GPT Image 2 vs GPT Image 1.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT Image 2 by OpenAI and GPT Image 1.5 by OpenAI 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, both models offer identical input token rates. On output generation, costs are matched. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 4K tokens. In latency-sensitive production environments, GPT Image 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.
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GPT Image 2
旗舰 frontier 大模型OpenAI 推出的 GPT Image 2 人工智能模型，具备 4K 上下文窗口，输入价格为 $5/百万 Token，输出价格为 $40/百万 Token，专为高质量生产环境、推理与自动化工作流打造。
$5.00 / 1M
$40.00 / 1M
4.1K tokens
68.5%
GPT Image 1.5
旗舰 frontier 大模型OpenAI 推出的 GPT Image 1.5 人工智能模型，具备 4K 上下文窗口，输入价格为 $5/百万 Token，输出价格为 $40/百万 Token，专为高质量生产环境、推理与自动化工作流打造。
$5.00 / 1M
$40.00 / 1M
4.1K tokens
52%
核心差异一览
- Both models cost the same under this workload — choose on capability, not price.
- GPT Image 2 is faster at 21 tok/s vs 17 tok/s.
- GPT Image 2 leads on SWE-bench coding (68.5% vs 52.0%).
| Feature | GPT Image 2 | GPT Image 1.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 59 | 46 |
Provider | OpenAI | OpenAI |
Input Price Cost per million input tokens | $5.00 / 1M | $5.00 / 1M |
Output Price Cost per million output tokens | $40.00 / 1M | $40.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $5.00 / 1M | $5.00 / 1M |
Context Window Maximum input + output tokens | 4.1K tokens~6 A4 pages of text | 4.1K tokens~6 A4 pages of text |
Max Output Tokens Per single request | 4K | 4K |
Throughput Speed Tokens generated per second | 21 tok/s | 17 tok/s |
SWE-bench Verified Real-world software engineering | 68.5% | 52% |
GPQA Diamond Graduate-level reasoning | 72.5% | 66% |
各项指标谁更胜一筹？
At-a-glance decision framework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 2 · Strengths & Key Advantages
- 由 OpenAI 研发的高精度 Frontier native multimodal image transformer 架构，支持 4K 上下文窗口
- 极具竞争力的 API 定价（输入 $5/1M，输出 $40/1M），支持高速推理与工具调用
- 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
- 超长上下文请求需要规划 Token 成本与并发配额
- 针对特定垂直领域任务建议结合系统提示词与检索增强（RAG）以获得最佳效果
GPT Image 1.5 · Strengths & Key Advantages
- 由 OpenAI 研发的高精度 Native multimodal image generation transformer 架构，支持 4K 上下文窗口
- 极具竞争力的 API 定价（输入 $5/1M，输出 $40/1M），支持高速推理与工具调用
- 在代码生成、逻辑推理与多语言处理基准测试中表现出色
Considerations & Trade-offs
- 超长上下文请求需要规划 Token 成本与并发配额
- 针对特定垂直领域任务建议结合系统提示词与检索增强（RAG）以获得最佳效果
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT Image 2 | GPT Image 1.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.36 | $0.34 |
Output Tokens / Task Tokens generated per task | 9K | 9K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
技术规格参数
Architecture, release timeline, capabilities, and modalities.
| Feature | GPT Image 2 | GPT Image 1.5 |
|---|---|---|
| Official API Model ID (SDK) | gpt-image-2 | gpt-image-1-5 |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-04 | 2025-11 |
| Knowledge Cutoff | March 2026 | October 2025 |
| Architecture | Frontier native multimodal image transformer | Native multimodal image generation transformer |
| 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 ($5/1M in) across full 4K window |
| Prompt Cache Policy & TTL | Automatic prefix caching at $0/1M (no extra cache-write fee) | Automatic prefix caching at $0/1M (no extra cache-write fee) |
| 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 | Prompt-based JSON extraction only |
| Web Search Grounding & Sandbox | Native Web Search tool + Hosted Code Interpreter & File Search RAG | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) |
| 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 | OpenAI Preparedness Framework Audited & System Card Published |
| 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 GPT Image 1.5: 常见问题解答 (FAQ)
Which is more intelligent, GPT Image 2 or GPT Image 1.5?
GPT Image 2 is more intelligent. It scores 59 compared with 46 on the composite Intelligence Index.
Which model is faster?
GPT Image 2 is faster, generating 21 tokens per second compared with 17 tokens per second.
Which model has lower latency?
GPT Image 2 has lower latency, with a time to first token of 6.20s compared with 7.10s.
综合结论
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 GPT Image 1.5 if your workflow prioritizes Design and marketing workflows needing reliable prompt adherence. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
常见问题 (FAQ)
How does GPT Image 2 compare to GPT Image 1.5 in API token pricing and cost per token?+
Both GPT Image 2 and GPT Image 1.5 share matched API token pricing at $5.00 per 1M input tokens and $40.00 per 1M output tokens. Because their token economics are identical, your selection should be guided by benchmark latency, memory horizon, and reasoning capabilities rather than operational token fees.
Which model has a larger context window: GPT Image 2 or GPT Image 1.5?+
Both GPT Image 2 and GPT Image 1.5 offer an identical context window of 4K tokens (~3k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: GPT Image 2 or GPT Image 1.5?+
GPT Image 2 scores 68.5% on SWE-bench Verified while GPT Image 1.5 scores 52%. For autonomous software engineering and multi-file debugging, GPT Image 2 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between GPT Image 2 and GPT Image 1.5?+
GPT Image 2 is optimized for low-latency direct generation. In contrast, GPT Image 1.5 focuses on standard fast inference.
How does inference speed (tokens per second) compare between GPT Image 2 and GPT Image 1.5?+
GPT Image 2 generates approximately 21 tokens per second, while GPT Image 1.5 delivers 17 tokens per second. In latency-sensitive production environments, GPT Image 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 GPT Image 1.5 to optimize costs?+
Yes! Tiered multi-model routing can optimize for latency and accuracy: you can route high-frequency conversational turns and latency-sensitive queries to GPT Image 2, and route deep architectural or complex reasoning queries to GPT Image 2. This balanced routing strategy maximizes system throughput and answer quality.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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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: GetInfoUs Independent AI Benchmarks & Official API Specs