GPT Image 1.5 vs Nano Banana Pro
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
OpenAI 的 GPT Image 1.5 与 Google 的 Nano Banana Pro 是当前备受关注的两款主力 AI 模型。GPT Image 1.5 提供 4.1K Token 上下文窗口，API 定价为每百万 Token 输入 $5.00 / 输出 $40.00；而 Nano Banana Pro 提供 65.5K Token 上下文窗口，定价为每百万 Token 输入 $3.50 / 输出 $35.00。以下为两者的基准测试、延迟与成本全面对比。
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GPT Image 1.5
高精度图像生成模型OpenAI 推出的 GPT Image 1.5 是一款专注于高分辨率视觉创作、精准文字渲染与图像生成的大模型，具备 4K 上下文窗口、17 Token/秒生成速度与 46/100 综合智能指数（每百万 Token $5 输入 / $40 输出）。
$5.00 / 1M
$40.00 / 1M
4.1K tokens
52%
Nano Banana Pro
高精度图像生成模型Google 推出的 Nano Banana Pro 是一款专注于高分辨率视觉创作、精准文字渲染与图像生成的大模型，具备 66K 上下文窗口、50 Token/秒生成速度与 83/100 综合智能指数（每百万 Token $3.5 输入 / $35 输出）。
$3.50 / 1M
$35.00 / 1M
65.5K tokens
N/A
核心差异一览
- Nano Banana Pro is 1.1x cheaper for API usage (input + output tokens combined).
- Nano Banana Pro has a larger context window (66K vs 4K tokens).
- Nano Banana Pro is faster at 50 tok/s vs 17 tok/s.
| Feature | GPT Image 1.5 | Nano Banana Pro |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 46 | 83 |
Provider | OpenAI | |
Input Price Cost per million input tokens | $5.00 / 1M | $3.50 / 1M |
Output Price Cost per million output tokens | $40.00 / 1M | $35.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $5.00 / 1M | $4.76 / 1M |
Context Window Maximum input + output tokens | 4.1K tokens~6 A4 pages of text | 65.5K tokens~98 A4 pages of text |
Max Output Tokens Per single request | 4K | 16K |
Throughput Speed Tokens generated per second | 17 tok/s | 50 tok/s |
SWE-bench Verified Real-world software engineering | 52% | N/A |
GPQA Diamond Graduate-level reasoning | 66% | N/A |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $0.80 / 1M |
各项指标谁更胜一筹？
At-a-glance decision frameworkEvaluations ongoing
权威基准测试得分对比
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.
延迟与响应速度
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
实时 Token 成本模拟器
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
GPT Image 1.5 · Strengths & Key Advantages
- 提供 4K 上下文窗口与最高 4K 输出容量，核心基准表现优异（SWE-bench Verified 52% · GPQA Diamond 66%）
- 高达 17 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 7100 毫秒
- 极具竞争力的 API 定价（每百万 Token $5 输入 / $40 输出），原生支持提示词缓存、函数调用与结构化 JSON 输出
Considerations & Trade-offs
- 闭源专有云端模型，不支持下载权重进行离线本地物理隔离部署
- 在大规模高频调用场景下，建议结合提示词缓存 (Prompt Caching) 与批量 API 以控制成本
Nano Banana Pro · Strengths & Key Advantages
- 提供 66K 上下文窗口与最高 16K 输出容量，核心基准表现优异（Arena Elo 1415）
- 高达 50 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 1200 毫秒
- 极具竞争力的 API 定价（每百万 Token $3.5 输入 / $35 输出），原生支持提示词缓存、函数调用与结构化 JSON 输出
Considerations & Trade-offs
- 闭源专有云端模型，不支持下载权重进行离线本地物理隔离部署
- 在大规模高频调用场景下，建议结合提示词缓存 (Prompt Caching) 与批量 API 以控制成本
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT Image 1.5 | Nano Banana Pro |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.34 | $0.05 |
Output Tokens / Task Tokens generated per task | 9K | 2K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 1K |
技术规格参数
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT Image 1.5 | Nano Banana Pro |
|---|---|---|
| Official API Model ID (SDK) | gpt-image-1-5 | models/nano-banana-pro |
| API Protocol | OpenAI Responses API & Chat Completions v1 | Google Gemini API (generateContent) + OpenAI-Compatible SDK |
| Release Date | 2025-11 | 2025-11 |
| Knowledge Cutoff | October 2025 | September 2025 |
| Architecture | Native multimodal image generation transformer | High-fidelity design-grade image generation and compositional editor |
| 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 ($3.5/1M in) across full 66K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0/1M (no extra cache-write fee) | Implicit + Explicit Context Caching at $0.8/1M 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 1.5 vs Nano Banana Pro: 常见问题解答 (FAQ)
Which is more intelligent, GPT Image 1.5 or Nano Banana Pro?
Nano Banana Pro is more intelligent. It scores 83 compared with 46 on the composite Intelligence Index.
Which model is faster?
Nano Banana Pro is faster, generating 50 tokens per second compared with 17 tokens per second.
Which model is cheaper to run?
Nano Banana Pro is cheaper at $4.76 per 1M tokens blended, compared with $5.00 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Nano Banana Pro has lower latency, with a time to first token of 1.20s compared with 7.10s.
Which model has a larger context window?
Nano Banana Pro has a larger context window, supporting 65.5K tokens compared with 4.1K tokens.
综合结论
综合来看，GPT Image 1.5（适合：专注于高分辨率视觉创作、精准文字渲染与图像生成的任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）与 Nano Banana Pro（适合：专注于高分辨率视觉创作、精准文字渲染与图像生成的任务、企业级 RAG 检索增强生成、自动化智能体工作流与高可靠 API 集成。）各具优势：Nano Banana Pro 在综合智能与编程基准测试中表现更强，Nano Banana Pro 拥有更快的 Token 生成速度，而 Nano Banana Pro 则在规模化 API 部署中具备更高的成本效益。
常见问题 (FAQ)
在编程和深度推理方面，GPT Image 1.5 和 Nano Banana Pro 哪个更强？+
在综合智能指数与编程基准评测中，Nano Banana Pro 表现占优。建议结合上方的 SWE-bench Verified 与 GPQA Diamond 跑分根据具体场景选择。
GPT Image 1.5 与 Nano Banana Pro 的 API 价格哪个更便宜？+
GPT Image 1.5 的 API 价格为输入 $5.00 / 输出 $40.00（每百万 Token），Nano Banana Pro 为输入 $3.50 / 输出 $35.00。综合混合成本来看，Nano Banana Pro 更具性价比。
哪款模型拥有更大的上下文窗口和更快的响应速度？+
GPT Image 1.5 支持 4.1K Token 上下文窗口，而 Nano Banana Pro 支持 65.5K Token。在流式生成速度方面，Nano Banana Pro 的吞吐表现更快。
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
- GPT Image 2 vs GPT Image 1.5：基准测试、API 价格与速度全面对比 (2026)对比
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- Nano Banana Pro vs Nano Banana：基准测试、API 价格与速度全面对比 (2026)对比
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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.
数据来源: OpenAI 与 Google 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。