. deepseek-r1-distill-qwen-7b) can therefore match a catalog entry whose context window and pricing do not describe your deployment. For self-hosted models, take the effective context length from your deployment configuration (e.g. llama.cpp n_ctx), not from the catalog.

// When correctness matters more than recall, bound the fuzziness:
ModelCatalog.FindModel("deepseek-r1-distill-qwen-7b", AliasMatchType.Exact);   // null — no false positive
ModelCatalog.FindModel("us.anthropic.claude-sonnet-4.6-v1");                   // matched via contains alias

// Or inspect which pass produced the match and apply confidence-based fallback:
var match = ModelCatalog.FindModelMatch("deepseek-r1-distill-qwen-7b");
Console.WriteLine(match?.MatchKind);   // Prefix — a fuzzy inference, not an exact hit
Console.WriteLine(match?.Model.ModelId);

Cost Calculation

// Basic cost (input + output tokens)
var cost = model?.CalculateCost(inputTokens: 500_000, outputTokens: 200_000);

// Cost including prompt cache tokens
var costWithCache = model?.CalculateCost(
    inputTokens: 100_000,
    outputTokens: 50_000,
    cacheReadTokens: 400_000,
    cacheWriteTokens: 50_000);

// Via CostCalculator (DI-friendly)
ICostCalculator calc = CostCalculator.Default();
var price = calc.CalculateCost("gpt-4o", inputTokens: 1_000, outputTokens: 500);

Browsing the Catalog

// By provider — typed convenience property
foreach (var m in ModelCatalog.Anthropic.Values)
    Console.WriteLine($"{m.ModelId}: ctx={m.ContextWindow}, ${m.InputPricePerMillion}/M");

// By provider — string-keyed (when the name is only known at runtime)
var openai = ModelCatalog.GetProvider("OpenAI");   // dict, empty if unknown

// By model type (the built-in catalog currently contains Chat models only)
var chatModels = ModelCatalog.GetByType(ModelType.Chat);

// All providers
var providers = ModelCatalog.GetProviderNames();

Custom Models

var calc = CostCalculator.Default();
calc.RegisterModel(new ModelInfo
{
    ModelId = "my-fine-tuned-model",
    Provider = "MyCompany",
    InputPricePerMillion = 2.00m,
    OutputPricePerMillion = 8.00m,
    ContextWindow = 128_000,
    SupportsToolCalling = true,
    ToolCallingFormat = ToolCallingFormat.OpenAI
});

var cost = calc.CalculateCost("my-fine-tuned-model", 10_000, 5_000);

Model Metadata

ModelInfo provides the following metadata:

Identity

Property	Type	Description
ModelId	string	Canonical model identifier for API calls
Provider	string?	Provider name (e.g., "OpenAI", "Anthropic")
DisplayName	string?	Human-readable name
ModelType	ModelType	Chat, Embedding, Reranker, ImageGeneration, TextToSpeech, SpeechToText
IsInstructTuned	bool	Instruction-tuned vs. base model

Limits

Property	Type	Description
ContextWindow	int?	Maximum input tokens
MaxOutputTokens	int?	Maximum generated tokens per response

Pricing (USD / 1M tokens)

Property	Description
InputPricePerMillion	Standard input token price
OutputPricePerMillion	Standard output token price
CacheReadPricePerMillion	Prompt cache hit price (often 90% discount)
CacheWritePricePerMillion	Prompt cache population price
ImageInputPrice	Per-image input cost
AudioInputPricePerSecond	Audio input cost per second

Note — one rate per model: these fields hold a provider's standard rate for a model. Where a provider charges more above a prompt-length threshold (several now publish a second, higher tier for long-context requests), the catalog carries the base tier only, so cost for a request past that threshold is understated. Cache-write cost falls back to the input rate when a provider does not price it separately, which matches how automatic prompt caching is normally billed.

Input Modalities

Property	Description
SupportsImageInput	Accepts image data
SupportsAudioInput	Accepts audio data
SupportsVideoInput	Accepts video data
SupportsDocumentInput	Accepts PDF/document files natively

API Capabilities

Property	Description
SupportsToolCalling	Tool/function calling
SupportsParallelToolCalling	Multiple tools per turn
SupportsStructuredOutput	JSON Schema-enforced output
SupportsJsonMode	JSON-guided output (soft)
SupportsStreaming	SSE streaming
PromptCachingMode	None / Explicit / Automatic
SupportsMcpToolUse	Native MCP tool support

Reasoning & Thinking

Property	Description
ReasoningMode	None / Optional / Always
ThinkingFormat	None / Block / InlineTag / SeparateField
ThinkingTagPattern	Tag pattern (e.g., <think>...</think>) for InlineTag format
ThinkingFieldName	Field name (e.g., reasoning_content) for SeparateField format
SupportsInterleavedThinking	Reasoning between tool calls
MaxThinkingTokens	Maximum reasoning budget

Tool Calling Wire Format

Value	Description
ToolCallingFormat.OpenAI	tool_calls / tool role (default)
ToolCallingFormat.Anthropic	tool_use / tool_result content blocks
ToolCallingFormat.Gemini	Google Gemini format

Supported Providers

Provider	Models
OpenAI	GPT-5.x, GPT-4.1, GPT-4o, o1, o3, o4-mini series
Anthropic	Claude 5, 4.x, 3.x families (Fable, Mythos, Opus, Sonnet, Haiku)
Google	Gemini 3.x, 2.5, 2.0, 1.5 families
xAI	Grok 4.x, 3.x series
Azure	Azure OpenAI equivalents
Mistral	Large, Medium, Small, Magistral, Pixtral
DeepSeek	V4 (Flash, Pro), R1 (reasoning), V3, Coder
Amazon Nova	Premier, Pro, Lite, Micro
Cohere	Command A, R+, R, R7B
Meta Llama	Maverick, Scout
Perplexity	Sonar Pro, Deep Research, Reasoning
Qwen	Max, Plus, Turbo

Data Freshness

Console.WriteLine(ModelCatalog.LastUpdated);        // 2026-08-01
Console.WriteLine(ModelCatalog.DataAgeDays);        // days since last update
Console.WriteLine(ModelCatalog.IsDataStale());      // true if > 90 days old

LastUpdated is derived from the lastUpdated field each bundled provider file declares, and reports the most recent of them. Providers are refreshed independently, so an individual provider's data can be considerably older than this value.

Note — what the signal does and does not tell you: it reports when this catalog was last refreshed, not whether a provider has changed its prices since. A vendor can cut a rate the day after a refresh, and IsDataStale() will still answer false while the bundled figure is wrong. Treat catalog pricing as a good default for estimation and budgeting, and read authoritative figures from your provider's billing data when they have to be exact.

Migration from 0.3.x

The following APIs were removed in 0.4.0:

• TokenMeter.Abstractions package (removed entirely)
• ITokenCounter, TokenCounter — use your own tokenizer library
• IUsageTracker, UsageTracker, UsageRecord, UsageStatistics — implement in your application
• ModelPricing → replaced by ModelInfo
• ModelPricingData → replaced by ModelCatalog
• ICostCalculator.GetPricing() → GetModel()
• ICostCalculator.RegisterPricing() → RegisterModel()

Requirements

• .NET 10.0 or later

License

MIT