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moondream · Balanced

Moondream 3.1 9B A2B

Added Oct 16, 2026

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Use in the app

Moondream 3.1 is the successor to Moondream 3 Preview: a distinct 9B mixture-of-experts vision-language checkpoint with 2B active parameters, for visual question answering, captioning, OCR, and visual reasoning. It accepts text or one image with optional reasoning, a 32,000-token context, and up to 4,096 output tokens.

  • Reasoning
  • Vision
Input
Text, Images
Output
Text
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$0.30
Output
$2.50

Reference prices as published by the model provider. API example

Specifications

Context window
32K
Max output
4.1K
Average output (7 days)
120 tokens
Longer than 11% of 468 models

Side by side

Moondream 3.1 9B A2B compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Moondream 3.1 9B A2BmoondreamThis modelQwen3 VL 235B A22B Instruct OriginalQwenRemove
ProvidermoondreamQwen
Discovery tierBalancedBalanced
AddedOct 16, 2026Sep 25, 2025
Limits
Context window32K—
Max output4.1K32.77KBest
Average output120 tokens288 tokens
Pricing, USD per 1M tokens
Input$0.30$0.30
Output$2.50$1.90Best
Performance
Request success (24h)—100.0%
Benchmark indexes
Intelligence Index—9.9
Math Index—70.7
Capabilities
ReasoningYesNo
VisionYesYes
Reasoning effort——

Public evaluations

Benchmarks

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

  • Moondream 3.1 9B A2B
  • Qwen3 VL 235B A22B Instruct Original

Intelligence Index

  • Moondream 3.1 9B A2B—
  • Qwen3 VL 235B A22B Instruct Original9.9
3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • Moondream 3.1 9B A2B: —
    • Qwen3 VL 235B A22B Instruct Original: 70.7

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Moondream 3.1 9B A2B: —
    • Qwen3 VL 235B A22B Instruct Original: 32.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Moondream 3.1 9B A2B: —
    • Qwen3 VL 235B A22B Instruct Original: 6.6%

  • GPQA Diamond

    Graduate-level science questions

    • Moondream 3.1 9B A2B: —
    • Qwen3 VL 235B A22B Instruct Original: 71.2%

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • Moondream 3.1 9B A2B: —
    • Qwen3 VL 235B A22B Instruct Original: 82.3%

  • IFBench

    Following precise output instructions

    • Moondream 3.1 9B A2B: —
    • Qwen3 VL 235B A22B Instruct Original: 42.7%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • Moondream 3.1 9B A2B: —
    • Qwen3 VL 235B A22B Instruct Original: 59.4%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • Moondream 3.1 9B A2B: —
    • Qwen3 VL 235B A22B Instruct Original: 70.7%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Moondream 3.1 9B A2B: —
    • Qwen3 VL 235B A22B Instruct Original: 6.8%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Moondream 3.1 9B A2B: —
    • Qwen3 VL 235B A22B Instruct Original: 35.1%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Moondream 3.1 9B A2B: —
    • Qwen3 VL 235B A22B Instruct Original: 32.7%

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": "moondream/moondream3.1-9b-a2b",
    "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="moondream/moondream3.1-9b-a2b",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

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