GPT Image 2 vs Nano Banana 2
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT Image 2 by OpenAI and Nano Banana 2 by Google 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, Nano Banana 2 holds a notable pricing advantage for token ingestion. On output generation, Nano Banana 2 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Nano Banana 2 provides an expanded memory horizon with 131K tokens. In latency-sensitive production environments, Nano Banana 2 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.
Changez et Comparez les Modèles
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GPT Image 2
Image de pointed'OpenAI 2026 image modèle pour prompt-driven génération, editing et design.
$5.00 / 1M
$40.00 / 1M
4.1K tokens
68.5%
Nano Banana 2
Retouche d'image de pointede pointe late-2026 image modèle blending profond linguistic raisonnement avec pinpoint visuel composition.
$3.00 / 1M
$30.00 / 1M
131.1K tokens
N/A
Différences Clés en un Coup d’Œil
- Nano Banana 2 is 1.3x cheaper for API usage (input + output tokens combined).
- Nano Banana 2 has a larger context window (131K vs 4K tokens).
- Nano Banana 2 is faster at 65 tok/s vs 21 tok/s.
| Caractéristique | GPT Image 2 | Nano Banana 2 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 59 | 88 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $5.00 / 1M | $3.00 / 1M |
Output Price Cost per million output tokens | $40.00 / 1M | $30.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $5.00 / 1M | $4.13 / 1M |
Context Window Maximum input + output tokens | 4.1K tokens~6 A4 pages of text | 131.1K tokens~197 A4 pages of text |
Max Output Tokens Per single request | 4K | 16K |
Throughput Speed Tokens generated per second | 21 tok/s | 65 tok/s |
SWE-bench Verified Real-world software engineering | 68.5% | N/A |
GPQA Diamond Graduate-level reasoning | 72.5% | N/A |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $0.75 / 1M |
Qui gagne où ?
At-a-glance decision frameworkEvaluations ongoing
Scores 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 Image 2 · Strengths & Key Advantages
- le plus élevé image qualité dans le GPT image line
- Excellent compositional et lighting control
- fiable multitour image editing
- Excellent à accurate dans-image texte et typography
Considerations & Trade-offs
- Premium tarification par generated image
- génération latence still élevé pour interactif design
Nano Banana 2 · Strengths & Key Advantages
- supérieur multi-scene storyboard fidelity
- en temps réel conversationnel visuel refinement
- exceptionnel handling de human hands et lighting
Considerations & Trade-offs
- Resource-heavy during élevé-concurrency requests
- Slightly supérieur coût structure
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT Image 2 | Nano Banana 2 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.36 | $0.04 |
Output Tokens / Task Tokens generated per task | 9K | 3K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 1K |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | GPT Image 2 | Nano Banana 2 |
|---|---|---|
| Official API Model ID (SDK) | gpt-image-2 | models/nano-banana-2 |
| API Protocol | OpenAI Responses API & Chat Completions v1 | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2026-04 | 2026-05 |
| Knowledge Cutoff | March 2026 | February 2026 |
| Architecture | Frontier native multimodal image transformer | Frontier conversational multimodal image engine |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Flat rate ($5/1M in) across full 4K window | Flat rate ($3/1M in) across full 131K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0/1M (no extra cache-write fee) | Implicit + Explicit Context Caching at $0.75/1M with configurable 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 | Prompt-based JSON extraction only | 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 | Built-in Google Search Grounding + Managed Python Code Execution Sandbox |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | Vertex AI Supervised Adapter Tuning & Context 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 | Google DeepMind Frontier Safety Framework 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, vision |
| Output Modalities | image | image |
GPT Image 2 vs Nano Banana 2: Réponses Rapides (FAQ)
Which is more intelligent, GPT Image 2 or Nano Banana 2?
Nano Banana 2 is more intelligent. It scores 88 compared with 59 on the composite Intelligence Index.
Which model is faster?
Nano Banana 2 is faster, generating 65 tokens per second compared with 21 tokens per second.
Which model is cheaper to run?
Nano Banana 2 is cheaper at $4.13 per 1M tokens blended, compared with $5.00 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Nano Banana 2 has lower latency, with a time to first token of 0.95s compared with 6.20s.
Which model has a larger context window?
Nano Banana 2 has a larger context window, supporting 131.1K tokens compared with 4.1K tokens.
Verdict
Verdict & Model Selection Recommendation: Choose GPT Image 2 if your priority is High-end visual production and campaign assets. Its performance in demanding tasks justifies its operational token cost. Choose Nano Banana 2 if your workflow prioritizes Full-scale comic generation, commercial advertising visuals, and film concept art. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Questions fréquentes
How does GPT Image 2 compare to Nano Banana 2 in API token pricing and cost per token?+
GPT Image 2 costs $5.00 per 1M input tokens and $40.00 per 1M output tokens, whereas Nano Banana 2 costs $3.00 input and $30.00 output. Overall, Nano Banana 2 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 Image 2 or Nano Banana 2?+
GPT Image 2 supports a context window of 4K tokens (~3k words), while Nano Banana 2 supports 131K tokens (~98k words). Therefore, Nano Banana 2 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: GPT Image 2 or Nano Banana 2?+
GPT Image 2 scores 68.5% on SWE-bench Verified, while Nano Banana 2 scores competitively for software generation. For complex autonomous debugging and agentic engineering, GPT Image 2 provides robust code generation and tool calling.
What is the difference in reasoning capability and extended thinking between GPT Image 2 and Nano Banana 2?+
GPT Image 2 is optimized for low-latency direct generation. In contrast, Nano Banana 2 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between GPT Image 2 and Nano Banana 2?+
GPT Image 2 generates approximately 21 tokens per second, while Nano Banana 2 delivers 65 tokens per second. In latency-sensitive production environments, Nano Banana 2 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining GPT Image 2 and Nano Banana 2 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Nano Banana 2 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to GPT Image 2. 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.
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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: GetInfoUs Independent AI Benchmarks & Official API Specs