Inception · Efficient
Mercury Coder Small
Model by Inception AI. A diffusion large language model that runs incredibly quickly (500+ tokens/second) while matching Claude 3.5 Haiku and GPT-4o-mini. 1st in speed on Copilot arena, and matching 2nd in quality.
- Input
- Text
- Output
- Text
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.25
- Output
- $1.00
Reference prices as published by the model provider. API example
Specifications
- Context window
- 32.8K
- Max output
- 16.4K
Side by side
Mercury Coder Small compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Mercury Coder SmallInceptionThis model | Mercury 3InceptionRemove | |
|---|---|---|
| Provider | Inception | Inception |
| Discovery tier | Efficient | Efficient |
| Added | Jan 1, 2024 | Oct 19, 2026 |
| Limits | ||
| Context window | 32.77K | 1MBest |
| Max output | 16.38K | 131.07KBest |
| Average output | — | 1.9K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.25 | $0.10Best |
| Output | $1.00 | $0.35Best |
| Cache read | — | $0.01 |
| Performance | ||
| Throughput | — | 913.7 tok/s |
| Time to first token | — | 1.9 s |
| Request success (24h) | — | 100.0% |
| Capabilities | ||
| Reasoning | No | Yes |
| Tools | No | Yes |
| Structured output | No | Yes |
| Parallel tools | No | Yes |
| Reasoning effort | — | none, low, medium, high |
Public evaluations
Benchmarks
There are no public benchmark results for these models yet.
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": "mercury-coder-small",
"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="mercury-coder-small",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Inception
Related models
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