Claude 3.5 Sonnet vs GPT-4o
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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Claude 3.5 Sonnet by Anthropic and GPT-4o 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, GPT-4o holds a notable pricing advantage for token ingestion. On output generation, GPT-4o is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Claude 3.5 Sonnet provides an expanded memory horizon with 200K tokens. In latency-sensitive production environments, GPT-4o 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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Claude 3.5 Sonnet
Model Flagship TerdepanClaude 3.5 Sonnet dari Anthropic adalah model AI canggih dengan jendela konteks 200K token serta harga API $3/1M token input dan $15/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.
$3.00 / 1M
$15.00 / 1M
200K tokens
65%
GPT-4o
Model Flagship TerdepanGPT-4o dari OpenAI adalah model AI canggih dengan jendela konteks 128K token serta harga API $2.5/1M token input dan $10/1M token output untuk pemrograman, penalaran, dan otomasi bisnis.
$2.50 / 1M
$10.00 / 1M
128K tokens
38.8%
Perbedaan Utama Sekilas
- GPT-4o is 1.3x cheaper for API usage (input + output tokens combined).
- Claude 3.5 Sonnet has a larger context window (200K vs 128K tokens).
- GPT-4o is faster at 105 tok/s vs 80 tok/s.
- Claude 3.5 Sonnet leads on SWE-bench coding (65.0% vs 38.8%).
| Feature | Claude 3.5 Sonnet | GPT-4o |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 50 | 41 |
Provider | Anthropic | OpenAI |
Input Price Cost per million input tokens | $3.00 / 1M | $2.50 / 1M |
Output Price Cost per million output tokens | $15.00 / 1M | $10.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.31 / 1M | $2.38 / 1M |
Context Window Maximum input + output tokens | 200K tokens~300 A4 pages of text | 128K tokens~192 A4 pages of text |
Max Output Tokens Per single request | 8K | 16K |
Throughput Speed Tokens generated per second | 80 tok/s | 105 tok/s |
SWE-bench Verified Real-world software engineering | 65% | 38.8% |
GPQA Diamond Graduate-level reasoning | 59.4% | 53.6% |
Cached Input Price Prompt caching discount per 1M tokens | $0.30 / 1M | $1.25 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkSkor Benchmark Terverifikasi
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.
Latensi & Waktu Respons
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulator Biaya Token Interaktif
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Claude 3.5 Sonnet · Strengths & Key Advantages
- Arsitektur Next-Gen Multimodal Hybrid Transformer mutakhir dari Anthropic dengan dukungan konteks 200K token
- Efisiensi biaya API yang kompetitif ($3/1M input, $15/1M output) dan respons cepat
- Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
- Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
- Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik
GPT-4o · Strengths & Key Advantages
- Arsitektur Omni-Multimodal Dense mutakhir dari OpenAI dengan dukungan konteks 128K token
- Efisiensi biaya API yang kompetitif ($2.5/1M input, $10/1M output) dan respons cepat
- Performa andal dalam pembuatan kode, analisis logika, serta pemahaman multibahasa
Considerations & Trade-offs
- Penggunaan konteks berukuran penuh memerlukan pengelolaan anggaran token yang cermat
- Membutuhkan perancangan prompt yang tepat untuk kasus penggunaan industri spesifik
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Claude 3.5 Sonnet | GPT-4o |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.20 | $0.68 |
Output Tokens / Task Tokens generated per task | 24K | 24K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude 3.5 Sonnet | GPT-4o |
|---|---|---|
| Official API Model ID (SDK) | claude-3-5-sonnet-20240601 | gpt-4o |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2024-06 | 2024-05 |
| Knowledge Cutoff | April 2024 | October 2023 |
| Architecture | Next-Gen Multimodal Hybrid Transformer | Omni-Multimodal 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 ($2.5/1M in) across full 128K window |
| Prompt Cache Policy & TTL | $0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL | Automatic prefix caching at $1.25/1M (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) · Audio (~25–32 tokens/sec) |
| 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, audio |
| Output Modalities | text | text, audio |
Claude 3.5 Sonnet vs GPT-4o: Jawaban Cepat (FAQ)
Which is more intelligent, Claude 3.5 Sonnet or GPT-4o?
Claude 3.5 Sonnet is more intelligent. It scores 50 compared with 41 on the composite Intelligence Index.
Which model is faster?
GPT-4o is faster, generating 105 tokens per second compared with 80 tokens per second.
Which model is cheaper to run?
Claude 3.5 Sonnet is cheaper at $2.31 per 1M tokens blended, compared with $2.38 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-4o has lower latency, with a time to first token of 0.41s compared with 0.48s.
Which model has a larger context window?
Claude 3.5 Sonnet has a larger context window, supporting 200K tokens compared with 128K tokens.
Kesimpulan
Verdict & Model Selection Recommendation: Choose Claude 3.5 Sonnet if your priority is Complex multi-file software engineering, developer agents, visual UI prototyping, and autonomous computer use. Its performance in demanding tasks justifies its operational token cost. Choose GPT-4o if your workflow prioritizes Omni-modal voice applications, conversational agents, and structured enterprise APIs. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Pertanyaan Umum (FAQ)
How does Claude 3.5 Sonnet compare to GPT-4o in API token pricing and cost per token?+
Claude 3.5 Sonnet costs $3.00 per 1M input tokens and $15.00 per 1M output tokens, whereas GPT-4o costs $2.50 input and $10.00 output. Overall, GPT-4o 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 3.5 Sonnet or GPT-4o?+
Claude 3.5 Sonnet supports a context window of 200K tokens (~150k words), while GPT-4o supports 128K tokens (~96k words). Therefore, Claude 3.5 Sonnet can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Claude 3.5 Sonnet or GPT-4o?+
Claude 3.5 Sonnet scores 65% on SWE-bench Verified while GPT-4o scores 38.8%. For autonomous software engineering and multi-file debugging, Claude 3.5 Sonnet holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Claude 3.5 Sonnet and GPT-4o?+
Claude 3.5 Sonnet is optimized for low-latency direct generation. In contrast, GPT-4o focuses on standard fast inference.
How does inference speed (tokens per second) compare between Claude 3.5 Sonnet and GPT-4o?+
Claude 3.5 Sonnet generates approximately 80 tokens per second, while GPT-4o delivers 105 tokens per second. In latency-sensitive production environments, GPT-4o provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Claude 3.5 Sonnet and GPT-4o to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GPT-4o to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude 3.5 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.
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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.
Sumber resmi: GetInfoUs Independent AI Benchmarks & Official API Specs