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GPT-5.1 Codex mini vs GPT-5-Codex

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
GPT-5.1 Codex mini vs GPT-5-Codex: Benchmarks, Pricing & Speed Comparison

GPT-5.1 Codex mini dari OpenAI dan GPT-5-Codex dari OpenAI adalah dua model AI unggulan. GPT-5.1 Codex mini menawarkan jendela konteks 400K token dengan harga $0.25/$2.00 per 1 juta token, sedangkan GPT-5-Codex menyediakan konteks 400K token seharga $1.25/$10.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.

Perbandingan Langsung (VS)

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OpenAI

GPT-5.1 Codex mini

Model Ringan & Hemat Biaya

GPT-5.1 Codex mini dari OpenAI adalah model AI yang dirancang untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, menghadirkan jendela konteks 400K, kecepatan 180 token/detik, indeks kecerdasan 47/100, serta ta

Intelligence Index47 / 100
Input Token:

$0.25 / 1M

Output Token:

$2.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

55.5%

OpenAI

GPT-5-Codex

Pemimpin Pemrograman & Kode

GPT-5-Codex dari OpenAI adalah model AI yang dirancang untuk rekayasa perangkat lunak otonom, refactoring multi-file, dan debugging mendalam, menghadirkan jendela konteks 400K, kecepatan 120 token/detik, indeks kecerdasan 57/100, serta tari

Intelligence Index57 / 100
Input Token:

$1.25 / 1M

Output Token:

$10.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

74.5%

Perbedaan Utama Sekilas

  • GPT-5.1 Codex mini is 5.0x cheaper for API usage (input + output tokens combined).
  • GPT-5.1 Codex mini is faster at 180 tok/s vs 120 tok/s.
  • GPT-5-Codex leads on SWE-bench coding (74.5% vs 55.5%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT-5.1 Codex miniGPT-5-Codex
Intelligence Index
Composite reasoning & knowledge score (0-100)
4757
Provider
OpenAIOpenAI
Input Price
Cost per million input tokens
$0.25 / 1M$1.25 / 1M
Output Price
Cost per million output tokens
$2.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.27 / 1M$1.34 / 1M
Context Window
Maximum input + output tokens
400K tokens~600 A4 pages of text400K tokens~600 A4 pages of text
Max Output Tokens
Per single request
128K128K
Throughput Speed
Tokens generated per second
180 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
55.5%74.5%
GPQA Diamond
Graduate-level reasoning
66.5%80.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.03 / 1M$0.13 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework
Coding
GPT-5-Codex
+19.0% SWE-bench lead
Cost
GPT-5.1 Codex mini
5.0x cheaper monthly runtime
Speed
GPT-5.1 Codex mini
+50% faster generation
Context
Tied
400K tokens window

Skor Benchmark Terverifikasi

Official evaluation metrics verified by independent third-party research labs.

GPT-5.1 Codex miniGPT-5-Codex
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

55.5%vs74.5%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

66.5%vs80.5%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

79%vs85.5%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1320ptsvs1360pts
Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

9.4%vs12%
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

32%vs50%
SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

33%vs45.5%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

58%vs73.5%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

84.5%vs90.5%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

69%vs77%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

180 tok/s vs120 tok/s

Latensi & Waktu Respons

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
GPT-5.1 Codex mini0.72s
GPT-5-Codex1.25s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-5.1 Codex mini3.50s
GPT-5-Codex5.42s

Simulator Biaya Token Interaktif

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
GPT-5.1 Codex mini Monthly API Bill
$2.21 / month
$0.25/1M in · $2/1M out
GPT-5-Codex Monthly API Bill
$11.06 / month
$1.25/1M in · $10/1M out
GPT-5.1 Codex mini saves approximately $8.85 / month (80%) under this workload.5.0x Savings

GPT-5.1 Codex mini · Strengths & Key Advantages

  • Jendela konteks 400K dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 55.5% · GPQA Diamond 66.5%)
  • Kecepatan generasi tinggi 180 token/detik dengan latensi token pertama (TTFT) hanya 720 ms
  • Skema harga API kompetitif (tarif $0.25/$2 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

GPT-5-Codex · Strengths & Key Advantages

  • Jendela konteks 400K dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 74.5% · GPQA Diamond 80.5%)
  • Kecepatan generasi tinggi 120 token/detik dengan latensi token pertama (TTFT) hanya 1250 ms
  • Skema harga API kompetitif (tarif $1.25/$10 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Pada tugas pembuktian ilmiah tingkat ekstrem, model penalaran berat kelas atas memberikan kedalaman lebih tinggi

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricGPT-5.1 Codex miniGPT-5-Codex
Cost per Task
Estimated USD to finish one task
$0.33$1.60
Output Tokens / Task
Tokens generated per task
48K58K
Reasoning Tokens / Task
Thinking tokens burned per task
23K32K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

FeatureGPT-5.1 Codex miniGPT-5-Codex
Official API Model ID (SDK)gpt-5-1-codex-minigpt-5-codex
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI Responses API & Chat Completions v1
Release Date2025-112025-09
Knowledge CutoffOctober 2024September 2024
ArchitectureCompact code-specialised reasoning modelCode-specialised unified reasoning model
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($0.25/1M in) across full 400K windowFlat rate ($1.25/1M in) across full 400K window
Prompt Cache Policy & TTLAutomatic prefix caching at $0.025/1M (no extra cache-write fee)Automatic prefix caching at $0.125/1M (no extra cache-write fee)
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText 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 VRAMCloud-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 ClassificationOpenAI Preparedness Framework Audited & System Card PublishedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

GPT-5.1 Codex mini vs GPT-5-Codex: Jawaban Cepat (FAQ)

Which is more intelligent, GPT-5.1 Codex mini or GPT-5-Codex?

GPT-5-Codex is more intelligent. It scores 57 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 120 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 $1.34 (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 1.25s.

Kesimpulan

Baik GPT-5.1 Codex mini (Sangat cocok untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun GPT-5-Codex (Sangat cocok untuk rekayasa perangkat lunak otonom, refactoring multi-file, dan debugging mendalam, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: GPT-5-Codex unggul dalam penalaran dan pemrograman, GPT-5.1 Codex mini memberikan kecepatan generasi token lebih tinggi, dan GPT-5.1 Codex mini lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, GPT-5.1 Codex mini atau GPT-5-Codex?+

Dalam indeks kecerdasan gabungan dan benchmark coding, GPT-5-Codex memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API GPT-5.1 Codex mini vs GPT-5-Codex?+

GPT-5.1 Codex mini mengenakan biaya $0.25 / $2.00 per 1M token input/output, sedangkan GPT-5-Codex sebesar $1.25 / $10.00. Secara keseluruhan, GPT-5.1 Codex mini lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

GPT-5.1 Codex mini mendukung konteks 400K token dibandingkan 400K token pada GPT-5-Codex, sementara GPT-5.1 Codex mini unggul dalam kecepatan output token per detik.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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: Dokumentasi API resmi OpenAI & OpenAI serta evaluasi benchmark independen (2026).