Atlas / Models / Inception / Inception: Mercury

Inception: Mercury✓ Catalog verified

inception/mercury

Mercury is the first diffusion large language model (dLLM). Applying a breakthrough discrete diffusion approach, the model runs 5-10x faster than even speed optimized models like GPT-4.1 Nano and Claude 3.5 Haiku while matching their performance. Mercury's speed enables developers to provide responsive user experiences, including with voice agents, search interfaces, and chatbots. Read more in the [blog post] (https://www.inceptionlabs.ai/blog/introducing-mercury) here.

Input price
$0.25 /1M
Output price
$0.75 /1M
Context
128K
Modalities
text
Released
Jun 26, 2025
Tool calling
✓ Yes
Atlas signal
84/100
01

Overview

Mercury is the first diffusion large language model (dLLM). Applying a breakthrough discrete diffusion approach, the model runs 5-10x faster than even speed optimized models like GPT-4.1 Nano and Claude 3.5 Haiku while matching their performance. Mercury's speed enables developers to provide responsive user experiences, including with voice agents, search interfaces, and chatbots. Read more in the [blog post] (https://www.inceptionlabs.ai/blog/introducing-mercury) here.

Access: available through the official Inception API. Context window: 128K.

Pricing and metadata from the ModelsAtlas catalog.Last refreshed Aug 5, 2026
02

Specifications

API identifierinception/mercury
ProviderInception
Model typeText LLM
Context window128K catalog
Input modalitiestext
Output modalitiestext
ReleasedJun 26, 2025
ModeratedNo
Architecture modalitytext->text
Scheduled expiry2026-04-15
Supported parameters
max_tokensresponse_formatstopstructured_outputstemperaturetool_choicetools
Source: provider documentation + catalog feedMethodology →

API defaults

Default parameters
{
  "top_p": null,
  "temperature": 0,
  "frequency_penalty": null
}
03

Pricing

Live pricing components for inception/mercury as published in the catalog.

$0.25
Input /1M
$0.75
Output /1M
Per request
Per image
Pricing componentRaw unit priceNormalizedUnit
Prompt tokens$2.5e-7$0.25 / 1MPer input token
Completion tokens$7.5e-7$0.75 / 1MPer output token
Request feeN/AN/APer request
Image feeN/AN/APer image unit
Web search feeN/AN/APer search request
Source: catalog pricing feedCompare all pricing →Cheapest models →
04

Cost calculator

Estimate monthly spend from your own token volumes.

Scale / Volume

Estimated Total Cost

$0.28Calculated from current list pricing in the ModelsAtlas catalog.
05

Capabilities

CapabilityStatusWhat it means
Visual UnderstandingNot advertisedImage and document analysis support
Audio ProcessingNot advertisedSpeech and voice aligned flows
Tool Calling✓ SupportedSupports tools / function calling
Self-HostingNot advertisedDeploy outside managed APIs
Derived from catalog capability tags and supported parameters
06

Capability signals

Directional signals derived from model metadata and capability tags — not official benchmark submissions.

Inception: Mercury
MMLU Signal (Reasoning)
79signal
Coding Signal (HumanEval proxy)
97signal
Math Signal (GSM8K proxy)
79signal
Science Signal (GPQA proxy)
79signal
Estimated from metadata — not an official benchmark runAll benchmarks →Methodology →
07

Quick start

Call Inception: Mercury through an OpenAI-compatible client.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="inception/mercury",
    messages=[{"role": "user", "content": "Explain quantum physics."}]
)

print(response.choices[0].message.content)
08

Alternatives

Closest models by context window from a different provider.

09

Sources & attribution

Pricing and metadata are maintained in the ModelsAtlas catalog.

Capability bars use metadata tags — directional estimates onlyHow we source and verify data →
10

Frequently asked questions

How much does Inception: Mercury cost?

$0.25 per 1M input tokens and $0.75 per 1M output tokens on the official Inception API.

What is the context window of Inception: Mercury?

Inception: Mercury supports up to 128K tokens of context.

Does Inception: Mercury support tool / function calling?

Yes, Inception: Mercury supports tool / function calling — you can register tools and the model will emit structured tool calls.

How do I access Inception: Mercury?

Use the official Inception API with the model id `inception/mercury`. See the Quick start section above for code examples.