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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

Side by side

Solar Pro 4 compared

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

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Solar Pro 4upstageThis modelNvidia Nemotron 3.5 Super VLnvidiaRemove
Providerupstagenvidia
Discovery tierEfficientOpen weights
AddedAug 11, 2026Oct 15, 2026
Limits
Context window524.29KBest262.14K
Max output131.07KBest16.38K
Average output546 tokens1.1K tokens
Pricing, USD per 1M tokens
Input$0.03Best$0.15
Output$0.12Best$0.50
Cache read$0.006Best$0.02
Performance
Throughput101.4 tok/s654.7 tok/sBest
Time to first token3.1 s1.8 sBest
Request success (24h)99.9%Best98.0%
Benchmark indexes
Intelligence Index26.6Best26.5
Capabilities
ReasoningNoYes
ToolsYesYes
VisionNoYes
Structured outputYesYes
Video inputNoYes
Reasoning effort—none, medium, high

Public evaluations

Benchmarks

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

  • Solar Pro 4
  • Nvidia Nemotron 3.5 Super VL

Intelligence Index

  • Solar Pro 426.6
  • Nvidia Nemotron 3.5 Super VL26.5

Solar Pro 4: Better than 67% of 326 scored models

3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Solar Pro 4: 13.6%
    • Nvidia Nemotron 3.5 Super VL: 14.8%Top

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Solar Pro 4: 2.4%Top
    • Nvidia Nemotron 3.5 Super VL: 2.0%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Solar Pro 4: 1,093 EloTop
    • Nvidia Nemotron 3.5 Super VL: 999 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Solar Pro 4: 1,106 Elo
    • Nvidia Nemotron 3.5 Super VL: 1,162 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Solar Pro 4: 7.0%
    • Nvidia Nemotron 3.5 Super VL: 8.0%Top

  • AA-LCRv1.1

    Reasoning across long documents

    • Solar Pro 4: 70.7%Top
    • Nvidia Nemotron 3.5 Super VL: 69.0%

  • MLCR-AA

    Long-context reasoning over medical records

    • Solar Pro 4: —
    • Nvidia Nemotron 3.5 Super VL: 13.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Solar Pro 4: 29.8%
    • Nvidia Nemotron 3.5 Super VL: 30.7%Top

  • GPQA Diamond

    Graduate-level science questions

    • Solar Pro 4: 89.1%
    • Nvidia Nemotron 3.5 Super VL: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Solar Pro 4: 0.0%Top
    • Nvidia Nemotron 3.5 Super VL: 0.0%Top

  • SciCode

    Scientific computing in Python

    • Solar Pro 4: 48.0%Top
    • Nvidia Nemotron 3.5 Super VL: 47.8%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Solar Pro 4: 70.7%Top
    • Nvidia Nemotron 3.5 Super VL: 69.0%

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
101.4 tok/s
Faster than 61% of 251 models
Time to first token
3.1 s
Quicker than 57% of 251 models
Prompt cache hits
1.1%
About $0.0297 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

Other upstage models, starting with the same family.