GPT-5.1 Codex Max vs Claude Opus 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT-5.1 Codex Max by OpenAI and Claude Opus 5.5 by Anthropic 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-5.1 Codex Max holds a notable pricing advantage for token ingestion. On output generation, GPT-5.1 Codex Max is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Claude Opus 5.5 provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, GPT-5.1 Codex Max 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.
بدّل وقارن بين أي نموذجين
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GPT-5.1 Codex Max
نموذج استدلال عميقنموذج GPT-5.1 Codex Max المقدم من OpenAI يوفر نافذة سياق تصل إلى 400K رمز، بتكلفة $1.75 لكل مليون رمز إدخال و$14 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.
$1.75 / 1M
$14.00 / 1M
400K tokens
78.2%
Claude Opus 5.5
نموذج استدلال عميقنموذج Claude Opus 5.5 المقدم من Anthropic يوفر نافذة سياق تصل إلى 1M رمز، بتكلفة $4.0 لكل مليون رمز إدخال و$20.0 لكل مليون رمز إخراج، ومصمم للبرمجة والاستدلال وتطبيقات الأعمال.
$4.00 / 1M
$20.00 / 1M
1M tokens
84.6%
أهم الفروقات في لمحة
- GPT-5.1 Codex Max is 1.6x cheaper for API usage (input + output tokens combined).
- Claude Opus 5.5 has a larger context window (1M vs 400K tokens).
- GPT-5.1 Codex Max is faster at 95 tok/s vs 78 tok/s.
- Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 78.2%).
| Feature | GPT-5.1 Codex Max | Claude Opus 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 62 | 94 |
Provider | OpenAI | Anthropic |
Input Price Cost per million input tokens | $1.75 / 1M | $4.00 / 1M |
Output Price Cost per million output tokens | $14.00 / 1M | $20.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $1.87 / 1M | $3.08 / 1M |
Context Window Maximum input + output tokens | 400K tokens~600 A4 pages of text | 1M tokens~1,500 A4 pages of text |
Max Output Tokens Per single request | 128K | 128K |
Throughput Speed Tokens generated per second | 95 tok/s | 78 tok/s |
SWE-bench Verified Real-world software engineering | 78.2% | 84.6% |
GPQA Diamond Graduate-level reasoning | 80% | 82.3% |
Cached Input Price Prompt caching discount per 1M tokens | $0.17 / 1M | $0.40 / 1M |
من يتفوق في كل مجال؟
At-a-glance decision frameworkنتائج الاختبارات المعيارية الموثقة
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.
زمن الاستجابة والسرعة
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
محاكي تكلفة الرموز التفاعلي
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
GPT-5.1 Codex Max · Strengths & Key Advantages
- بنية Maximum-capability code-specialised reasoning model متطورة من OpenAI مع سعة سياق تبلغ 400K رمز
- كفاءة عالية في التكلفة ($1.75/1M إدخال و$14/1M إخراج) وسرعة استجابة ممتازة
- أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
- يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
- قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة
Claude Opus 5.5 · Strengths & Key Advantages
- بنية Extended Autonomous Hybrid Reasoning Transformer متطورة من Anthropic مع سعة سياق تبلغ 1M رمز
- كفاءة عالية في التكلفة ($4.0/1M إدخال و$20.0/1M إخراج) وسرعة استجابة ممتازة
- أداء قوي في اختبارات البرمجة، الاستدلال المنطقي، ودعم اللغات المتعددة
Considerations & Trade-offs
- يتطلب إدارة دقيقة لاستهلاك الرموز عند استخدام نافذة السياق الكاملة
- قد يحتاج إلى ضبط دقيق للتعليمات (Prompt Engineering) في المهام التخصصية المعقدة
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT-5.1 Codex Max | Claude Opus 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.40 | $3.85 |
Output Tokens / Task Tokens generated per task | 62K | 68K |
Reasoning Tokens / Task Thinking tokens burned per task | 36K | 42K |
المواصفات التقنية
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT-5.1 Codex Max | Claude Opus 5.5 |
|---|---|---|
| Official API Model ID (SDK) | gpt-5-1-codex-max | claude-opus-5-5-20260901 |
| API Protocol | OpenAI Responses API & Chat Completions v1 | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2025-11 | 2026-09 |
| Knowledge Cutoff | October 2024 | June 2026 |
| Architecture | Maximum-capability code-specialised reasoning model | Extended Autonomous Hybrid Reasoning Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($1.75/1M in) across full 400K window | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.175/1M (no extra cache-write fee) | $0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL |
| 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 tool + Hosted Code Interpreter & File Search RAG | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | Custom Model Tuning via Amazon Bedrock & Prompt Distillation |
| 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 | OpenAI Preparedness Framework Audited & System Card Published | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated |
| 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 |
GPT-5.1 Codex Max vs Claude Opus 5.5: إجابات سريعة (FAQ)
Which is more intelligent, GPT-5.1 Codex Max or Claude Opus 5.5?
Claude Opus 5.5 is more intelligent. It scores 94 compared with 62 on the composite Intelligence Index.
Which model is faster?
GPT-5.1 Codex Max is faster, generating 95 tokens per second compared with 78 tokens per second.
Which model is cheaper to run?
GPT-5.1 Codex Max is cheaper at $1.87 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Claude Opus 5.5 has lower latency, with a time to first token of 1.40s compared with 1.70s.
Which model has a larger context window?
Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 400K tokens.
الحكم النهائي
Verdict & Model Selection Recommendation: Choose GPT-5.1 Codex Max if your priority is Enterprise-scale code agents and monorepo work. Its performance in demanding tasks justifies its operational token cost. Choose Claude Opus 5.5 if your workflow prioritizes Large-scale software development agents, enterprise codebases, and mission-critical scientific synthesis. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
الأسئلة الشائعة (FAQ)
How does GPT-5.1 Codex Max compare to Claude Opus 5.5 in API token pricing and cost per token?+
GPT-5.1 Codex Max costs $1.75 per 1M input tokens and $14.00 per 1M output tokens, whereas Claude Opus 5.5 costs $4.00 input and $20.00 output. Overall, GPT-5.1 Codex Max 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: GPT-5.1 Codex Max or Claude Opus 5.5?+
GPT-5.1 Codex Max supports a context window of 400K tokens (~300k words), while Claude Opus 5.5 supports 1,000K tokens (~750k words). Therefore, Claude Opus 5.5 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: GPT-5.1 Codex Max or Claude Opus 5.5?+
GPT-5.1 Codex Max scores 78.2% on SWE-bench Verified while Claude Opus 5.5 scores 84.6%. For autonomous software engineering and multi-file debugging, Claude Opus 5.5 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between GPT-5.1 Codex Max and Claude Opus 5.5?+
GPT-5.1 Codex Max features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude Opus 5.5 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between GPT-5.1 Codex Max and Claude Opus 5.5?+
GPT-5.1 Codex Max generates approximately 95 tokens per second, while Claude Opus 5.5 delivers 78 tokens per second. In latency-sensitive production environments, GPT-5.1 Codex Max provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining GPT-5.1 Codex Max and Claude Opus 5.5 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GPT-5.1 Codex Max to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude Opus 5.5. 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
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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.
المصادر الرسمية: GetInfoUs Independent AI Benchmarks & Official API Specs