Inception: Mercury 2
Reasoning model for deliberate analysis, multi-step problem solving, and tool use
- Model lab
- Inception
- Model family
- mercury
Quickstart
Use your Moduck API Key, set the API base URL to https://api.moduck.ai/v1, and set the model parameter to inception/mercury-2.
import os
import requests
base_url = "https://api.moduck.ai/v1"
api_key = os.environ["MODUCK_API_KEY"]
model_id = "inception/mercury-2"
response = requests.post(
f"{base_url}/chat/completions",
headers={
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
},
json={
"model": model_id,
"messages": [{"role": "user", "content": "Hello!"}],
"stream": False,
},
timeout=60,
)
response.raise_for_status()
print(response.json())Use the familiar OpenAI-style chat request format to make model integration easier.
Mercury 2 API Pricing
| Type | Price information |
|---|---|
| Input | USD 0.2 / 1M tokens |
| Output | USD 0.6 / 1M tokens |
| Cached input | USD 0.02 / 1M tokens |
Benchmarks
Performance
Measured on the Moduck gateway across live traffic, hour by hour over the last 24 hours. Time to first token is how long before anything appears; throughput is how fast the answer is written after that; end-to-end latency is the whole round trip. Figures are medians unless the card says otherwise.
Artificial Analysis measurement
Performance trends
Availability
Uptime is the share of time at least one provider serving this model responded. Availability is stricter: the share of requests actually served. A provider that answers but fails part of the traffic lowers availability without lowering uptime. Both cover the last three days.
Mercury 2 Compare models
| Model | Input price | Output price | Context window | Capabilities |
|---|---|---|---|---|
| Mercury 2This page | USD 0.2 / 1M tokens | USD 0.6 / 1M tokens | 128,000 | Text output · Reasoning · Tool calling |
| Mercury 2.5 | USD 0.2 / 1M tokens | USD 0.75 / 1M tokens | 260,000 | Text output · Reasoning · Tool calling |
| Beam 1.0 501B A23B | USD 0.2 / 1M tokens | USD 0.8 / 1M tokens | 1,048,576 | Text output · Reasoning · Tool calling |
| Ling 3.1 Flash | USD 0.06 / 1M tokens | USD 0.176 / 1M tokens | 262,144 | Text output · Reasoning · Tool calling |
| Schematron V2 Small | USD 0.04 / 1M tokens | USD 0.184 / 1M tokens | 128,000 | Text output |
Model specifications
- Input
- text
- Output
- text
- Context window
- 128,000
- Maximum output
- 50,000
- Release date
- 2026-03-04
- Attachments
- No
- Reasoning
- Yes
- Tool calling
- Yes
- Structured output
- Yes
- Temperature setting
- Yes
- Open weights
- No
Frequently asked questions
What is Mercury 2 for?
Reasoning model for deliberate analysis, multi-step problem solving, and tool use
What inputs and outputs does Mercury 2 support?
Recorded inputs: text; outputs: text.
How is Mercury 2 priced?
The pricing table shows the current recorded Moduck price. For example: Input USD 0.2 / 1M tokens; Output USD 0.6 / 1M tokens. See the pricing table for all units, variants, and conditions.
What specifications are recorded for Mercury 2?
Current model records list Context window 128,000 tokens; Maximum output 50,000 tokens.
What model parameter does the Quickstart use?
The example uses inception/mercury-2. This value comes from the page identifier and is not confirmed as a callable Moduck public ID.
Can I call this model through the Moduck API now?
This page has no verified Moduck API call for this model. A Quickstart example or reserved ID does not establish access; check the models available to your account.