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Inception · Efficient

Mercury Coder Small

Added Jan 1, 2024

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Use in the app

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.

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Mercury Coder SmallInceptionThis modelGemini 3.1 Flash LiteGoogleRemove
ProviderInceptionGoogle
Discovery tierEfficientEfficient
AddedJan 1, 2024Mar 3, 2026
Limits
Context window32.77K1.05MBest
Max output16.38K65.54KBest
Average output—669 tokens
Pricing, USD per 1M tokens
Input$0.25$0.25
Output$1.00Best$1.50
Cache read—$0.025
Cache write—$0.0833
Performance
Request success (24h)—100.0%
Benchmark indexes
Intelligence Index—15.6
Coding Index—34.7
Capabilities
ReasoningNoYes
ToolsNoYes
VisionNoYes
Structured outputNoYes
PDF inputNoYes
Audio inputNoYes
Video inputNoYes
Reasoning effort—minimal, low, medium, high

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Mercury Coder Small
  • Gemini 3.1 Flash Lite

Intelligence Index

  • Mercury Coder Small—
  • Gemini 3.1 Flash Lite15.6
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 34.7

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 6.8%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 0.5%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 207 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 430 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 7.8%

  • AA-LCRv1.1

    Reasoning across long documents

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 74.3%

  • MLCR-AA

    Long-context reasoning over medical records

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 5.0%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 17.2%

  • GPQA Diamond

    Graduate-level science questions

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 82.2%

  • IFBench

    Following precise output instructions

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 77.2%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 0.5%

  • SciCode

    Scientific computing in Python

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 43.4%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 24.2%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 31.3%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Mercury Coder Small: —
    • Gemini 3.1 Flash Lite: 74.3%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
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

Other Inception models, starting with the same family.