GPT-5.3 Codex vs KAT-Coder-Air V2.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT-5.3 Codex dari OpenAI dan KAT-Coder-Air V2.5 dari Kwaipilot adalah dua model AI unggulan. GPT-5.3 Codex menawarkan jendela konteks 400K token dengan harga $2.00/$16.00 per 1 juta token, sedangkan KAT-Coder-Air V2.5 menyediakan konteks 256K token seharga $0.10/$0.40 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.
Ganti & Bandingkan Model Apa Saja
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GPT-5.3 Codex
Pemimpin Pemrograman & KodeGPT-5.3 Codex dari OpenAI adalah model AI yang dirancang untuk rekayasa perangkat lunak otonom, refactoring multi-file, dan debugging mendalam, menghadirkan jendela konteks 400K, kecepatan 122 token/detik, indeks kecerdasan 72/100, serta ta
$2.00 / 1M
$16.00 / 1M
400K tokens
79%
KAT-Coder-Air V2.5
Model Ringan & Hemat BiayaKAT-Coder-Air V2.5 dari Kwaipilot adalah model AI yang dirancang untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, menghadirkan jendela konteks 256K, kecepatan 145 token/detik, indeks kecerdasan 77/100, serta
$0.10 / 1M
$0.40 / 1M
256K tokens
N/A
Perbedaan Utama Sekilas
- KAT-Coder-Air V2.5 is 33.7x cheaper for API usage (input + output tokens combined).
- GPT-5.3 Codex has a larger context window (400K vs 256K tokens).
- KAT-Coder-Air V2.5 is faster at 145 tok/s vs 122 tok/s.
| Feature | GPT-5.3 Codex | KAT-Coder-Air V2.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 72 | 77 |
Provider | OpenAI | Kwaipilot |
Input Price Cost per million input tokens | $2.00 / 1M | $0.10 / 1M |
Output Price Cost per million output tokens | $16.00 / 1M | $0.40 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $2.14 / 1M | $0.07 / 1M |
Context Window Maximum input + output tokens | 400K tokens~600 A4 pages of text | 256K tokens~384 A4 pages of text |
Max Output Tokens Per single request | 128K | 8K |
Throughput Speed Tokens generated per second | 122 tok/s | 145 tok/s |
SWE-bench Verified Real-world software engineering | 79% | N/A |
GPQA Diamond Graduate-level reasoning | 79.2% | N/A |
Cached Input Price Prompt caching discount per 1M tokens | $0.20 / 1M | $0.01 / 1M |
Siapa Unggul di Mana?
At-a-glance decision frameworkEvaluations ongoing
Skor 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.
GPT-5.3 Codex · Strengths & Key Advantages
- Jendela konteks 400K dengan kapasitas output maksimum hingga 128K token (SWE-bench Verified 79% · GPQA Diamond 79.2%)
- Kecepatan generasi tinggi 122 token/detik dengan latensi token pertama (TTFT) hanya 1230 ms
- Skema harga API kompetitif (tarif $2/$16 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
- Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya
KAT-Coder-Air V2.5 · Strengths & Key Advantages
- Jendela konteks 256K dengan kapasitas output maksimum hingga 8K token (MMLU-Pro 74% · Arena Elo 1285)
- Kecepatan generasi tinggi 145 token/detik dengan latensi token pertama (TTFT) hanya 290 ms
- Skema harga API kompetitif (tarif $0.1/$0.4 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.
| Metric | GPT-5.3 Codex | KAT-Coder-Air V2.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $2.60 | $0.03 |
Output Tokens / Task Tokens generated per task | 62K | 14K |
Reasoning Tokens / Task Thinking tokens burned per task | 36K | 1K |
Spesifikasi Teknis
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT-5.3 Codex | KAT-Coder-Air V2.5 |
|---|---|---|
| Official API Model ID (SDK) | gpt-5-3-codex | kat-coder-air-v2-5 |
| API Protocol | OpenAI Responses API & Chat Completions v1 | Kwaipilot REST API (OpenAI-Compatible) |
| Release Date | 2026-02 | 2026-07 |
| Knowledge Cutoff | November 2025 | April 2026 |
| Architecture | Code-specialised unified reasoning model | Lightweight Code-Generation Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | 5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($2/1M in) across full 400K window | Flat rate ($0.1/1M in) across full 256K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0.2/1M (no extra cache-write fee) | Cached input at $0.01/1M tokens |
| Computer Use / GUI Agent | Supported (Screen coordinate grounding, browser & desktop GUI action loops) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| 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 | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | API Prompt Engineering & RAG Distillation |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) |
| 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 | Kwaipilot Production Safety & Alignment Verified |
| 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 |
| Output Modalities | text | text |
GPT-5.3 Codex vs KAT-Coder-Air V2.5: Jawaban Cepat (FAQ)
Which is more intelligent, GPT-5.3 Codex or KAT-Coder-Air V2.5?
KAT-Coder-Air V2.5 is more intelligent. It scores 77 compared with 72 on the composite Intelligence Index.
Which model is faster?
KAT-Coder-Air V2.5 is faster, generating 145 tokens per second compared with 122 tokens per second.
Which model is cheaper to run?
KAT-Coder-Air V2.5 is cheaper at $0.07 per 1M tokens blended, compared with $2.14 (7:2:1 cache:input:output ratio).
Which model has lower latency?
KAT-Coder-Air V2.5 has lower latency, with a time to first token of 0.29s compared with 1.23s.
Which model has a larger context window?
GPT-5.3 Codex has a larger context window, supporting 400K tokens compared with 256K tokens.
Kesimpulan
Baik GPT-5.3 Codex (Sangat cocok untuk rekayasa perangkat lunak otonom, refactoring multi-file, dan debugging mendalam, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun KAT-Coder-Air V2.5 (Sangat cocok untuk efisiensi biaya API maksimal per token dan throughput produksi yang ringan, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: KAT-Coder-Air V2.5 unggul dalam penalaran dan pemrograman, KAT-Coder-Air V2.5 memberikan kecepatan generasi token lebih tinggi, dan KAT-Coder-Air V2.5 lebih hemat biaya untuk penggunaan API skala besar.
Pertanyaan Umum (FAQ)
Mana yang lebih baik untuk coding dan penalaran, GPT-5.3 Codex atau KAT-Coder-Air V2.5?+
Dalam indeks kecerdasan gabungan dan benchmark coding, KAT-Coder-Air V2.5 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.
Berapa perbandingan harga API GPT-5.3 Codex vs KAT-Coder-Air V2.5?+
GPT-5.3 Codex mengenakan biaya $2.00 / $16.00 per 1M token input/output, sedangkan KAT-Coder-Air V2.5 sebesar $0.10 / $0.40. Secara keseluruhan, KAT-Coder-Air V2.5 lebih hemat biaya.
Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+
GPT-5.3 Codex mendukung konteks 400K token dibandingkan 256K token pada KAT-Coder-Air V2.5, sementara KAT-Coder-Air V2.5 unggul dalam kecepatan output token per detik.
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: Dokumentasi API resmi OpenAI & Kwaipilot serta evaluasi benchmark independen (2026).