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upstage · Efficient

Solar Pro 4

Added Aug 11, 2026

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Use in the app

Upstage's Solar Pro 4 is a long-context language model for agentic workflows, office productivity, document-intensive work, and coding. This variant keeps reasoning disabled for faster direct responses.

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

Pricing

USD per 1M tokens
Input
$0.03
Output
$0.12
Cache read
$0.006

Reference prices as published by the model provider. API example

Specifications

Context window
524.3K
Max output
131.1K
Average output (7 days)
546 tokens
Longer than 51% of 465 models

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TryGLM 5 TurboNvidia Nemotron 3.5 Super VLClaude 4.6 OpusAll 3

Public evaluations

Benchmarks

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

Intelligence Index

26.6

Better than 67% of 326 scored models

3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    13.6%

    Workflow automation, penalized for guardrail violations

    Better than 35% 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

    1,093 Elo

    Agentic knowledge work, rated head to head

    Better than 51% of 166 scored models

  • GDPval-AAv2.1

    1,106 Elo

    Economically valuable occupational tasks, rated head to head

    Better than 45% of 187 scored models

Document reasoning

  • GDP.pdf

    7.0%

    Professional reasoning over PDF documents, all-pass rate

    Better than 30% of 171 scored models

  • AA-LCRv1.1

    70.7%

    Reasoning across long documents

    Better than 51% of 309 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    29.8%

    Expert-level questions across academic fields

    Better than 62% of 323 scored models

  • GPQA Diamond

    89.1%

    Graduate-level science questions

    Better than 72% of 291 scored models

Coding

  • Terminal-Benchv4.0

    0.0%

    Practical software engineering in a terminal

    Better than 0% of 171 scored models

  • SciCode

    48.0%

    Scientific computing in Python

    Better than 44% of 174 scored models

Legacy evaluations

  • AA-LCR (unversioned)

    70.7%

    Long-context reasoning, earlier grading

    Better than 51% 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
80.3 tok/s
Faster than 51% of 247 models
Time to first token
2.4 s
Quicker than 67% of 247 models
Prompt cache hits
0.8%
About $0.0298 per 1M input tokens with caching
Request success (24h)
99.9%
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 97.5%
  • 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-pro4",
    "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-pro4",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

upstage

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