Vercel AI Gateway exposes Mercury 3 through model ID inception/mercury-3. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-10-19. Next refresh: weekly.
Quick Start
- 1
- 2Use the Vercel AI Gateway SDK or REST API to call
inception/mercury-3— see the documentation for request format. - 3
Code Examples
pip install openaiAI_GATEWAY_API_KEYinception/mercury-3creator/model-name e.g. kwaipilot/kat-coder-pro-v2
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],
base_url="https://ai-gateway.vercel.sh/v1"
)
response = client.chat.completions.create(
model="inception/mercury-3",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Vercel AI Gateway
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.10 |
| Output tokens | $0.35 |
Capabilities
About Mercury 3
Mercury 3 is Inception's diffusion LLM (dLLM), released 2026-10-19 on the Inception API (model id mercury-3) and through OpenRouter, Baseten and Vercel. It has a 1M-token context window and up to 131,072 output tokens, takes text in and returns text, and supports tool calling and structured outputs via the OpenAI-compatible v1/chat/completions endpoint. Reasoning effort can be set to instant, low, medium or high, and temperature from 0.5 to 1.0. Inception reports 1,068 output tokens per second on NVIDIA GPUs and says the model is more than 40x larger in total parameters than Mercury 1 (absolute size not disclosed).