Inception · Efficient
Mercury 3
Mercury 3 is Inception's diffusion language model for fast chat, coding, and multi-step agents. It accepts and generates text, with adjustable reasoning, parallel tool calls, structured JSON output, and a shared 1,000,000-token context window. Responses can use up to 131,072 tokens, including reasoning, within the remaining context.
- Reasoning
- Tools
- Structured output
- Parallel tools
- Input
- Text
- Output
- Text
- Reasoning effort
- none · low · medium · high
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.10
- Output
- $0.35
- Cache read
- $0.01
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 131.1K
- Average output (7 days)
- 1.9K tokens
- Longer than 91% of 465 models
Side by side
Mercury 3 compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Mercury 3InceptionThis model | GPT 6 LunaOpenAIRemove | |
|---|---|---|
| Provider | Inception | OpenAI |
| Discovery tier | Efficient | Efficient |
| Added | Oct 19, 2026 | Sep 22, 2026 |
| Limits | ||
| Context window | 1M | 1.05MBest |
| Max output | 131.07KBest | 128K |
| Average output | 1.9K tokens | 120 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.10 | $0.10 |
| Output | $0.35Best | $0.50 |
| Cache read | $0.01 | $0.01 |
| Cache write | — | $0.13 |
| Performance | ||
| Throughput | 735.8 tok/sBest | 68.2 tok/s |
| Time to first token | 3.7 sBest | 4.9 s |
| Request success (24h) | 100.0%Best | 99.8% |
| Benchmark indexes | ||
| Intelligence Index | — | 29.9 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | No | Yes |
| Structured output | Yes | Yes |
| PDF input | No | Yes |
| Parallel tools | Yes | No |
| Reasoning effort | none, low, medium, high | none, low, medium, high, xhigh, max |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Mercury 3
- GPT 6 Luna
Intelligence Index
- Mercury 3—
- GPT 6 Luna29.9
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Mercury 3: —
- GPT 6 Luna: 40.5%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Mercury 3: —
- GPT 6 Luna: 10.2%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Mercury 3: —
- GPT 6 Luna: 1,097 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Mercury 3: —
- GPT 6 Luna: 1,263 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Mercury 3: —
- GPT 6 Luna: 13.8%
AA-LCRv1.1
Reasoning across long documents
- Mercury 3: —
- GPT 6 Luna: 78.3%
MLCR-AA
Long-context reasoning over medical records
- Mercury 3: —
- GPT 6 Luna: 18.3%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Mercury 3: —
- GPT 6 Luna: 28.3%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Mercury 3: —
- GPT 6 Luna: 2.5%
SciCode
Scientific computing in Python
- Mercury 3: —
- GPT 6 Luna: 50.9%
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Mercury 3: —
- GPT 6 Luna: 78.3%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- Mercury 3
- GPT 6 Luna
| Leaderboard | Mercury 3 | GPT 6 Luna |
|---|---|---|
| ARC-AGI-3 (Default harness) | Not in top 20 | #18 · 0.2% |
Ranks among Noumen catalog models on ARC Prize leaderboards. Only top-20 placements are listed.ARC Prize
- Mercury 3
- GPT 6 Luna
| Leaderboard | Mercury 3 | GPT 6 Luna |
|---|---|---|
| SVG | Not in top 20 | #16 · 1250 |
Ranks among Noumen catalog models on Design Arena leaderboards. Only top-20 placements are listed.Design Arena
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Throughput
- 735.8 tok/s
- Faster than 99% of 251 models
- Time to first token
- 3.7 s
- Quicker than 47% of 251 models
- Prompt cache hits
- 77.9%
- About $0.0299 per 1M input tokens with caching
- Request success (24h)
- 100.0%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "inception/mercury-3",
"reasoning_effort": "medium",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="inception/mercury-3",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Inception
Related models
Other Inception models, starting with the same family.