Models

BlockRun provides access to models from multiple providers through a unified API.

List Models

GET https://blockrun.ai/api/v1/models

Returns a list of available models with pricing information. The response now includes extended metadata for each model.

Response Fields

Each model object in the response includes:

Example Response

{
  "models": [
    {
      "id": "openai/gpt-5.5",
      "name": "GPT-5.5",
      "description": "OpenAI's flagship — first fully retrained base since GPT-4.5; 1M context, 128K output, native agent + computer use",
      "provider": "openai",
      "inputPrice": 5.00,
      "outputPrice": 30.00,
      "context_window": 1050000,
      "max_output": 128000,
      "categories": ["chat", "coding", "vision"],
      "available": true
    }
  ]
}

Available Models (chat / image / video / music / speech / sound effects)

All prices shown are provider rates. BlockRun adds a 5% platform fee to cover infrastructure costs.

OpenAI GPT-5.6 Family

Released 2026-07-09 — three fixed tiers (Sol / Terra / Luna) replacing the single-model-plus-effort-knob line. Note: on /v1/chat/completions, GPT-5.6 accepts function tools only with reasoning_effort: "none" — the BlockRun gateway sets this automatically when tools are present, so no client change is needed.

OpenAI GPT-5.5 Family

Released 2026-04-23 — first fully retrained base since GPT-4.5.

OpenAI GPT-5.4 Family

OpenAI GPT-5 Family

OpenAI O-Series (Reasoning)

Anthropic Claude

Google Gemini

Gemini Pro models (gemini-2.5-pro, gemini-3.1-pro) bill a long-context tier — 2x input, 1.5x output above 200K prompt tokens (mirrors Google's official pricing: gemini-2.5-pro is $2.50/M in · $15.00/M out, gemini-3.1-pro is $4.00/M in · $18.00/M out above the threshold). Flash / Flash-Lite are flat-priced.

xAI Grok

Grok bills a long-context tier at 2x the rates above once a request's prompt reaches 200K tokens (mirrors xAI's official pricing — e.g. Grok 4.5 is $5.00/M in · $18.00/M out above the threshold). Live Search adds $0.025 per source used. Grok Imagine image/video SKUs are listed under Image / Video Generation below.

DeepSeek

Z.AI

Moonshot

K3 is the current flagship — a 2.8-trillion-parameter open MoE with a 1M-token context window, image + text input, returning reasoning_content on completions. K2.7 (256K, adds video input) remains routable but superseded; K2.6 and K2.5 are earlier multi-modal generations, still routable.

MiniMax

Qwen (Alibaba)

Free Tier (open-weight)

Open-weight models served free of charge (no x402 payment), subject to a small per-IP rate limit. The free tier auto-routes around any temporarily unavailable model, so the live set is best read from GET /api/v1/models (filter on billingMode: "free"). There are 8 free models listed on mainnet; the free tier's fallback workhorse is nvidia/gpt-oss-120b (nvidia/llama-4-maverick is temporarily offline upstream and auto-redirects to it).

Image Generation

Video Generation

Seedance defaults to 720p with synced audio for text-to-video; pass resolution / generate_audio to override. See Video Generation API.

For character consistency across multiple Seedance videos, enroll a Virtual Portrait ($0.012 one-time, no KYC) for AI characters, or a RealFace ($0.012 one-time, no KYC, requires brief on-phone liveness check) for real people. Pass the returned ta_xxx as real_face_asset_id.

Model Categories

Each model includes a categories array in the API response. Categories indicate model capabilities:

• chat - General conversation
• reasoning - Complex problem-solving
• coding - Code generation and analysis
• vision - Image understanding

Filter models by category:

models = client.list_models()
reasoning_models = [m for m in models if "reasoning" in m.get("categories", [])]

Pricing

Prices are per 1 million tokens. Your actual cost depends on:

1. Input tokens - Length of your prompt and context
2. Output tokens - Length of the model's response
3. Platform fee - 5% added to provider rates

The SDK calculates the exact price before each request.

Want to save 87% automatically? ClawRouter routes each request to the cheapest model that can handle it.

Example

What's next?