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Head-to-Head Model Comparison

Nano Banana vs GPT Image 1.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial
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Related topics (12)
AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Nano Banana vs GPT Image 1.5: Benchmarks, Pricing & Speed Comparison

Nano Banana dari Google dan GPT Image 1.5 dari OpenAI adalah dua model AI unggulan. Nano Banana menawarkan jendela konteks 32.8K token dengan harga $2.00/$20.00 per 1 juta token, sedangkan GPT Image 1.5 menyediakan konteks 4.1K token seharga $5.00/$40.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.

Perbandingan Langsung (VS)

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Nano Banana

Model Generasi Gambar AI

Nano Banana dari Google adalah model AI yang dirancang untuk pembuatan gambar AI resolusi tinggi, desain visual, dan perenderan tipografi akurat, menghadirkan jendela konteks 33K, kecepatan 60 token/detik, indeks kecerdasan 75/100, serta ta

Intelligence Index75 / 100
Input Token:

$2.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

32.8K tokens

SWE-bench Verified:

N/A

OpenAI

GPT Image 1.5

Model Generasi Gambar AI

GPT Image 1.5 dari OpenAI adalah model AI yang dirancang untuk pembuatan gambar AI resolusi tinggi, desain visual, dan perenderan tipografi akurat, menghadirkan jendela konteks 4K, kecepatan 17 token/detik, indeks kecerdasan 46/100, serta t

Intelligence Index46 / 100
Input Token:

$5.00 / 1M

Output Token:

$40.00 / 1M

Context Window:

4.1K tokens

SWE-bench Verified:

52%

Perbedaan Utama Sekilas

  • Nano Banana is 2.0x cheaper for API usage (input + output tokens combined).
  • Nano Banana has a larger context window (33K vs 4K tokens).
  • Nano Banana is faster at 60 tok/s vs 17 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureNano BananaGPT Image 1.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
7546
Provider
GoogleOpenAI
Input Price
Cost per million input tokens
$2.00 / 1M$5.00 / 1M
Output Price
Cost per million output tokens
$20.00 / 1M$40.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$2.75 / 1M$5.00 / 1M
Context Window
Maximum input + output tokens
32.8K tokens~49 A4 pages of text4.1K tokens~6 A4 pages of text
Max Output Tokens
Per single request
8K4K
Throughput Speed
Tokens generated per second
60 tok/s17 tok/s
SWE-bench Verified
Real-world software engineering
N/A52%
GPQA Diamond
Graduate-level reasoning
N/A66%
Cached Input Price
Prompt caching discount per 1M tokens
$0.50 / 1M$0.00 / 1M

Siapa Unggul di Mana?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Nano Banana
2.0x cheaper monthly runtime
Speed
Nano Banana
+253% faster generation
Context
Nano Banana
32.8K tokens window

Skor Benchmark Terverifikasi

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

Nano BananaGPT Image 1.5
SWE-bench Verified (Autonomous Coding)

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

N/Avs52%
GPQA Diamond (Doctorate-Level Science & Math)

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

N/Avs66%
MMLU-Pro (Multi-task Language Understanding)

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

N/Avs78.5%
LMSYS Chatbot Arena Elo

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

1360ptsvs1315pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

N/Avs9.2%
Terminal-Bench (Agentic Coding & Terminal Use)

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

N/Avs30.5%
SciCode (Scientific Computing)

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

N/Avs32%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

N/Avs56.5%
AIME (Advanced Math Competition)

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

N/Avs84%
Long-Context Reasoning

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

N/Avs68.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

60 tok/s vs17 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
Nano Banana0.90s
GPT Image 1.57.10s
Est. End-to-End Response (500 tokens)TTFT + generation time
Nano Banana9.23s
GPT Image 1.536.51s

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)
Nano Banana Monthly API Bill
$21.75 / month
$2/1M in · $20/1M out
GPT Image 1.5 Monthly API Bill
$43.50 / month
$5/1M in · $40/1M out
Nano Banana saves approximately $21.75 / month (50%) under this workload.2.0x Savings

Nano Banana · Strengths & Key Advantages

  • Jendela konteks 33K dengan kapasitas output maksimum hingga 8K token (Arena Elo 1360)
  • Kecepatan generasi tinggi 60 token/detik dengan latensi token pertama (TTFT) hanya 900 ms
  • Skema harga API kompetitif (tarif $2/$20 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

GPT Image 1.5 · Strengths & Key Advantages

  • Jendela konteks 4K dengan kapasitas output maksimum hingga 4K token (SWE-bench Verified 52% · GPQA Diamond 66%)
  • Kecepatan generasi tinggi 17 token/detik dengan latensi token pertama (TTFT) hanya 7100 ms
  • Skema harga API kompetitif (tarif $5/$40 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

Token Use & Task Economics

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

MetricNano BananaGPT Image 1.5
Cost per Task
Estimated USD to finish one task
$0.03$0.34
Output Tokens / Task
Tokens generated per task
1K9K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Spesifikasi Teknis

Architecture, release timeline, capabilities, and modalities.

FeatureNano BananaGPT Image 1.5
Official API Model ID (SDK)models/nano-bananagpt-image-1-5
API ProtocolGoogle Gemini API (generateContent) + OpenAI-Compatible SDKOpenAI Responses API & Chat Completions v1
Release Date2025-082025-11
Knowledge CutoffJune 2025October 2025
ArchitectureConversational in-context image generation and editing transformerNative multimodal image generation transformer
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 ($2/1M in) across full 33K windowFlat rate ($5/1M in) across full 4K window
Prompt Cache Policy & TTLImplicit + Explicit Context Caching at $0.5/1M with configurable TTLAutomatic prefix caching at $0/1M (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 SchemaPrompt-based JSON extraction only
Web Search Grounding & SandboxBuilt-in Google Search Grounding + Managed Python Code Execution SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportVertex AI Supervised Adapter Tuning & Context DistillationSupervised 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 ClassificationGoogle DeepMind Frontier Safety Framework VerifiedOpenAI 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 Modalitiesimageimage

Nano Banana vs GPT Image 1.5: Jawaban Cepat (FAQ)

Which is more intelligent, Nano Banana or GPT Image 1.5?

Nano Banana is more intelligent. It scores 75 compared with 46 on the composite Intelligence Index.

Which model is faster?

Nano Banana is faster, generating 60 tokens per second compared with 17 tokens per second.

Which model is cheaper to run?

Nano Banana is cheaper at $2.75 per 1M tokens blended, compared with $5.00 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Nano Banana has lower latency, with a time to first token of 0.90s compared with 7.10s.

Which model has a larger context window?

Nano Banana has a larger context window, supporting 32.8K tokens compared with 4.1K tokens.

Kesimpulan

Baik Nano Banana (Sangat cocok untuk pembuatan gambar AI resolusi tinggi, desain visual, dan perenderan tipografi akurat, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun GPT Image 1.5 (Sangat cocok untuk pembuatan gambar AI resolusi tinggi, desain visual, dan perenderan tipografi akurat, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Nano Banana unggul dalam penalaran dan pemrograman, Nano Banana memberikan kecepatan generasi token lebih tinggi, dan Nano Banana lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Nano Banana atau GPT Image 1.5?+

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

Berapa perbandingan harga API Nano Banana vs GPT Image 1.5?+

Nano Banana mengenakan biaya $2.00 / $20.00 per 1M token input/output, sedangkan GPT Image 1.5 sebesar $5.00 / $40.00. Secara keseluruhan, Nano Banana lebih hemat biaya.

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

Nano Banana mendukung konteks 32.8K token dibandingkan 4.1K token pada GPT Image 1.5, sementara Nano Banana 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 Google & OpenAI serta evaluasi benchmark independen (2026).