Mercury 3 is a diffusion-based LLM from Inception, released on October 19, 2026. It achieves performance on par with or better than GPT-6 Luna and Claude Haiku 5.5 across benchmarks while delivering 4–8× higher speed at over 1,000 tokens per second and a 1-million-token context window. (Sources: Inception announcement, Unite.ai coverage)
Pricing
Prices as of October 24, 2026, source: qubax.ai/price-index
| Provider | Input ($/1M) | Output ($/1M) |
|---|---|---|
| Qubax | 0.075 | 0.2625 |
| OpenRouter | 0.10 | 0.35 |
Qubax provides the lowest price for Mercury 3.
How to Use Mercury 3
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("QUBAX_API_KEY"),
base_url="https://api.qubax.ai/v1",
)
response = client.chat.completions.create(
model="mercury-3",
messages=[{"role": "user", "content": "Explain how diffusion LLMs generate text in parallel."}]
)
print(response.choices[0].message.content)Full setup in /docs/quickstart. The model slug is mercury-3.
When to Choose Mercury 3
Choose Mercury 3 for latency-sensitive applications like real-time agents, tutoring, or search where speed >1k tok/s matters. It offers better price/performance than alternatives.
- Vs GLM-5.3: faster inference at lower cost for most workloads.
- Vs DeepSeek V4 Flash: higher quality for agentic tasks while remaining competitive on price.
See live benchmarks on /price-index and our LLM cost audit.
FAQ
What is the price of Mercury 3 on Qubax?
$0.075 per million input tokens and $0.2625 per million output tokens.
What is the context length of Mercury 3?
1 million tokens.
How do I call the Mercury 3 API?
Use the OpenAI Python SDK with base_url="https://api.qubax.ai/v1" and model="mercury-3".
Is Mercury 3 cheaper than on OpenRouter?
Yes — Qubax is 25% lower on both input and output pricing.
What makes Mercury 3 different from traditional LLMs?
It is a diffusion LLM that generates and refines many tokens in parallel through iterative denoising instead of sequential next-token prediction.
