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Available now on ModelsLab · Language Model

Upstage: Solar Pro 3Reason Deeper. Scale Effortlessly

Deploy Production Reasoning Now

MoE Architecture

102B Parameters Active 12B

Tripled scale over Solar Pro 2 delivers 30% reasoning gains without TPS or cost increase.

Instruction Following

52% IFBench Improvement

Excels in multi-step tasks and user intent capture for Korean and English queries.

Enterprise Ready

Same Latency Costs

Retains Solar Pro 2 efficiency for complex agent workflows and production stability.

Examples

See what Upstage: Solar Pro 3 can create

Copy any prompt below and try it yourself in the playground.

Logic Puzzle

Solve this step-by-step: Three houses in a row, labeled A B C. A has red door, B blue, C green. Owners: Smith likes cats, Jones dogs, Lee birds. Smith not in green. Dogs not next to birds. Who owns birds?

Math Proof

Prove by induction: Sum of first n even numbers equals n(n+1). Show base case, assume for k, prove for k+1. Explain each step clearly.

Code Debug

Fix this Python function that sorts list but fails on duplicates: def sort_unique(lst): return sorted(set(lst)). Add tests for [1,2,2,3] expecting [1,2,3]. Preserve order where possible.

Strategy Plan

Outline 5-step plan to launch AI agent for customer support. Include reasoning for each step, metrics for success, and edge cases like multilingual queries.

For Developers

A few lines of code.
Reasoning LLM. One Call.

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

  • Serverless: scales to zero, scales to millions
  • Pay per token, no minimums
  • Python and JavaScript SDKs, plus REST API
import requests
response = requests.post(
"https://modelslab.com/api/v7/llm/chat/completions",
json={
"key": "YOUR_API_KEY",
"prompt": "",
"model_id": ""
}
)
print(response.json())

FAQ

Common questions about Upstage: Solar Pro 3

Read the docs

Ready to create?

Start generating with Upstage: Solar Pro 3 on ModelsLab.