upstage
Upstage: Solar Pro 4
upstage/solar-pro4
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to the OpenRouter catalog, upstage/solar-pro4 (listed as Upstage: Solar Pro 4, canonical snapshot upstage/solar-pro4-20260810) is a text-only large language model positioned as cost-efficient, offering a 524K-token context window described as suited to long-horizon tasks and agentic workflows. The catalog reports optional reasoning, disabled by default with several configurable effort levels, plus support for tool calling, parallel tool calls, structured outputs, and standard sampling parameters. Arena and index measurements exist in the structured data, but an independent model card was not available in this source pack, so real-world behavior warrants validation on target workloads.[1]
Strengths
- Large 524K-token context window per the catalog listing, suited to long documents and extended sessions.[1]
- Optional reasoning with configurable effort levels, disabled by default, allowing latency and cost trade-offs.[1]
- Supports tool calling, parallel tool calls, structured outputs, and response formatting per the catalog's parameter list.[1]
Limitations
Where to use it
- A reasonable candidate to evaluate for agentic workflows that combine tool calling and structured outputs, per the catalog description.[1]
- Worth testing for document-intensive, long-context tasks such as summarizing or querying large files, given the listed context window.[1]
- May fit cost-sensitive office productivity assistants, a capability area named in the catalog description, subject to workload validation.[1]
Sources
- [1] OpenRouter catalog · Upstage: Solar Pro 4Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
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...
Specifications
- Model ID
- upstage/solar-pro4
- Canonical ID
- upstage/solar-pro4-20260810
- Creator
- upstage
- Added to OpenRouter
- 10.08.2026
- Context length
- 524,288
- Modality
- text->text
- Input modalities
- text
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.150 / out $0.600
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | BB — next 30% of the cohort | reasoning: optional · default medium · efforts: max, xhigh, high, medium, low, minimal, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | BB — next 30% of the cohort | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: optional · default medium · efforts: max, xhigh, high, medium, low, minimal, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | — |
| Vision | No measurement | — |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Intelligence index | 28.2 | BB — next 30% of the cohort | 13.11.2026 |
| Artificial Analysis | Coding index | 52.7 | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · webappswin rate 30% · rank 40 | 1,087Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · 3dwin rate 46.8% · rank 65 | 1,162Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 38.8% · rank 71 | 1,171Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · datavizwin rate 41.3% · rank 68 | 1,175Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 40.9% · rank 68 | 1,169Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 35.5% · rank 86 | 1,140Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · websitewin rate 36.8% · rank 85 | 1,164Elo | CC — below the B band | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Upstage | 524,288 | $0.150 | $0.600 | — | — | 100% |
| Upstage | 524,288 | $0.150 | $0.600 | — | — | 100% |
| KT | 524,288 | $0.300 | $1.2 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.