GPT-5.1 Codex mini vs Claude Opus 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (4)
Compare GPT-5.1 Codex mini by OpenAI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.
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Live comparison: no in-depth editorial review has been published for this pair yet.
GPT-5.1 Codex mini
Modèle Léger et ÉconomiqueGPT-5.1 Codex mini de OpenAI est un modèle d’IA conçu pour une efficacité économique maximale par token et une exécution légère à grande échelle, offrant une fenêtre de contexte de 400K, une vitesse de 180 tokens/s, un indice d’intelligence
$0.25 / 1M
$2.00 / 1M
400K tokens
55.5%
Claude Opus 5.5
Modèle Phare de PointeClaude Opus 5.5 de Anthropic est un modèle d’IA conçu pour le raisonnement d’entreprise de pointe, l’ingénierie logicielle et la production IA, offrant une fenêtre de contexte de 1M, une vitesse de 78 tokens/s, un indice d’intelligence de 9
$4.00 / 1M
$20.00 / 1M
1M tokens
84.6%
Différences Clés en un Coup d’Œil
- GPT-5.1 Codex mini is 11.1x 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 mini is faster at 180 tok/s vs 78 tok/s.
- Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 55.5%).
| Caractéristique | GPT-5.1 Codex mini | Claude Opus 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 47 | 94 |
Provider | OpenAI | Anthropic |
Input Price Cost per million input tokens | $0.25 / 1M | $4.00 / 1M |
Output Price Cost per million output tokens | $2.00 / 1M | $20.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.27 / 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 | 180 tok/s | 78 tok/s |
SWE-bench Verified Real-world software engineering | 55.5% | 84.6% |
GPQA Diamond Graduate-level reasoning | 66.5% | 82.3% |
Cached Input Price Prompt caching discount per 1M tokens | $0.03 / 1M | $0.40 / 1M |
Qui gagne où ?
At-a-glance decision frameworkScores de Benchmarks Vérifiés
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.
Latence et Temps de Réponse
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulateur Interactif de Coût de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
GPT-5.1 Codex mini · Strengths & Key Advantages
- Fenêtre de contexte de 400K et capacité de sortie maximale de 128K tokens (SWE-bench Verified 55.5% · GPQA Diamond 66.5%)
- Débit rapide de 180 tokens/seconde avec une latence au premier token (TTFT) de 720 ms
- Tarification API optimisée ($0.25/$2 par million de tokens) avec prise en charge du cache de prompts et des schémas JSON stricts
Considerations & Trade-offs
- Modèle cloud propriétaire ne permettant pas le téléchargement local des poids sur serveur isolé
- Sur les problèmes de recherche fondamentale très complexes, les modèles de raisonnement lourd restent supérieurs
Claude Opus 5.5 · Strengths & Key Advantages
- Fenêtre de contexte de 1M et capacité de sortie maximale de 128K tokens (SWE-bench Verified 84.6% · GPQA Diamond 82.3%)
- Débit rapide de 78 tokens/seconde avec une latence au premier token (TTFT) de 1400 ms
- Tarification API optimisée ($4/$20 par million de tokens) avec prise en charge du cache de prompts et des schémas JSON stricts
Considerations & Trade-offs
- Modèle cloud propriétaire ne permettant pas le téléchargement local des poids sur serveur isolé
- Pour les charges à très fort volume, l’activation du cache de prompts et de l’API Batch est recommandée
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT-5.1 Codex mini | Claude Opus 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.33 | $3.85 |
Output Tokens / Task Tokens generated per task | 48K | 68K |
Reasoning Tokens / Task Thinking tokens burned per task | 23K | 42K |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | GPT-5.1 Codex mini | Claude Opus 5.5 |
|---|---|---|
| Official API Model ID (SDK) | gpt-5-1-codex-mini | 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 | Compact 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 ($0.25/1M 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 $0.025/1M (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 mini vs Claude Opus 5.5: Réponses Rapides (FAQ)
Which is more intelligent, GPT-5.1 Codex mini or Claude Opus 5.5?
Claude Opus 5.5 is more intelligent. It scores 94 compared with 47 on the composite Intelligence Index.
Which model is faster?
GPT-5.1 Codex mini is faster, generating 180 tokens per second compared with 78 tokens per second.
Which model is cheaper to run?
GPT-5.1 Codex mini is cheaper at $0.27 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-5.1 Codex mini has lower latency, with a time to first token of 0.72s compared with 1.40s.
Which model has a larger context window?
Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 400K tokens.
Verdict
Choose GPT-5.1 Codex mini for conçu pour une efficacité économique maximale par token et une exécution légère à grande échelle, l’intégration rag et les pipelines de production évolutifs., or choose Claude Opus 5.5 for conçu pour le raisonnement d’entreprise de pointe, l’ingénierie logicielle et la production ia, l’intégration rag et les pipelines de production évolutifs..
Questions fréquentes
Which is cheaper: GPT-5.1 Codex mini or Claude Opus 5.5?+
GPT-5.1 Codex mini costs $0.25/1M input and $2/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.
Which model has a larger context window: GPT-5.1 Codex mini or Claude Opus 5.5?+
GPT-5.1 Codex mini supports 400K tokens whereas Claude Opus 5.5 supports 1M tokens.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.
Sources: OpenAI & Anthropic Official Documentation