llm-zoo 🦁

LLM pricing and capabilities change weekly. Docs are scattered. There's no single source of truth.

One package. 70+ models. Always current.

import { lookup, cost, cheapest } from 'llm-zoo';

// Know everything about any model
const claude = lookup('sonnet45');
console.log(claude.contextWindow);  // 200000
console.log(claude.inputPrice);     // 3

// Calculate exact costs
const price = cost('gpt4o', { input: 50000, output: 10000 });

// Find the right model
const budget = cheapest({ supportsVision: true, supportsReasoning: true });

Zero dependencies. Full TypeScript. Tree-shakeable. Zod schemas included.

Install

npm install llm-zoo

Model Rankings

Cheapest ($/1M tokens)

| Model | Input | Output | Provider | |-------|-------|--------|----------| | qwenturbo | $0.05 | $0.50 | DashScope | | gpt41-- | $0.10 | $0.40 | OpenAI | | gemini25f- | $0.10 | $0.40 | Google | | dsv3 | $0.14 | $0.28 | DeepSeek | | gpt4o- | $0.15 | $0.60 | OpenAI | | haiku3 | $0.25 | $1.25 | Anthropic | | deepseek | $0.28 | $0.42 | DeepSeek | | gemini3f | $0.30 | $2.50 | Google |

Premium ($/1M tokens)

| Model | Input | Output | Reasoning | Provider | |-------|-------|--------|-----------|----------| | o1pro | $150 | $600 | ✓ | OpenAI | | gpt45 | $75 | $150 | - | OpenAI | | gpt52pro | $21 | $168 | ✓ | OpenAI | | o3pro | $20 | $80 | ✓ | OpenAI | | opus41T | $15 | $75 | ✓ | Anthropic | | opus41 | $15 | $75 | - | Anthropic | | opus45T | $5 | $25 | ✓ | Anthropic | | opus45 | $5 | $25 | - | Anthropic |

Largest Context

| Model | Context | Provider | |-------|---------|----------| | gemini3p | 1M | Google | | gemini25p | 1M | Google | | qwenplus | 1M | DashScope | | gpt41 | 1M | OpenAI | | gpt5 | 400K | OpenAI | | kimi2 | 262K | Moonshot | | grok4 | 256K | xAI | | sonnet45 | 200K | Anthropic |

Capabilities

| Capability | Count | Examples | |------------|-------|----------| | Vision | 45+ | sonnet45, gpt4o, gemini25p | | Reasoning | 30+ | opus45T, o3, deepseekT, grok4 | | Code Execution | 20+ | sonnet45, gpt41, gemini3p | | Web Search | 15+ | opus45, gpt4o, o3 | | Prompt Caching | 25+ | All Claude, Gemini, DeepSeek |

Providers

| Provider | Models | Highlights | |----------|--------|------------| | Anthropic | 21 | 90% cache savings, PDF support | | OpenAI | 28 | o-series reasoning, deep research | | Google | 6 | 1M context, audio input | | DeepSeek | 7 | Budget reasoning ($0.28/1M) | | xAI | 5 | Grok 4 with 256K context | | Moonshot | 8 | Kimi K2 thinking mode | | DashScope | 3 | Qwen with 1M context | | Copilot | 1 | Free GPT-4o | | OpenRouter | 2 | Llama 405B, QVQ-72B |

API

Lookup

lookup('sonnet45')              // → ModelConfig | undefined
resolve('claude-sonnet-4-5')    // → by full API name
exists('gpt4o')                 // → true

Filter

from(ModelProvider.ANTHROPIC)   // → all Claude models
where(c => c.supportsVision)    // → by capability predicate
supporting('supportsReasoning') // → models with reasoning
withContext(500000)             // → 500K+ context models

Cost

cost('sonnet45', { input: 10000, output: 5000 })
cost('sonnet45', { input: 10000, output: 5000, cached: 8000 })  // with caching
maxCost('gpt4o', 50000)                                         // worst case
compareCosts(['sonnet45', 'gpt4o'], { input: 10000, output: 2000 })

Select

cheapest({ supportsVision: true })
cheapest({ supportsReasoning: true }, { minContext: 100000 })
smartpick(5)                    // best model under $5/1M tokens
ranked('price')                 // cheapest first
ranked('context', 'desc')       // largest context first

Insights

const { totalModels, providers, pricing, context } = insights();

Zod Schemas (v4)

Validate model configs at runtime (requires zod@^4.0.0):

import { ModelConfigSchema } from 'llm-zoo/schemas';

// Validate custom model config
const result = ModelConfigSchema.safeParse(myConfig);
if (!result.success) {
  console.error(result.error);
}

// Validate API responses
const validatedModel = ModelConfigSchema.parse(apiResponse);

Available schemas:

• ModelConfigSchema — Full model configuration
• ModelCapabilitiesSchema — Capability flags
• ModelProviderSchema — Provider enum
• ReasoningEffortSchema — Reasoning levels

Data Structure

interface ModelConfig {
  name: string;              // 'sonnet45'
  fullName: string;          // 'claude-sonnet-4-5'
  provider: ModelProvider;
  inputPrice: number;        // $/1M tokens
  outputPrice: number;
  contextWindow: number;
  maxOutputTokens: number;
  capabilities: ModelCapabilities;
  openRouterOnly: boolean;
  openrouterFullName?: string;
}

interface ModelCapabilities {
  supportsFunctionCalling: boolean;
  supportsVision: boolean;
  supportsReasoning: boolean;
  supportsNativeCodeExecution: boolean;
  supportsNativeWebSearch: boolean;
  supportsPromptCaching: boolean;
  cacheDiscountFactor: number;   // 0.1 = 90% savings
  // ... and more
}

Use Cases

LLM Router

import { where, cost } from 'llm-zoo';

function route(needs: { vision?: boolean; budget: number; tokens: number }) {
  return where(c => !needs.vision || c.supportsVision)
    .filter(m => cost(m, { input: needs.tokens, output: 4000 }) <= needs.budget)
    .sort((a, b) => a.inputPrice - b.inputPrice)[0];
}

Edge Function (Supabase/Vercel)

import { lookup, exists, cost } from 'llm-zoo';

export async function validateRequest(model: string, tokens: number, tier: string) {
  if (!exists(model)) return { error: 'Unknown model' };

  const config = lookup(model)!;
  if (tier === 'free' && config.inputPrice > 1) {
    return { error: 'Upgrade for premium models' };
  }

  return {
    allowed: true,
    estimatedCost: cost(model, { input: tokens, output: 4000 })
  };
}

Cost Dashboard

import { cost, MODEL_CONFIGS } from 'llm-zoo';

const report = Object.entries(usage).map(([model, tokens]) => ({
  model,
  spent: cost(model, tokens),
  provider: MODEL_CONFIGS[model]?.provider,
}));

Direct Access

import { MODEL_CONFIGS, MODELS, ANTHROPIC_MODELS } from 'llm-zoo';

MODEL_CONFIGS['sonnet45'].inputPrice;
MODELS.forEach(name => console.log(name));
Object.keys(ANTHROPIC_MODELS);

Contributing

Found incorrect pricing? Missing capability? New model released? PRs welcome!

Model data lives in src/providers/. Just update the relevant file and submit a PR.

License

MIT