Claude Opus 4.8 vs GPT-5.5 Instant
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Claude Opus 4.8 by Anthropic and GPT-5.5 Instant 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-5.5 Instant holds a notable pricing advantage for token ingestion. On output generation, GPT-5.5 Instant is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Claude Opus 4.8 provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, GPT-5.5 Instant 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
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
Claude Opus 4.8
डीप रीजनिंग मॉडलAnthropic द्वारा विकसित Claude Opus 4.8 एक उन्नत AI मॉडल है, जिसमें 1M टोकन का कॉन्टेक्स्ट विंडो और $5/1M इनपुट तथा $25/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$5.00 / 1M
$25.00 / 1M
1M tokens
80.8%
GPT-5.5 Instant
डीप रीजनिंग मॉडलOpenAI द्वारा विकसित GPT-5.5 Instant एक उन्नत AI मॉडल है, जिसमें 400K टोकन का कॉन्टेक्स्ट विंडो और $0.75/1M इनपुट तथा $6/1M आउटपुट मूल्य निर्धारण है। यह कोडिंग, विश्लेषण और एंटरप्राइज वर्कफ़्लो के लिए उपयुक्त है।
$0.75 / 1M
$6.00 / 1M
400K tokens
74.5%
एक नज़र में मुख्य अंतर
- GPT-5.5 Instant is 4.6x cheaper for API usage (input + output tokens combined).
- Claude Opus 4.8 has a larger context window (1M vs 400K tokens).
- GPT-5.5 Instant is faster at 168 tok/s vs 64 tok/s.
- Claude Opus 4.8 leads on SWE-bench coding (80.8% vs 74.5%).
| Feature | Claude Opus 4.8 | GPT-5.5 Instant |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 67 | 65 |
Provider | Anthropic | OpenAI |
Input Price Cost per million input tokens | $5.00 / 1M | $0.75 / 1M |
Output Price Cost per million output tokens | $25.00 / 1M | $6.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $3.85 / 1M | $0.80 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 A4 pages of text | 400K tokens~600 A4 pages of text |
Max Output Tokens Per single request | 128K | 128K |
Throughput Speed Tokens generated per second | 64 tok/s | 168 tok/s |
SWE-bench Verified Real-world software engineering | 80.8% | 74.5% |
GPQA Diamond Graduate-level reasoning | 78.9% | 75% |
Cached Input Price Prompt caching discount per 1M tokens | $0.50 / 1M | $0.07 / 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 Opus 4.8 · Strengths & Key Advantages
- Anthropic की उन्नत Frontier Hybrid Cognitive Architecture आर्किटेक्चर और 1M कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($5/1M इनपुट, $25/1M 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
GPT-5.5 Instant · Strengths & Key Advantages
- OpenAI की उन्नत Low-latency compact reasoning model आर्किटेक्चर और 400K कॉन्टेक्स्ट विंडो क्षमता
- किफायती और पारदर्शी API मूल्य ($0.75/1M इनपुट, $6/1M 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 Opus 4.8 | GPT-5.5 Instant |
|---|---|---|
Cost per Task Estimated USD to finish one task | $5.49 | $0.95 |
Output Tokens / Task Tokens generated per task | 72K | 52K |
Reasoning Tokens / Task Thinking tokens burned per task | 37K | 26K |
तकनीकी विशिष्टताएँ (Specs)
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude Opus 4.8 | GPT-5.5 Instant |
|---|---|---|
| Official API Model ID (SDK) | claude-opus-4-8-20260501 | gpt-5-5-instant |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-05 | 2026-05 |
| Knowledge Cutoff | March 2026 | December 2025 |
| Architecture | Frontier Hybrid Cognitive Architecture | Low-latency compact reasoning model |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 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 ($0.75/1M in) across full 400K window |
| Prompt Cache Policy & TTL | $0.5/1M cached read (90% off); 5-min default & 1-hour extended TTL | Automatic prefix caching at $0.075/1M (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 Opus 4.8 vs GPT-5.5 Instant: त्वरित प्रश्नोत्तर (FAQ)
Which is more intelligent, Claude Opus 4.8 or GPT-5.5 Instant?
Claude Opus 4.8 is more intelligent. It scores 67 compared with 65 on the composite Intelligence Index.
Which model is faster?
GPT-5.5 Instant is faster, generating 168 tokens per second compared with 64 tokens per second.
Which model is cheaper to run?
GPT-5.5 Instant is cheaper at $0.80 per 1M tokens blended, compared with $3.85 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-5.5 Instant has lower latency, with a time to first token of 0.78s compared with 1.65s.
Which model has a larger context window?
Claude Opus 4.8 has a larger context window, supporting 1M tokens compared with 400K tokens.
निष्कर्ष
Verdict & Model Selection Recommendation: Choose Claude Opus 4.8 if your priority is Frontier AI research, multi-agent systems orchestration, and enterprise software engineering. Its performance in demanding tasks justifies its operational token cost. Choose GPT-5.5 Instant if your workflow prioritizes Interactive assistants and latency-sensitive routing. 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 Opus 4.8 compare to GPT-5.5 Instant in API token pricing and cost per token?+
Claude Opus 4.8 costs $5.00 per 1M input tokens and $25.00 per 1M output tokens, whereas GPT-5.5 Instant costs $0.75 input and $6.00 output. Overall, GPT-5.5 Instant 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 Opus 4.8 or GPT-5.5 Instant?+
Claude Opus 4.8 supports a context window of 1,000K tokens (~750k words), while GPT-5.5 Instant supports 400K tokens (~300k words). Therefore, Claude Opus 4.8 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Claude Opus 4.8 or GPT-5.5 Instant?+
Claude Opus 4.8 scores 80.8% on SWE-bench Verified while GPT-5.5 Instant scores 74.5%. For autonomous software engineering and multi-file debugging, Claude Opus 4.8 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Claude Opus 4.8 and GPT-5.5 Instant?+
Claude Opus 4.8 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, GPT-5.5 Instant provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Claude Opus 4.8 and GPT-5.5 Instant?+
Claude Opus 4.8 generates approximately 64 tokens per second, while GPT-5.5 Instant delivers 168 tokens per second. In latency-sensitive production environments, GPT-5.5 Instant provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Claude Opus 4.8 and GPT-5.5 Instant to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GPT-5.5 Instant to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude Opus 4.8. 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