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Model Registry

LLMKit includes a built-in registry of 11,000+ models with pricing, capabilities, and specifications. No API calls needed — all data is compiled into the binary for instant lookups.

Quick Start

Rust

use llmkit::{get_model_info, get_models_by_provider, get_models_with_capability};

// Get model details
let info = get_model_info("anthropic/claude-sonnet-4-20250514")?;
println!("Context window: {} tokens", info.context_window);
println!("Input price: ${}/1M tokens", info.input_price);
println!("Output price: ${}/1M tokens", info.output_price);

// Find models by provider
let anthropic_models = get_models_by_provider("anthropic");

// Find models with specific capabilities
let vision_models = get_models_with_capability(ModelCapability::Vision);
let thinking_models = get_models_with_capability(ModelCapability::Thinking);

Python

from llmkit import get_model_info, get_models_by_provider, get_models_with_capability

# Get model details
info = get_model_info("anthropic/claude-sonnet-4-20250514")
print(f"Context window: {info.context_window:,} tokens")
print(f"Input price: ${info.input_price}/1M tokens")
print(f"Output price: ${info.output_price}/1M tokens")

# Find models by provider
anthropic_models = get_models_by_provider("anthropic")

# Find models with specific capabilities
vision_models = get_models_with_capability(vision=True)
thinking_models = get_models_with_capability(thinking=True)

Node.js

import { getModelInfo, getModelsByProvider, getModelsWithCapability } from 'llmkit-node'

// Get model details
const info = getModelInfo('anthropic/claude-sonnet-4-20250514')
console.log(`Context window: ${info.contextWindow.toLocaleString()} tokens`)
console.log(`Input price: $${info.inputPrice}/1M tokens`)
console.log(`Output price: $${info.outputPrice}/1M tokens`)

// Find models by provider
const anthropicModels = getModelsByProvider('anthropic')

// Find models with specific capabilities
const visionModels = getModelsWithCapability({ vision: true })
const thinkingModels = getModelsWithCapability({ thinking: true })

Model Information

Each model entry includes:

Field Description
id Unique identifier (provider/model-name)
name Human-readable name
provider Provider identifier
context_window Maximum context length in tokens
max_output_tokens Maximum output length
input_price Price per 1M input tokens (USD)
output_price Price per 1M output tokens (USD)
supports_vision Image/vision input support
supports_tools Function/tool calling support
supports_streaming Streaming response support
supports_json_mode JSON output mode
supports_thinking Extended thinking/reasoning
supports_caching Prompt caching support

Popular Models

Anthropic Claude

Model Context Input Price Output Price Features
anthropic/claude-sonnet-4-20250514 200K $3.00 $15.00 Vision, Tools, Caching, Thinking
anthropic/claude-opus-4-20250514 200K $15.00 $75.00 Vision, Tools, Caching, Thinking
anthropic/claude-3-5-haiku-20241022 200K $0.80 $4.00 Vision, Tools, Caching

OpenAI GPT

Model Context Input Price Output Price Features
openai/gpt-4o 128K $2.50 $10.00 Vision, Tools, JSON
openai/gpt-4o-mini 128K $0.15 $0.60 Vision, Tools, JSON
openai/o1 200K $15.00 $60.00 Thinking
openai/o1-mini 128K $3.00 $12.00 Thinking

Google Gemini

Model Context Input Price Output Price Features
google/gemini-2.0-flash 1M $0.075 $0.30 Vision, Tools, Caching
google/gemini-1.5-pro 2M $1.25 $5.00 Vision, Tools, Caching
google/gemini-1.5-flash 1M $0.075 $0.30 Vision, Tools, Caching

DeepSeek

Model Context Input Price Output Price Features
deepseek/deepseek-chat 64K $0.14 $0.28 Tools, Caching
deepseek/deepseek-reasoner 64K $0.55 $2.19 Thinking, Caching

Mistral

Model Context Input Price Output Price Features
mistral/mistral-large 128K $2.00 $6.00 Vision, Tools
mistral/mistral-small 32K $0.20 $0.60 Tools
mistral/codestral 32K $0.20 $0.60 Code

Open Source (via Groq, Together, etc.)

Model Context Provider Features
groq/llama-3.3-70b-versatile 128K Groq Ultra-fast, Tools
together/meta-llama/Meta-Llama-3.1-405B 128K Together Tools, Vision
fireworks/llama-v3p1-70b-instruct 128K Fireworks Tools

Capability Queries

Find Vision Models

vision_models = get_models_with_capability(vision=True)
for model in vision_models[:10]:
    print(f"{model.id}: {model.context_window:,} tokens")

Find Thinking/Reasoning Models

thinking_models = get_models_with_capability(thinking=True)
# Returns: claude-sonnet-4, claude-opus-4, o1, o1-mini, deepseek-reasoner, gemini-2.0-flash-thinking

Find Models with Caching

cache_models = get_models_with_capability(caching=True)
# Returns models supporting prompt caching for cost savings

Find Budget-Friendly Models

all_models = get_all_models()
budget_models = [m for m in all_models if m.input_price < 1.0]
budget_models.sort(key=lambda m: m.input_price)

Cost Estimation

from llmkit import get_model_info

def estimate_cost(model_id: str, input_tokens: int, output_tokens: int) -> float:
    info = get_model_info(model_id)
    input_cost = (input_tokens / 1_000_000) * info.input_price
    output_cost = (output_tokens / 1_000_000) * info.output_price
    return input_cost + output_cost

# Example: 10K input, 2K output with Claude Sonnet
cost = estimate_cost("anthropic/claude-sonnet-4-20250514", 10000, 2000)
print(f"Estimated cost: ${cost:.4f}")  # $0.06

Model ID Format

All models use the provider/model-name format:

anthropic/claude-sonnet-4-20250514
openai/gpt-4o
google/gemini-2.0-flash
groq/llama-3.3-70b-versatile
deepseek/deepseek-chat
mistral/mistral-large
bedrock/anthropic.claude-3-sonnet
azure/gpt-4o
vertex/gemini-pro

Updating the Registry

The model registry is updated with each LLMKit release. To get the latest models and pricing, update to the newest version:

# Rust
cargo update llmkit

# Python
pip install --upgrade llmkit-python

# Node.js
npm update llmkit-node