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upstage · Efficient

Solar Mini 4

Added Sep 23, 2026

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Use in the app

Upstage's compact 35B-parameter mixture-of-experts model with 3B active parameters and a 524K context window. Built for fast, cost-efficient agentic tasks, with strong Korean and English support.

  • Tools
  • Structured output
Input
Text
Output
Text
Discovery tier
Efficient

Pricing

USD per 1M tokens
Input
$0.05
Output
$0.20
Cache read
$0.005

Reference prices as published by the model provider. API example

Specifications

Context window
524.3K
Max output
131.1K
Average output (7 days)
561 tokens
Longer than 53% of 465 models

Side by side

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TryDeepSeek V4 Flash 0423 (Thinking)GPT 5.1 Codex MaxLing 3.0 Flash VLAll 3

Public evaluations

Benchmarks

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

Intelligence Index

24.1

Better than 59% of 326 scored models

3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    22.3%

    Workflow automation, penalized for guardrail violations

    Better than 45% of 173 scored models

  • AutomationBench-AA tasks completed

    2.4%

    Workflows finished end to end without a guardrail violation

    Better than 37% of 173 scored models

  • AA-Briefcasev1.1

    867 Elo

    Agentic knowledge work, rated head to head

    Better than 35% of 166 scored models

  • GDPval-AAv2.1

    1,085 Elo

    Economically valuable occupational tasks, rated head to head

    Better than 44% of 187 scored models

Document reasoning

  • GDP.pdf

    5.0%

    Professional reasoning over PDF documents, all-pass rate

    Better than 21% of 171 scored models

  • AA-LCRv1.1

    83.3%

    Reasoning across long documents

    Better than 92% of 309 scored models

  • MLCR-AA

    6.7%

    Long-context reasoning over medical records

    Better than 25% of 121 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    25.8%

    Expert-level questions across academic fields

    Better than 56% of 323 scored models

Coding

  • Terminal-Benchv4.0

    1.0%

    Practical software engineering in a terminal

    Better than 37% of 171 scored models

  • SciCode

    47.6%

    Scientific computing in Python

    Better than 41% of 174 scored models

Legacy evaluations

  • AA-LCR (unversioned)

    83.3%

    Long-context reasoning, earlier grading

    Better than 92% of 309 scored models

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

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
90.8 tok/s
Faster than 58% of 251 models
Time to first token
2.2 s
Quicker than 73% of 251 models
Prompt cache hits
0.0%
About $0.05 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.

Hourly request success · last 72 hoursLowest hour 100.0%
  • 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.

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": "upstage/solar-mini4",
    "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="upstage/solar-mini4",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

upstage

Other upstage models, starting with the same family.