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 | Nvidia Nemotron 3.5 Super VLnvidiaRemove | |
|---|---|---|
| Provider | upstage | nvidia |
| Discovery tier | Efficient | Open weights |
| Added | Aug 11, 2026 | Oct 15, 2026 |
| Limits | ||
| Context window | 524.29KBest | 262.14K |
| Max output | 131.07KBest | 16.38K |
| Average output | 1.7K tokens | 1.1K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.03Best | $0.15 |
| Output | $0.12Best | $0.50 |
| Cache read | $0.006Best | $0.02 |
| Performance | ||
| Throughput | — | 654.7 tok/s |
| Time to first token | — | 1.8 s |
| Request success (24h) | 99.6%Best | 98.0% |
| Benchmark indexes | ||
| Intelligence Index | 26.6Best | 26.5 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | No | Yes |
| Structured output | Yes | Yes |
| Video input | No | Yes |
| Reasoning effort | none, low, medium, high | none, medium, high |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Solar Pro 4 Thinking
- Nvidia Nemotron 3.5 Super VL
Intelligence Index
- Solar Pro 4 Thinking26.6
- Nvidia Nemotron 3.5 Super VL26.5
Solar Pro 4 Thinking: Better than 67% of 326 scored models
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Solar Pro 4 Thinking: 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 Thinking: 2.4%Top
- Nvidia Nemotron 3.5 Super VL: 2.0%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Solar Pro 4 Thinking: 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 Thinking: 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 Thinking: 7.0%
- Nvidia Nemotron 3.5 Super VL: 8.0%Top
AA-LCRv1.1
Reasoning across long documents
- Solar Pro 4 Thinking: 70.7%Top
- Nvidia Nemotron 3.5 Super VL: 69.0%
MLCR-AA
Long-context reasoning over medical records
- Solar Pro 4 Thinking: —
- Nvidia Nemotron 3.5 Super VL: 13.3%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Solar Pro 4 Thinking: 29.8%
- Nvidia Nemotron 3.5 Super VL: 30.7%Top
GPQA Diamond
Graduate-level science questions
- Solar Pro 4 Thinking: 89.1%
- Nvidia Nemotron 3.5 Super VL: —
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Solar Pro 4 Thinking: 0.0%Top
- Nvidia Nemotron 3.5 Super VL: 0.0%Top
SciCode
Scientific computing in Python
- Solar Pro 4 Thinking: 48.0%Top
- Nvidia Nemotron 3.5 Super VL: 47.8%
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Solar Pro 4 Thinking: 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.
- 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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