Solar Pro 4
Upstage · released Aug 10, 2026
Solar Pro 4 is Upstage's cost-efficient large language model, featuring a 524K context window. It is built for long-horizon tasks and agentic workflows, with strong capabilities in office productivity, document-intensive...
Specification
- Context window
- 524K
- Max output
- 131K
- Knowledge cutoff
- Not stated
- Parameters
- Undisclosed
- Licence
- Proprietary
- Serving providers
- 1
- Moderated
- No
- Uptime
- 100.0%
Intelligence
28.2
81th percentile
Coding
52.7
Coding Index
Agentic
—
Agentic Index
Output speed
68 t/s
Median across providers
Latency
672ms
Time to first token
Cost per task
$0.03
Estimated
Benchmarks
Where the score comes from
The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.
Evaluation scores
Percentage correct · higher is better
- GPQA Diamond89.1%
- AA-LCR (long context)74.0%
- SciCode44.6%
- Humanity's Last Exam29.2%
- τ²-bench (Telecom)23.3%
An evaluation missing from this list was not run for this model — it is not a zero.
View as table
| Evaluation | Score |
|---|---|
| GPQA Diamond | 89.1% |
| AA-LCR (long context) | 74.0% |
| SciCode | 44.6% |
| Humanity's Last Exam | 29.2% |
| τ²-bench (Telecom) | 23.3% |
Against its peers
Intelligence Index · this model highlighted, nearest peers in grey
- Gemini 3.1 Pro PreviewGoogle29.7
- Qwen3.7 MaxQwen29.5
- MiniMax M3MiniMax29.2
- GPT-5.2-CodexOpenAI28.5
- Solar Pro 4Upstage28.2
- GLM 5Z.ai27.9
- Kimi K2.6Moonshot AI27.0
- Qwen3.6 PlusQwen27.0
Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.
View as table
| Model | Intelligence |
|---|---|
| Gemini 3.1 Pro Preview | 29.7 |
| Qwen3.7 Max | 29.5 |
| MiniMax M3 | 29.2 |
| GPT-5.2-Codex | 28.5 |
| Solar Pro 4 | 28.2 |
| GLM 5 | 27.9 |
| Kimi K2.6 | 27.0 |
| Qwen3.6 Plus | 27.0 |
Percentile among all indexed models
Pricing
What it costs to run
List prices per million tokens, plus what one representative task works out to.
List price
- Input / 1M tokens
- $0.09
- Output / 1M tokens
- $0.36
- Cached input / 1M
- $0.018
- Blended 3:1
- $0.158
One task, estimated
$0.03
- Input tokens
- 50,000
- Output tokens
- 80,000
- Profile
- Reasoning
Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).
Serving providers
Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.