Upstage の Solar Pro は、最先端のエンタープライズ推論、ソフトウェア工学、ミッションクリティカルな本番運用向けに設計されたAIモデルです。33K のコンテキストウィンドウ、毎秒 100 トークンの生成速度、知能指数 75/100（1Mトークンあたり入力$0.25・出力$0.25）を実現しています。
Technical Specifications
- Provider
- Upstage
- Category
- flagship
- Release Date
- 2024-10
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- API Pay-as-you-go
- Reasoning Effort Control
- Fixed
- Structured Outputs
- Yes
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- solar-pro
- Supported SDK & API Protocol
- Upstage REST API (OpenAI-Compatible)
- Lifecycle & Deprecation Status
- Legacy Stable (Upgrade path available in Upstage lineup)
- Production Rate Limits (RPM & TPM)
- 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM
- Long-Context Pricing Tier (>128K / >200K)
- Flat rate ($0.25/1M in) across full 33K window
- Prompt Cache Write & TTL Policy
- Cached input at $0.025/1M tokens
- Computer Use & Browser GUI Agent
- API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
- MCP & Parallel Tool Calling
- Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
- Web Search Grounding & Code Sandbox
- Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
- Fine-Tuning & Distillation Support
- API Prompt Engineering & RAG Distillation
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token)
- Weights Precision & Quantization
- Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster)
- Minimum GPU VRAM Requirement
- Zero Local VRAM Required (100% Serverless Cloud API)
- Supported Inference Engines
- Managed Upstage Cloud API
- System Card & Safety Framework
- Upstage Production Safety & Alignment Verified
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Solar Pro Cost, Context, Hardware & API Integration
Pay-as-you-go API is cheaper for this volume (saves $8.00/mo vs $20 flat plan).
Break-even point: ~833 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to Solar Pro:
Benchmark Scores & 6-Axis Capability Radar
- MMLU-Pro
- 73.5%
- HumanEval
- 81%
- Chatbot Arena Elo
- 1260pts
Strengths
- 33K のコンテキストウィンドウと最大 4K トークンの出力容量（MMLU-Pro 73.5% · Arena Elo 1260）
- 毎秒 100 トークンの高速スループットと、初回トークン到達時間（TTFT）わずか 380ms の低遅延
- 優れたAPI経済性（1Mトークンあたり入力$0.25・出力$0.25）に加え、プロンプトキャッシュや構造化JSON出力・関数呼び出しに完全対応
Limitations & Trade-offs
- クラウド専用のプロプライエタリモデルのため、モデル重みをダウンロードしてオフライン実行することはできません
- 極めて高度な専門科学の証明問題では、上位の大型推論特化モデルの方がより深い洞察を提供する場合があります
Editorial Assessment
知能指数 75/100、33K コンテキスト、毎秒 100 トークンの速度を兼ね備えた Solar Pro は、Upstage のラインナップにおいて非常に実用性の高い主力モデルです。
Best for: 最先端のエンタープライズ推論、ソフトウェア工学、ミッションクリティカルな本番運用、エンタープライズRAG基盤、スケーラブルな本番API統合に最適。
Compare Solar Pro
Frequently Asked Questions about Solar Pro
How much does the Solar Pro API cost per 1M tokens?+
Solar Pro by Upstage is priced at $0.25 per 1M input tokens and $0.25 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.025 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the Solar Pro pay-as-you-go API?+
A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.
How many words and pages fit in Solar Pro's context window?+
Solar Pro features a 33K tokens context window, which equals approximately 24,576 English words or ~66 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 4,096 tokens.
Can I run Solar Pro locally on my own GPU (Open Weights)?+
No, Solar Pro is a proprietary closed-weights model hosted by Upstage. It cannot be downloaded for local GPU execution and must be accessed via Upstage's official API or cloud platform.
Does Upstage train on data sent to the Solar Pro API, and is commercial use allowed?+
API payloads are excluded from model training by default. License tier: Proprietary Commercial API (Upstage Terms). Full commercial ownership of generated outputs. Supported deployment channels include: Upstage Cloud API & Enterprise Endpoints.
How does Solar Pro perform on coding and reasoning benchmarks?+
Solar Pro achieves a composite Intelligence Index of 75/100, scoring N/A% on SWE-bench Verified, N/A% on GPQA Diamond, 73.5% on MMLU-Pro, and 1260 pts on Chatbot Arena Elo.
What is Solar Pro best used for?+
Solar Pro is best suited for: 最先端のエンタープライズ推論、ソフトウェア工学、ミッションクリティカルな本番運用、エンタープライズRAG基盤、スケーラブルな本番API統合に最適。. Assessment: 知能指数 75/100、33K コンテキスト、毎秒 100 トークンの速度を兼ね備えた Solar Pro は、Upstage のラインナップにおいて非常に実用性の高い主力モデルです。
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to Solar Pro:
The basic unit of text that a language model processes, typically representing about 3 to 4 English characters or roughly 0.75 words. For example, the sentence "Artificial intelligence is fast" breaks down into about 5 tokens.
A standardized evaluation suite used to objectively measure and rank an AI model's capabilities across specific tasks — such as SWE-bench Verified for software engineering, AIME for competitive math, or MMLU for general knowledge.
The maximum number of tokens a model can consider at once — both the input it reads and the output it writes. A 1,000,000-token context window can hold roughly 750,000 English words in a single request.
The ability of a language model to recognize when an external capability is needed and output structured JSON arguments to invoke external APIs, databases, or terminal commands. The runtime executes the tool and passes results back to the model.
An open standard created by Anthropic that allows AI applications and agents to connect seamlessly to local filesystems, development environments, and third-party APIs via standardized server interfaces.
A cost and latency optimization where inference providers store pre-computed attention states for repeated prompt prefixes. Reusing cached tokens typically slashes API input costs by 50% to 90% and cuts TTFT substantially.
Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.