Upstage (Solar) (Upstage (Solar))
综合排名 #30 ⭐ 可考虑
⚠️ 需代理 / 经 OpenRouter;支持本地与专用部署 | 🌍 国际
💰 Token 价格
| 类型 | 价格 | 备注 |
|---|---|---|
| 输入 (Input) | Solar Pro 4: $0.30/M list (促销: 90% off = $0.03/M 至 2026-09-10, 70% off = $0.09/M 至 2026-10-10); Solar Pro 3 / Pro 2: $0.15/M | 每百万 tokens |
| 输出 (Output) | Solar Pro 4: $1.20/M list (促销 $0.12/M → $0.36/M); 缓存输入 $0.06/M 标价 ($0.006 → $0.018 促销); Solar Pro 3 / Pro 2: $0.60/M | 每百万 tokens |
💡 免费额度
Studio 智能体 10 次免费运行(无需信用卡)
🤖 支持模型(共 6 个)
Solar Pro 4 (agentic flagship, 512K ctx, 128K max output, $0.30/$1.20; 90% off thru Sep 10 2026, 70% off thru Oct 10) Solar Pro 3 (previous-gen flagship, 128K ctx, $0.15/$0.60) Solar Pro 2 (enterprise reasoning, 128K ctx, $0.15/$0.60) Solar Mini (lightweight cost-efficient tier) Syn Pro (locally trained for the Japanese market) Solar Open 2 (open-weights sibling, self-hostable — distinct from the Pro 4 API)
✨ 优势
- ✓ Solar Pro 4:512K 上下文 / 128K 输出的智能体模型,2026 年 8 月发布
- ✓ 发布促销 9 月 10 日前 90% 折扣($0.03/$0.12 每百万),10 月 10 日前 70%
- ✓ OpenAI 兼容 API,迁移仅需更换端点与模型名 solar-pro4
- ✓ 英/韩/日三语输入输出;推理力度可调(高低两档)
- ✓ 文档 AI 按页计费:Parse $0.01/页、Extract $0.03/页、Classify 免费
- ✓ SOC 2 + ISO 27001 认证;AWS / Azure / Snowflake 市场上架
⚠️ 不足
- × 促销价与标价随日期切换,定价页脚本按阶段替换显示,易误读
- × 所有价格不含 10% 增值税
- × 无中国大陆边缘节点,需代理或经 OpenRouter
- × AIME 2026(95.3 对 95.7)与日语 IFEval(81.6 对 82.5)相对 Solar Open 2 略降
- × Solar Pro 4 不自托管(自托管需选 Solar Open 2)
🎯 适合场景
文档密集型、多步骤的智能体流水线:跨多份合同评审、在报告间核对数字、按政策筛选候选方案,以及任何错误数值会传播进下游交付物的场景;需要韩语/日语支持的团队;想在编译前用极低价评测前沿级长上下文模型的开发者。
💰 价格与方案
| 模型 | 输入 /百万 | 缓存 /百万 | 输出 /百万 | 备注 |
|---|---|---|---|---|
| Solar Pro 4 | $0.30(促销 $0.03) | $0.06(促销 $0.006) | $1.20(促销 $0.12) | 512K 上下文 / 128K 输出;2026-09-10 前 90% 折扣,10-10 前 70% 折扣 |
| Solar Pro 3 | $0.15 | $0.015 | $0.60 | 128K 上下文;上一代旗舰 |
| Solar Pro 2 | $0.15 | $0.015 | $0.60 | 128K 上下文;企业级推理 |
| Solar Mini | 定价页已公布 | — | 定价页已公布 | 轻量、成本友好档 |
| Syn Pro | 定价页已公布 | — | 定价页已公布 | 面向日本市场本地化训练 |
| Document Parse | $0.01/页(Standard)· $0.03/页(Enhanced) | — | — | 结构化、可被 LLM 读取的抽取 |
| Information Extract | $0.03/页(Standard)· $0.05/页(Enhanced) | — | — | 从非结构化文本抽取关键字段 |
| Classify / Instruct | 免费(Beta) | — | — | 文档分类与自定义自然语言 LLM 步骤 |
🔧 API 与开发者体验
- •OpenAI-Compatible Base URL: Solar Pro 4 is exposed through an OpenAI-compatible chat completions interface under the model name solar-pro4. If your stack already speaks the OpenAI protocol, the entire migration is the base URL plus the model string — no new SDK, no bespoke request format.
- •Reasoning by Default: Solar Pro 4 reasons by default and the response carries the reasoning trace, so the mental model is closer to a reasoning model than a classic completion endpoint. Handle the trace in your client.
- •Adjustable Reasoning Effort: Response speed is a dial rather than a fixed property: high reasoning effort favours deep analysis, low targets real-time interaction at what Upstage calls everyday-chatbot speed. For agent loops calling the model dozens of times per job, this is the main cost and latency lever.
- •Context Window: 512K-token input context with up to 128K output tokens — enough to load several contracts, reports, and data files into a single session without splitting them. OpenRouter lists the context at 524,288.
- •Languages: English, Korean, and Japanese for both input and output. Japanese-specific instruction-following (IFEval JA 81.6) is marginally behind the open-weights sibling (82.5).
- •Distribution: Upstage Console (primary API), SolarChat (free browser playground, no key), OpenRouter (upstage/solar-pro4), Hermes Agent, Upstage Studio (no-code document agents), and dedicated / on-premises deployment.
- •Compliance & Procurement: Upstage operates under SOC 2 and ISO 27001 certification; models are also available on AWS, Azure, and Snowflake marketplaces for buyers who procure through a cloud account rather than a new vendor relationship.
📊 基准测试(Solar Pro 4 对 Solar Open 2)
| 类别 | 基准 | Solar Open 2 | Solar Pro 4 | 差值 |
|---|---|---|---|---|
| 智能体执行 | Terminal-Bench v2.1 | 43.2 | 57.0 | +13.8 |
| 智能体执行 | GDPval-AA v2 | 31.4 | 38.8 | +7.4 |
| 智能体执行 | BrowseComp* | 37.3 | 49.2 | +11.9 |
| 智能体执行 | SWE-Bench Verified (OpenHands)* | 69.2 | 70.6 | +1.4 |
| 智能体执行 | MCP-Atlas* | 58.2 | 61.4 | +3.2 |
| 智能体执行 | APEX-Agents* | 16.6 | 18.7 | +2.1 |
| 智能体执行 | t3-Banking | 18.1 | 23.0 | +4.9 |
| 长文档 | AA-LCR | 62.7 | 71.0 | +8.3 |
| 知识 / 推理 / 编程 | GPQA Diamond | 85.6 | 89.0 | +3.4 |
| 知识 / 推理 / 编程 | MMLU-Pro* | 86.2 | 86.3 | +0.1 |
| 知识 / 推理 / 编程 | LiveCodeBench* | 87.0 | 87.8 | +0.8 |
| 知识 / 推理 / 编程 | AIME 2026* | 95.7 | 95.3 | -0.4 |
| 韩日工作负载 | KMMLU-Pro* | 78.4 | 79.2 | +0.8 |
| 韩日工作负载 | KBL(法律)* | 75.5 | 77.5 | +2.0 |
| 韩日工作负载 | KorMedMCQA(医学)* | 93.0 | 93.2 | +0.2 |
| 韩日工作负载 | Ko-GDPval* | 86.8 | 87.3 | +0.5 |
| 韩日工作负载 | Arena-Hard v2(日语)* | 75.3 | 81.9 | +6.6 |
| 韩日工作负载 | MMLU(日语)* | 89.5 | 89.5 | +0.2 |
| 韩日工作负载 | IFEval(日语)* | 82.5 | 81.6 | -0.9 |
🎯 适用场景与结论
- •Choose Solar Pro 4 if…: your workload is genuinely multi-step and document-heavy: contract review across several files, reconciling figures between reports, screening candidates against a policy, or any pipeline where a wrong value propagates into a downstream deliverable. The 512K context removes the need to split document sets, and the model's trained habit of flagging what it cannot verify is exactly the property you want where a hallucinated number is expensive.
- •Be careful if…: your work is math-heavy or Japanese-instruction-sensitive — AIME 2026 and Japanese IFEval are essentially flat or slightly down versus Solar Open 2, so the agentic uplift does not generalise automatically. And if you need to self-host for data-residency reasons, Solar Pro 4 is the wrong choice by design; look at Solar Open 2.
- •Watch the calendar: The 90%-off phase ends September 10, 2026 at 23:59 UTC and steps down to 70% off on September 11 before reverting to standard pricing on October 11. The same tokens cost roughly 3x more three days later and 10x more five weeks later. That is the published price schedule, not artificial urgency.
- •Work agents & cookbook: Upstage shipped seven work agents alongside the model (Excel workbook generation, evidence-based Word reports, PowerPoint decks with speaker notes), each with its system prompt, actual outputs, and pass criteria, plus a full English worked assignment so you can run the same job yourself rather than trusting a demo.