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Head-to-Head Model Comparison

GPT Image 2 vs GPT Image 1.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

由 GetInfoUs 研究团队审核最后审核日期：October 2026编辑政策
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
GPT Image 2 vs GPT Image 1.5: Benchmarks, Pricing & Speed Comparison

OpenAI 的 GPT Image 2 与 OpenAI 的 GPT Image 1.5 是当前备受关注的两款主力 AI 模型。GPT Image 2 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 GPT Image 1.5 提供 4.1K Token 上下文窗口，定价为每百万 Token 输入 $5.00 / 输出 $40.00。以下为两者的基准测试、延迟与成本全面对比。

模型直接对比 (VS)

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OpenAI

GPT Image 2

高精度图像生成模型

OpenAI 推出的 GPT Image 2 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、21 Token/秒生成速度与 59/100 综合智能指数（每百万 Token $5 输入 / $40 输出）。

Intelligence Index59 / 100
Input Token:

$5.00 / 1M

Output Token:

$40.00 / 1M

Context Window:

4.1K tokens

SWE-bench Verified:

68.5%

OpenAI

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）。

Intelligence Index46 / 100
Input Token:

$5.00 / 1M

Output Token:

$40.00 / 1M

Context Window:

4.1K tokens

SWE-bench Verified:

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%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT Image 2GPT Image 1.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
5946
Provider
OpenAIOpenAI
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 text4.1K tokens~6 A4 pages of text
Max Output Tokens
Per single request
4K4K
Throughput Speed
Tokens generated per second
21 tok/s17 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
Coding
GPT Image 2
+16.5% SWE-bench lead
Cost
Tied
Identical monthly runtime cost
Speed
GPT Image 2
+24% faster generation
Context
Tied
4.1K tokens window

权威基准测试得分对比

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

GPT Image 2GPT Image 1.5
SWE-bench Verified (Autonomous Coding)

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

68.5%vs52%
GPQA Diamond (Doctorate-Level Science & Math)

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

72.5%vs66%
MMLU-Pro (Multi-task Language Understanding)

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

84.8%vs78.5%
LMSYS Chatbot Arena Elo

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

1375ptsvs1315pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

12.2%vs9.2%
Terminal-Bench (Agentic Coding & Terminal Use)

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

41.5%vs30.5%
SciCode (Scientific Computing)

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

40%vs32%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

67%vs56.5%
AIME (Advanced Math Competition)

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

89.6%vs84%
Long-Context Reasoning

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

78%vs68.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

21 tok/s vs17 tok/s

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.

Time to First Token (TTFT)Lower is better
GPT Image 26.20s
GPT Image 1.57.10s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT Image 230.01s
GPT Image 1.536.51s

实时 Token 成本模拟器

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)
GPT Image 2 Monthly API Bill
$43.50 / month
$5/1M in · $40/1M out
GPT Image 1.5 Monthly API Bill
$43.50 / month
$5/1M in · $40/1M out
These models cost the same under this workload — no savings either way.Break-even

GPT Image 2 · 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 68.5% · GPQA Diamond 72.5%）
  • 高达 21 Token/秒的生成吞吐量，首字延迟 (TTFT) 仅约 6200 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

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

Token Use & Task Economics

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

MetricGPT Image 2GPT Image 1.5
Cost per Task
Estimated USD to finish one task
$0.36$0.34
Output Tokens / Task
Tokens generated per task
9K9K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureGPT Image 2GPT Image 1.5
Official API Model ID (SDK)gpt-image-2gpt-image-1-5
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI Responses API & Chat Completions v1
Release Date2026-042025-11
Knowledge CutoffMarch 2026October 2025
ArchitectureFrontier native multimodal image 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 ($5/1M in) across full 4K windowFlat rate ($5/1M in) across full 4K window
Prompt Cache Policy & TTLAutomatic prefix caching at $0/1M (no extra cache-write fee)Automatic 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 CallingPrompt-based JSON extraction onlyPrompt-based JSON extraction only
Web Search Grounding & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Supervised 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 ClassificationOpenAI Preparedness Framework Audited & System Card PublishedOpenAI 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

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

综合来看，GPT Image 2（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 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。）各具优势：GPT Image 2 在综合智能与编程基准测试中表现更强，GPT Image 2 拥有更快的 Token 生成速度，而 GPT Image 2 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 2 和 GPT Image 1.5 哪个更强？+

在综合智能指数与编程基准评测中，GPT Image 2 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 2 与 GPT Image 1.5 的 API 价格哪个更便宜？+

GPT Image 2 的 API 价格为输入 $5.00 / 输出 $40.00（每百万 Token），GPT Image 1.5 为输入 $5.00 / 输出 $40.00。综合混合成本来看，GPT Image 2 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 2 支持 4.1K Token 上下文窗口，而 GPT Image 1.5 支持 4.1K Token。在流式生成速度方面，GPT Image 2 的吞吐表现更快。

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.

数据来源: OpenAI 与 OpenAI 官方 API 文档、模型发布说明及独立基准测试报告 (2026)。