Solar Pro vs Grok 2
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Solar Pro by Upstage and Grok 2 by xAI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Solar Pro holds a notable pricing advantage for token ingestion. On output generation, Solar Pro is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Grok 2 provides an expanded memory horizon with 131K tokens. In latency-sensitive production environments, Solar Pro leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
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Solar Pro
フラッグシップ最先端モデルUpstage が提供する Solar Pro は、最大 32K トークンのコンテキストウィンドウを備え、入力 $0.25/100万トークン・出力 $0.25/100万トークンで利用可能な、コーディング・推論・業務自動化向け AI モデルです。
$0.25 / 1M
$0.25 / 1M
32.8K tokens
N/A
Grok 2
フラッグシップ最先端モデルxAI が提供する Grok 2 は、最大 131K トークンのコンテキストウィンドウを備え、入力 $2/100万トークン・出力 $10/100万トークンで利用可能な、コーディング・推論・業務自動化向け AI モデルです。
$2.00 / 1M
$10.00 / 1M
131.1K tokens
36.5%
ひと目でわかる主な違い
- Solar Pro is 21.2x cheaper for API usage (input + output tokens combined).
- Grok 2 has a larger context window (131K vs 33K tokens).
- Solar Pro is faster at 100 tok/s vs 85 tok/s.
| Feature | Solar Pro | Grok 2 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 75 | 45 |
Provider | Upstage | xAI |
Input Price Cost per million input tokens | $0.25 / 1M | $2.00 / 1M |
Output Price Cost per million output tokens | $0.25 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.09 / 1M | $2.10 / 1M |
Context Window Maximum input + output tokens | 32.8K tokens~49 A4 pages of text | 131.1K tokens~197 A4 pages of text |
Max Output Tokens Per single request | 4K | 8K |
Throughput Speed Tokens generated per second | 100 tok/s | 85 tok/s |
SWE-bench Verified Real-world software engineering | N/A | 36.5% |
GPQA Diamond Graduate-level reasoning | N/A | 56% |
Cached Input Price Prompt caching discount per 1M tokens | $0.03 / 1M | $1.00 / 1M |
分野別勝者スコアカード
At-a-glance decision frameworkEvaluations ongoing
検証済みベンチマークスコア比較
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Tokens emitted per second during active generation streaming.
レイテンシ＆応答時間
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
リアルタイムAPIトークン料金シミュレーター
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Solar Pro · Strengths & Key Advantages
- Upstage の高度な Depth-Upscaled Dense Language Transformer アーキテクチャと 32K トークンのコンテキスト処理能力
- 優れたコストパフォーマンス（入力 $0.25/1M、出力 $0.25/1M）と安定した応答速度
- プログラミング、論理的推論、多言語タスクにおいて高いベンチマーク精度を実現
Considerations & Trade-offs
- 大規模な長文コンテキスト処理時はトークン消費量の最適化が必要
- 専門領域のタスクでは適切なプロンプト設計や RAG の併用が推奨される
Grok 2 · Strengths & Key Advantages
- xAI の高度な Frontier Multimodal Mixture-of-Experts アーキテクチャと 131K トークンのコンテキスト処理能力
- 優れたコストパフォーマンス（入力 $2/1M、出力 $10/1M）と安定した応答速度
- プログラミング、論理的推論、多言語タスクにおいて高いベンチマーク精度を実現
Considerations & Trade-offs
- 大規模な長文コンテキスト処理時はトークン消費量の最適化が必要
- 専門領域のタスクでは適切なプロンプト設計や RAG の併用が推奨される
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Solar Pro | Grok 2 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.04 | $0.20 |
Output Tokens / Task Tokens generated per task | 10K | 24K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
技術仕様・スペック
Architecture, release timeline, capabilities, and modalities.
| Feature | Solar Pro | Grok 2 |
|---|---|---|
| Official API Model ID (SDK) | solar-pro | grok-2-latest |
| API Protocol | Upstage REST API (OpenAI-Compatible) | xAI REST API (OpenAI-Compatible) |
| Release Date | 2024-10 | 2024-08 |
| Knowledge Cutoff | June 2024 | August 2024 |
| Architecture | Depth-Upscaled Dense Language Transformer | Frontier Multimodal Mixture-of-Experts |
| Parameters | 22B (Depth-Upscaled) | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($0.25/1M in) across full 33K window | Flat rate ($2/1M in) across full 131K window |
| Prompt Cache Policy & TTL | Cached input at $0.025/1M tokens | Cached input at $1/1M tokens |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | 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 | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Real-time Web & X (Twitter) Search Grounding + Code Execution |
| Official Fine-Tuning Support | API Prompt Engineering & RAG Distillation | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) |
| Quantization & Min GPU VRAM | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) | Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API) |
| Safety & Frontier Classification | Upstage Production Safety & Alignment Verified | xAI Production Safety & Alignment Verified |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier | SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier |
| Input Modalities | text | text, vision |
| Output Modalities | text | text |
Solar Pro vs Grok 2: よくある質問 (FAQ)
Which is more intelligent, Solar Pro or Grok 2?
Solar Pro is more intelligent. It scores 75 compared with 45 on the composite Intelligence Index.
Which model is faster?
Solar Pro is faster, generating 100 tokens per second compared with 85 tokens per second.
Which model is cheaper to run?
Solar Pro is cheaper at $0.09 per 1M tokens blended, compared with $2.10 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Solar Pro has lower latency, with a time to first token of 0.38s compared with 0.48s.
Which model has a larger context window?
Grok 2 has a larger context window, supporting 131.1K tokens compared with 32.8K tokens.
総合評価
Verdict & Model Selection Recommendation: Choose Solar Pro if your priority is Korean enterprise applications, customer service bots, and specialized legal translation. Its performance in demanding tasks justifies its operational token cost. Choose Grok 2 if your workflow prioritizes Real-time trending news synthesis, visual STEM reasoning, and interactive X applications. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
よくある質問 (FAQ)
How does Solar Pro compare to Grok 2 in API token pricing and cost per token?+
Solar Pro costs $0.25 per 1M input tokens and $0.25 per 1M output tokens, whereas Grok 2 costs $2.00 input and $10.00 output. Overall, Solar Pro is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Solar Pro or Grok 2?+
Solar Pro supports a context window of 33K tokens (~25k words), while Grok 2 supports 131K tokens (~98k words). Therefore, Grok 2 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Solar Pro or Grok 2?+
Solar Pro scores at the frontier of coding benchmarks, while Grok 2 scores 36.5%. For complex autonomous debugging and agentic engineering, Grok 2 provides robust code generation and tool calling.
What is the difference in reasoning capability and extended thinking between Solar Pro and Grok 2?+
Solar Pro is optimized for low-latency direct generation. In contrast, Grok 2 focuses on standard fast inference.
How does inference speed (tokens per second) compare between Solar Pro and Grok 2?+
Solar Pro generates approximately 100 tokens per second, while Grok 2 delivers 85 tokens per second. In latency-sensitive production environments, Solar Pro provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Solar Pro and Grok 2 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Solar Pro to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Grok 2. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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.
公的ソース: GetInfoUs Independent AI Benchmarks & Official API Specs