upstage · Efficient
Solar Pro 4 Thinking
Upstage's Solar Pro 4 with reasoning enabled for harder agentic workflows, document-intensive work, coding, planning, and analysis across a 524K-token context window.
- Reasoning
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Reasoning effort
- none · low · medium · high
- 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)
- 1.7K tokens
- Longer than 88% of 465 models
Side by side
Solar Pro 4 Thinking compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Solar Pro 4 ThinkingupstageThis model | Solar Pro 3upstageRemove | |
|---|---|---|
| Provider | upstage | upstage |
| Discovery tier | Efficient | Efficient |
| Added | Aug 11, 2026 | Mar 3, 2026 |
| Limits | ||
| Context window | 524.29KBest | 131.07K |
| Max output | 131.07K | — |
| Average output | 1.7K tokens | — |
| Pricing, USD per 1M tokens | ||
| Input | $0.03Best | $0.15 |
| Output | $0.12Best | $0.60 |
| Cache read | $0.006Best | $0.015 |
| Performance | ||
| Request success (24h) | 99.6% | — |
| Benchmark indexes | ||
| Intelligence Index | 26.6Best | 7.8 |
| Coding Index | — | 16.2 |
| Capabilities | ||
| Reasoning | Yes | No |
| Tools | Yes | No |
| Structured output | Yes | No |
| Reasoning effort | none, low, medium, high | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Solar Pro 4 Thinking
- Solar Pro 3
Intelligence Index
- Solar Pro 4 Thinking26.6
- Solar Pro 37.8
Solar Pro 4 Thinking: Better than 67% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Solar Pro 4 Thinking: —
- Solar Pro 3: 16.2
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Solar Pro 4 Thinking: 13.6%Top
- Solar Pro 3: 0.5%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Solar Pro 4 Thinking: 2.4%Top
- Solar Pro 3: 0.0%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Solar Pro 4 Thinking: 1,093 EloTop
- Solar Pro 3: 99 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Solar Pro 4 Thinking: 1,106 EloTop
- Solar Pro 3: 264 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Solar Pro 4 Thinking: 7.0%Top
- Solar Pro 3: 1.6%
AA-LCRv1.1
Reasoning across long documents
- Solar Pro 4 Thinking: 70.7%Top
- Solar Pro 3: 32.3%
MLCR-AA
Long-context reasoning over medical records
- Solar Pro 4 Thinking: —
- Solar Pro 3: 0.6%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Solar Pro 4 Thinking: 29.8%Top
- Solar Pro 3: 10.3%
GPQA Diamond
Graduate-level science questions
- Solar Pro 4 Thinking: 89.1%Top
- Solar Pro 3: 72.4%
IFBench
Following precise output instructions
- Solar Pro 4 Thinking: —
- Solar Pro 3: 71.2%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Solar Pro 4 Thinking: 0.0%Top
- Solar Pro 3: 0.0%Top
SciCode
Scientific computing in Python
- Solar Pro 4 Thinking: 48.0%Top
- Solar Pro 3: 25.5%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Solar Pro 4 Thinking: —
- Solar Pro 3: 7.6%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Solar Pro 4 Thinking: —
- Solar Pro 3: 86.3%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Solar Pro 4 Thinking: 70.7%Top
- Solar Pro 3: 32.3%
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.
- Prompt cache hits
- 19.1%
- About $0.0254 per 1M input tokens with caching
- Request success (24h)
- 99.5%
- 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.
- 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.
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:thinking",
"reasoning_effort": "medium",
"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:thinking",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)upstage
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