upstage · Efficient
Solar Pro 4
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.
| Solar Pro 4upstageThis model | GLM 5 TurboZ.aiRemove | |
|---|---|---|
| Provider | upstage | Z.ai |
| Discovery tier | Efficient | Open weights |
| Added | Aug 11, 2026 | Mar 15, 2026 |
| Limits | ||
| Context window | 524.29KBest | 202.8K |
| Max output | 131.07K | 131.07K |
| Average output | 546 tokens | 557 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.03Best | $1.20 |
| Output | $0.12Best | $4.00 |
| Cache read | $0.006Best | $0.24 |
| Performance | ||
| Throughput | 101.4 tok/s | — |
| Time to first token | 3.1 s | — |
| Request success (24h) | 99.9% | 100.0%Best |
| Benchmark indexes | ||
| Intelligence Index | 26.6 | 26.6 |
| Capabilities | ||
| Tools | Yes | Yes |
| Structured output | Yes | Yes |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Solar Pro 4
- GLM 5 Turbo
Intelligence Index
- Solar Pro 426.6
- GLM 5 Turbo26.6
Solar Pro 4: Better than 67% of 326 scored models
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Solar Pro 4: 13.6%
- GLM 5 Turbo: —
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Solar Pro 4: 2.4%
- GLM 5 Turbo: —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Solar Pro 4: 1,093 Elo
- GLM 5 Turbo: —
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Solar Pro 4: 1,106 Elo
- GLM 5 Turbo: —
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Solar Pro 4: 7.0%
- GLM 5 Turbo: —
AA-LCRv1.1
Reasoning across long documents
- Solar Pro 4: 70.7%
- GLM 5 Turbo: 71.7%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Solar Pro 4: 29.8%Top
- GLM 5 Turbo: 27.8%
GPQA Diamond
Graduate-level science questions
- Solar Pro 4: 89.1%Top
- GLM 5 Turbo: 84.7%
IFBench
Following precise output instructions
- Solar Pro 4: —
- GLM 5 Turbo: 73.2%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Solar Pro 4: 0.0%
- GLM 5 Turbo: —
SciCode
Scientific computing in Python
- Solar Pro 4: 48.0%
- GLM 5 Turbo: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Solar Pro 4: —
- GLM 5 Turbo: 33.3%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Solar Pro 4: —
- GLM 5 Turbo: 98.5%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Solar Pro 4: 70.7%
- GLM 5 Turbo: 71.7%Top
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.
- 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",
"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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