Claude 3.7 Sonnet vs o3-mini
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Claude 3.7 Sonnet by Anthropic and o3-mini 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, o3-mini holds a notable pricing advantage for token ingestion. On output generation, o3-mini 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, o3-mini 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.
İstediğiniz Modelleri Seçin ve Karşılaştırın
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Claude 3.7 Sonnet
Derin Akıl Yürütme ModeliAnthropic tarafından geliştirilen Claude 3.7 Sonnet, 200K token bağlam penceresi ve 1M girdi başına $3, 1M çıktı başına $15 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.
$3.00 / 1M
$15.00 / 1M
200K tokens
70.3%
o3-mini
Derin Akıl Yürütme ModeliOpenAI tarafından geliştirilen o3-mini, 200K token bağlam penceresi ve 1M girdi başına $1.1, 1M çıktı başına $4.4 API fiyatlandırmasıyla yazılım geliştirme, analiz ve kurumsal otomasyon için tasarlanmıştır.
$1.10 / 1M
$4.40 / 1M
200K tokens
49%
Bir Bakışta Temel Farklar
- o3-mini is 2.9x cheaper for API usage (input + output tokens combined).
- o3-mini is faster at 85 tok/s vs 72 tok/s.
- Claude 3.7 Sonnet leads on SWE-bench coding (70.3% vs 49.0%).
| Feature | Claude 3.7 Sonnet | o3-mini |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 48 | 51 |
Provider | Anthropic | OpenAI |
Input Price Cost per million input tokens | $3.00 / 1M | $1.10 / 1M |
Output Price Cost per million output tokens | $15.00 / 1M | $4.40 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.31 / 1M | $1.05 / 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 | 72 tok/s | 85 tok/s |
SWE-bench Verified Real-world software engineering | 70.3% | 49% |
GPQA Diamond Graduate-level reasoning | 65% | 79.7% |
Cached Input Price Prompt caching discount per 1M tokens | $0.30 / 1M | $0.55 / 1M |
Hangi Alanda Kim Kazanıyor?
At-a-glance decision frameworkDoğrulanmış Benchmark Puanları
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.
Gecikme Süresi ve Yanıt Hızı
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Gerçek Zamanlı Token Maliyet Simülatörü
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Claude 3.7 Sonnet · Strengths & Key Advantages
- Anthropic imzalı gelişmiş Hybrid Reasoning MoE mimarisi ve 200K token bağlam kapasitesi
- Dengeli API maliyeti ($3/1M girdi, $15/1M çıktı) ve yüksek yanıt hızı
- Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
- Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
- Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir
o3-mini · Strengths & Key Advantages
- OpenAI imzalı gelişmiş Chain-of-Thought Reasoning Dense mimarisi ve 200K token bağlam kapasitesi
- Dengeli API maliyeti ($1.1/1M girdi, $4.4/1M çıktı) ve yüksek yanıt hızı
- Kod üretimi, mantıksal çıkarım ve çok dilli görevlerde güçlü kıyaslama (benchmark) sonuçları
Considerations & Trade-offs
- Çok uzun bağlamlı sorgularda token maliyetlerinin dikkatli yönetilmesi gerekir
- Alan bazlı özel iş akışlarında en yüksek verim için doğru istem (prompt) tasarımı önerilir
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Claude 3.7 Sonnet | o3-mini |
|---|---|---|
Cost per Task Estimated USD to finish one task | $1.42 | $1.30 |
Output Tokens / Task Tokens generated per task | 41K | 45K |
Reasoning Tokens / Task Thinking tokens burned per task | 22K | 25K |
Teknik Özellikler
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude 3.7 Sonnet | o3-mini |
|---|---|---|
| Official API Model ID (SDK) | claude-3-7-sonnet-20250201 | o3-mini |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-02 | 2025-01 |
| Knowledge Cutoff | November 2024 | October 2023 |
| Architecture | Hybrid Reasoning MoE | Chain-of-Thought Reasoning Dense |
| 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 ($1.1/1M 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 $0.55/1M (no extra cache-write fee) |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | 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 | 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) |
| 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 |
| Output Modalities | text | text |
Claude 3.7 Sonnet vs o3-mini: Hızlı Yanıtlar (SSS)
Which is more intelligent, Claude 3.7 Sonnet or o3-mini?
o3-mini is more intelligent. It scores 51 compared with 48 on the composite Intelligence Index.
Which model is faster?
o3-mini is faster, generating 85 tokens per second compared with 72 tokens per second.
Which model is cheaper to run?
o3-mini is cheaper at $1.05 per 1M tokens blended, compared with $2.31 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Claude 3.7 Sonnet has lower latency, with a time to first token of 0.52s compared with 1.40s.
Sonuç
Verdict & Model Selection Recommendation: Choose Claude 3.7 Sonnet if your priority is Full-stack software architecture, complex refactoring, and agentic workflows. Its performance in demanding tasks justifies its operational token cost. Choose o3-mini if your workflow prioritizes Competitive coding, mathematical research, algorithmic optimization, and backend logic. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Sıkça Sorulan Sorular (SSS)
How does Claude 3.7 Sonnet compare to o3-mini in API token pricing and cost per token?+
Claude 3.7 Sonnet costs $3.00 per 1M input tokens and $15.00 per 1M output tokens, whereas o3-mini costs $1.10 input and $4.40 output. Overall, o3-mini 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 3.7 Sonnet or o3-mini?+
Both Claude 3.7 Sonnet and o3-mini 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 3.7 Sonnet or o3-mini?+
Claude 3.7 Sonnet scores 70.3% on SWE-bench Verified while o3-mini scores 49%. For autonomous software engineering and multi-file debugging, Claude 3.7 Sonnet holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Claude 3.7 Sonnet and o3-mini?+
Claude 3.7 Sonnet features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, o3-mini provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Claude 3.7 Sonnet and o3-mini?+
Claude 3.7 Sonnet generates approximately 72 tokens per second, while o3-mini delivers 85 tokens per second. In latency-sensitive production environments, o3-mini provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Claude 3.7 Sonnet and o3-mini to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to o3-mini to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude 3.7 Sonnet. 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.
Related reading
- Claude 3.7 Sonnet vs DeepSeek R1: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- Claude 3.7 Sonnet vs GPT-4o: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- Claude Sonnet 4 vs Claude 3.7 Sonnet: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- DeepSeek R1 vs o3-mini: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- Gemini 2.0 Pro vs Claude 3.7 Sonnet: Benchmarks, Pricing & Speed ComparisonKarşılaştır
- Grok 3 Mini vs Claude 3.7 Sonnet: Benchmarks, Pricing & Speed ComparisonKarşılaştır
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.
Resmi kaynaklar: GetInfoUs Independent AI Benchmarks & Official API Specs