Claude Sonnet 4 vs o1-pro
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Claude Sonnet 4 by Anthropic and o1-pro by OpenAI 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, Claude Sonnet 4 holds a notable pricing advantage for token ingestion. On output generation, Claude Sonnet 4 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 200K tokens. In latency-sensitive production environments, Claude Sonnet 4 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.
किसी भी मॉडल को बदलें और तुलना करें
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Claude Sonnet 4
डीप रीजनिंग मॉडलAnthropic द्वारा विकसित Claude Sonnet 4 एक उन्नत AI मॉडल है, जिसमें 200K टोकन का कॉन्टेक्स्ट विंडो और $3/1M इनपुट तथा $15/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$3.00 / 1M
$15.00 / 1M
200K tokens
72.7%
o1-pro
डीप रीजनिंग मॉडलOpenAI द्वारा विकसित o1-pro एक उन्नत AI मॉडल है, जिसमें 200K टोकन का कॉन्टेक्स्ट विंडो और $150/1M इनपुट तथा $600/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$150.00 / 1M
$600.00 / 1M
200K tokens
51.5%
एक नज़र में मुख्य अंतर
- Claude Sonnet 4 is 44.5x cheaper for API usage (input + output tokens combined).
- Claude Sonnet 4 is faster at 85 tok/s vs 22 tok/s.
- Claude Sonnet 4 leads on SWE-bench coding (72.7% vs 51.5%).
| Feature | Claude Sonnet 4 | o1-pro |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 58 | 57 |
Provider | Anthropic | OpenAI |
Input Price Cost per million input tokens | $3.00 / 1M | $150.00 / 1M |
Output Price Cost per million output tokens | $15.00 / 1M | $600.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.31 / 1M | $116.25 / 1M |
Context Window Maximum input + output tokens | 200K tokens~300 A4 pages of text | 200K tokens~300 A4 pages of text |
Max Output Tokens Per single request | 64K | 100K |
Throughput Speed Tokens generated per second | 85 tok/s | 22 tok/s |
SWE-bench Verified Real-world software engineering | 72.7% | 51.5% |
GPQA Diamond Graduate-level reasoning | 71.2% | 79% |
Cached Input Price Prompt caching discount per 1M tokens | $0.30 / 1M | $37.50 / 1M |
किस क्षेत्र में कौन आगे है?
At-a-glance decision frameworkसत्यापित बेंचमार्क स्कोर तुलना
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.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
लेटेंसी और रिस्पॉन्स समय
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
रियल-टाइम टोकन लागत सिम्युलेटर
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Claude Sonnet 4 · Strengths & Key Advantages
- Anthropic की उन्नत Hybrid Multimodal Reasoning Transformer आर्किटेक्चर और 200K कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($3/1M इनपुट, $15/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
- जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
- बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
- विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है
o1-pro · Strengths & Key Advantages
- OpenAI की उन्नत High-compute reasoning transformer आर्किटेक्चर और 200K कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($150/1M इनपुट, $600/1M आउटपुट) तेज़ रिस्पॉन्स के साथ
- जटिल कोडिंग, तार्किक विश्लेषण और बहुभाषी कार्यों में उच्च सटीकता
Considerations & Trade-offs
- बड़े पैमाने पर लंबे कॉन्टेक्स्ट प्रॉम्प्ट्स के लिए टोकन बजट प्रबंधन आवश्यक है
- विशिष्ट डोमेन कार्यों में सर्वोत्तम परिणाम के लिए सटीक प्रॉम्प्ट इंजीनियरिंग की आवश्यकता होती है
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Claude Sonnet 4 | o1-pro |
|---|---|---|
Cost per Task Estimated USD to finish one task | $3.29 | $94.20 |
Output Tokens / Task Tokens generated per task | 72K | 62K |
Reasoning Tokens / Task Thinking tokens burned per task | 37K | 45K |
तकनीकी विशिष्टताएँ (Specs)
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude Sonnet 4 | o1-pro |
|---|---|---|
| Official API Model ID (SDK) | claude-sonnet-4-20250501 | o1-pro |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-05 | 2025-03 |
| Knowledge Cutoff | March 2025 | October 2023 |
| Architecture | Hybrid Multimodal Reasoning Transformer | High-compute reasoning transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($150/1M in) across full 200K window |
| Prompt Cache Policy & TTL | $0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL | Automatic prefix caching at $37.5/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | Supported (Screen coordinate grounding, browser & desktop GUI action loops) |
| 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 | Native Web Search Citations + Code Execution Tool + MCP Connectors | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Custom Model Tuning via Amazon Bedrock & Prompt Distillation | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | 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 | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated | OpenAI Preparedness Framework Audited & System Card Published |
| 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, vision | text, vision |
| Output Modalities | text | text |
Claude Sonnet 4 vs o1-pro: त्वरित प्रश्नोत्तर (FAQ)
Which is more intelligent, Claude Sonnet 4 or o1-pro?
Claude Sonnet 4 is more intelligent. It scores 58 compared with 57 on the composite Intelligence Index.
Which model is faster?
Claude Sonnet 4 is faster, generating 85 tokens per second compared with 22 tokens per second.
Which model is cheaper to run?
Claude Sonnet 4 is cheaper at $2.31 per 1M tokens blended, compared with $116.25 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Claude Sonnet 4 has lower latency, with a time to first token of 0.52s compared with 4.20s.
निष्कर्ष
Verdict & Model Selection Recommendation: Choose Claude Sonnet 4 if your priority is Full-stack software engineering agents, CI/CD pipeline automation, and enterprise production applications. Its performance in demanding tasks justifies its operational token cost. Choose o1-pro if your workflow prioritizes Rare, high-stakes analytical problems where cost is irrelevant. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
अक्सर पूछे जाने वाले प्रश्न (FAQ)
How does Claude Sonnet 4 compare to o1-pro in API token pricing and cost per token?+
Claude Sonnet 4 costs $3.00 per 1M input tokens and $15.00 per 1M output tokens, whereas o1-pro costs $150.00 input and $600.00 output. Overall, Claude Sonnet 4 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: Claude Sonnet 4 or o1-pro?+
Both Claude Sonnet 4 and o1-pro offer an identical context window of 200K tokens (~150k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: Claude Sonnet 4 or o1-pro?+
Claude Sonnet 4 scores 72.7% on SWE-bench Verified while o1-pro scores 51.5%. For autonomous software engineering and multi-file debugging, Claude Sonnet 4 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Claude Sonnet 4 and o1-pro?+
Claude Sonnet 4 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, o1-pro provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Claude Sonnet 4 and o1-pro?+
Claude Sonnet 4 generates approximately 85 tokens per second, while o1-pro delivers 22 tokens per second. In latency-sensitive production environments, Claude Sonnet 4 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Claude Sonnet 4 and o1-pro to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Claude Sonnet 4 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to o1-pro. 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.
स्रोत: GetInfoUs Independent AI Benchmarks & Official API Specs