One API key.
Every model.

The Yielding Bear API provides unified access to 50+ large language models through a single universal endpoint. Just change your base URL — no code refactoring required.

Our intelligent routing picks the most efficient model for your reasoning needs — fast models for simple tasks, high-reasoning models for complex work — delivering meaningful cost reductions vs direct API calls. Every request is analyzed, classified, and routed to the optimal model.

The API supports both direct model selection (you pick the exact model) and automatic routing (Yielding Bear picks the best model for your task). Both modes are available through the same endpoint.

All API requests require an API key passed as a Bearer token in the Authorization header. Get your API key from the dashboard.

Authorization: Bearer yb_live_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

export YB_API_KEY="yb_live_sk_aaf1ccf8b34ebda1c52d..."

# Verify your key works
curl https://yieldingbear.com/api/v1/usage \
  -H "Authorization: Bearer $YB_API_KEY"

The Chat Completions endpoint is universally compatible. Send a POST request with messages and receive a structured response. Works with any LLM SDK, including the OpenAI SDKs.

POST /v1/chat/completions

{
  "model": "groq/llama-3.1-8b-instant",
  "messages": [
    { "role": "system", "content": "You are a helpful assistant." },
    { "role": "user", "content": "What is the capital of France?" }
  ],
  "temperature": 0.7,
  "max_tokens": 256,
  "stream": false
}

curl -X POST https://yieldingbear.com/api/v1/chat/completions \
  -H "Authorization: Bearer $YB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "groq/llama-3.1-8b-instant",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

{
  "id": "chatcmpl-3552055b-e963-4907-a077-d76f5a1019e7",
  "object": "chat.completion",
  "created": 1781641651,
  "model": "groq/llama-3.1-8b-instant",
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "The capital of France is Paris."
    },
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 36,
    "completion_tokens": 24,
    "total_tokens": 36
  },
  "cost_usd": 0.000017,
  "balance_remaining_usd": 4.9911
}

{
  "id": "chatcmpl-3552055b-e963-4907-a077-d76f5a1019e7",
  "object": "chat.completion",
  "created": 1781641651,
  "model": "groq/llama-3-3-70b-versatile",   ← actual underlying model that served the request
  "choices": [{
    "index": 0,
    "message": {
      "role": "assistant",
      "content": "It's nice to meet you. Is there something I can help you with, or would you like to chat?"
    },
    "finish_reason": "stop"
  }],
  "usage": {
    "prompt_tokens": 36,
    "completion_tokens": 24,
    "total_tokens": 36
  },
  "cost_usd": 0.000017,
  "balance_remaining_usd": 4.9911,
  "routing": {
    "category": "general",                                       ← which specialist was called
    "intent":   "text",                                          ← text or image
    "tier":     "low",                                           ← low = cheap, high = powerful
    "routed_to": "groq/llama-3-3-70b-versatile",                 ← resolved underlying model
    "reason":    "general:no-high-signals;default-low",          ← why this tier was picked
    "explicit":  false                                           ← true if user forced tier/force via header or body
  }
}

{
  "id": "chatcmpl-R1p2pOLmD2huJgdFQLrm0BCd",
  "model": "deepinfra/qwen3-coder-480b",   ← swapped to the 480B free Coder
  ...
  "routing": {
    "category": "coding",
    "intent":   "text",
    "tier":     "high",
    "routed_to": "deepinfra/qwen3-coder-480b",
    "reason":    "cat=coding, kw:\"refactor\"",
    "explicit":  false
  }
}

Call any of the five Grizzly 1.0G smart routers instead of a specific model. The router classifies the prompt and picks the most efficient underlying model — paying nothing extra on top of the routed model's per-Mtok rate. Same endpoint, same auth, same response shape as Chat Completions. Returns an extra routing field so you can see what was picked.

curl https://yieldingbear.com/api/v1/chat/completions \
  -H "Authorization: Bearer $YB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "yieldingbear/grizzly-1.0g",
    "messages": [
      { "role": "user", "content": "Write a haiku about coding" }
    ]
  }'

curl https://yieldingbear.com/api/v1/chat/completions \
  -H "Authorization: Bearer $YB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "yieldingbear/grizzly-1.0g-coding",
    "messages": [
      { "role": "user", "content": "Refactor this Python function to use async/await:\n\ndef fetch_all(urls):\n    return [requests.get(u).json() for u in urls]" }
    ]
  }'

curl https://yieldingbear.com/api/v1/chat/completions \
  -H "Authorization: Bearer $YB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "yieldingbear/grizzly-1.0g-creative",
    "messages": [
      { "role": "user", "content": "Write a 3-sentence product description for a bear-themed energy drink" }
    ]
  }'

curl https://yieldingbear.com/api/v1/chat/completions \
  -H "Authorization: Bearer $YB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "yieldingbear/grizzly-1.0g-finance",
    "messages": [
      { "role": "user", "content": "What is the current price of NVDA and what is its 50-day moving average?" }
    ]
  }'

Generate text embeddings through a single endpoint. Output is an OpenAI-shaped vector array you can drop into any vector DB (Pinecone, Supabase pgvector, Weaviate, etc.). Use the response data[].embedding field — no parsing needed.

POST /v1/embeddings

{
  "model": "deepinfra/bge-base-en-v1.5",
  "input": "The food was delicious and the service was excellent."
}

curl -X POST https://yieldingbear.com/api/v1/embeddings \
  -H "Authorization: Bearer $YB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepinfra/bge-base-en-v1.5",
    "input": "The food was delicious and the service was excellent."
  }'

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [0.0107, 0.0557, 0.0270, ...768 floats total]
    }
  ],
  "model": "deepinfra/bge-base-en-v1.5",
  "usage": { "prompt_tokens": 4, "total_tokens": 4 },
  "cost_usd": 0,
  "balance_remaining_usd": 4.99
}

List all available models. This endpoint is public and does not require authentication. Use it to discover models and check their current pricing.

GET /v1/models

curl https://yieldingbear.com/api/v1/models

Rate limits protect the API from abuse and ensure fair access. Limits are applied per API key and vary by tier.

{
  "error": {
    "message": "Rate limit exceeded: 60 requests per minute",
    "type": "rate_limit_exceeded",
    "code": "rate_limit_exceeded"
  }
}

Enable streaming to receive tokens as they are generated. This reduces perceived latency for long responses. Use the stream: true parameter.

{
  "model": "groq/llama-3.1-8b-instant",
  "messages": [{"role": "user", "content": "Write a haiku about coding"}],
  "stream": true
}

data: {"id":"chatcmpl-e96f1581-d9bb-46c9-8f9c-68b27e45a717","choices":[{"finish_reason":null,"index":0,"delta":{"function_call":null,"tool_calls":null,"content":"Lines","role":"assistant"}}],"created":1781641928,"model":"llama-3.1-8b-instant","object":"chat.completion.chunk","system_fingerprint":"fp_e2c608b1d6","usage":{}}

data: {"id":"chatcmpl-e96f1581-d9bb-46c9-8f9c-68b27e45a717","choices":[{"finish_reason":null,"index":0,"delta":{"function_call":null,"tool_calls":null,"content":" of"}}],"created":1781641928,"model":"llama-3.1-8b-instant","object":"chat.completion.chunk","system_fingerprint":"fp_e2c608b1d6","usage":{}}

data: {"id":"chatcmpl-e96f1581-d9bb-46c9-8f9c-68b27e45a717","choices":[{"finish_reason":"stop","index":0,"delta":{"content":null}}],"created":1781641928,"model":"llama-3.1-8b-instant","object":"chat.completion.chunk","system_fingerprint":null,"usage":{}}

data: [DONE]

import sys
sys.path.insert(0, os.path.expanduser("~/.yieldingbear"))
from yieldingbear import YieldingBear

client = YieldingBear.from_key_file()  # picks up ~/.hermes/secrets/yieldingbear-token

for chunk in client.chat.completions.stream(
    model="yieldingbear/grizzly-1.0g",   # or any specific model
    messages=[{"role": "user", "content": "Hello!"}],
):
    if chunk.delta:                      # chunk.delta is a str of the new text
        print(chunk.delta, end="", flush=True)

Every chat response includes cost_usd and balance_remaining_usd. For an aggregated view (totals, per-model breakdown, recent requests), call GET /api/v1/usage with your API key.

GET /api/v1/usage

curl https://yieldingbear.com/api/v1/usage \
  -H "Authorization: Bearer $YB_API_KEY"

{
  "account": { "email": "you@example.com", "credit_balance_usd": 4.99 },
  "totals": {
    "cost_usd": 0.000452,
    "prompt_tokens": 1359,
    "completion_tokens": 1020,
    "total_tokens": 2379,
    "calls": 50
  },
  "by_model": [
    { "model": "yieldingbear/grizzly-1.0g", "calls": 3, "tokens": 157, "cost_usd": 0.000031 },
    { "model": "anthropic/claude-3-5-sonnet-latest", "calls": 2, "tokens": 34, "cost_usd": 0.000306 }
  ],
  "usage": [
    {
      "id": "edfcb790-d59e-4f51-b543-f45bf39bb3e9",
      "model": "groq/llama-3.1-8b-instant",
      "provider": "groq",
      "input_tokens": 36,
      "output_tokens": 8,
      "total_tokens": 44,
      "cost_usd": 0,
      "latency_ms": 137,
      "created_at": "2026-06-16T20:27:16.396812+00:00"
    }
  ]
}

The API follows OpenAI's error format. All errors return a JSON body with a top-level error object. Always check for errors in your response handling.

{
  "error": {
    "message": "Invalid API key",
    "type": "invalid_request_error",
    "code": "authentication_error",
    "param": null,
    "status": 401
  }
}

Free tier includes unlimited requests to Groq, Cerebras, and Together models. Paid tier gives access to premium models (OpenAI, Anthropic, Google, DeepSeek, Mistral) with a small markup over provider pricing.

Start with the native Yielding Bear SDK — zero dependencies, vendored by the installer. Every other LLM SDK works too: just point its base_url at https://yieldingbear.com/api/v1.

Yielding Bear SDK

Zero dependencies. Vendored to ~/.yieldingbear/lib/ by the installer.

Python

Node