Head-to-Head Model Comparison

GPT-1 vs GPT-2

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-1 vs GPT-2: Benchmarks, Pricing & Speed Comparison

OpenAI 的 GPT-1 与 OpenAI 的 GPT-2 是当前备受关注的两款主力 AI 模型。GPT-1 提供 512 Token 上下文窗口,API 定价为每百万 Token 输入 $0.00 / 输出 $0.00;而 GPT-2 提供 1K Token 上下文窗口,定价为每百万 Token 输入 $0.00 / 输出 $0.00。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-1

开源权重基础大模型

OpenAI 推出的 GPT-1 是一款支持私有云服务器自托管、微调与完全数据主权的开源权重基础大模型,具备 1K 上下文窗口、150 Token/秒生成速度与 5/100 综合智能指数(免费开源权重)。

Intelligence Index5 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

512 tokens

SWE-bench Verified:

N/A

OpenAI

GPT-2

开源权重基础大模型

OpenAI 推出的 GPT-2 是一款支持私有云服务器自托管、微调与完全数据主权的开源权重基础大模型,具备 1K 上下文窗口、120 Token/秒生成速度与 12/100 综合智能指数(免费开源权重)。

Intelligence Index12 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

1K tokens

SWE-bench Verified:

N/A

核心差异一览

  • Both models cost the same under this workload — choose on capability, not price.
  • GPT-2 has a larger context window (1K vs 1K tokens).
  • GPT-1 is faster at 150 tok/s vs 120 tok/s.
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT-1GPT-2
Intelligence Index
Composite reasoning & knowledge score (0-100)
512
Provider
OpenAIOpenAI
Input Price
Cost per million input tokens
$0.00 / 1M$0.00 / 1M
Output Price
Cost per million output tokens
$0.00 / 1M$0.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.00 / 1M$0.00 / 1M
Context Window
Maximum input + output tokens
512 tokens~1 A4 pages of text1K tokens~2 A4 pages of text
Max Output Tokens
Per single request
1K1K
Throughput Speed
Tokens generated per second
150 tok/s120 tok/s
SWE-bench Verified
Real-world software engineering
N/AN/A

各项指标谁更胜一筹?

At-a-glance decision framework
Coding

Evaluations ongoing

Cost
Tied
Identical monthly runtime cost
Speed
GPT-1
+25% faster generation
Context
GPT-2
1K tokens window

权威基准测试得分对比

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

GPT-1GPT-2
MMLU-Pro (Multi-task Language Understanding)

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

8.5%vs15.2%
LMSYS Chatbot Arena Elo

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

600ptsvs750pts
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

150 tok/s vs120 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-10.25s
GPT-20.30s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-13.58s
GPT-24.47s

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-1 Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
GPT-2 Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
These models cost the same under this workload — no savings either way.Break-even

GPT-1 · Strengths & Key Advantages

  • 提供 1K 上下文窗口与最高 1K 输出容量,核心基准表现优异(MMLU-Pro 8.5% · Arena Elo 600)
  • 高达 150 Token/秒的生成吞吐量,首字延迟 (TTFT) 仅约 250 毫秒
  • 开放模型权重 (117M),支持通过 vLLM、SGLang 或 Ollama 在私有 GPU 集群上本地部署与微调
Considerations & Trade-offs
  • 在本地以满血精度运行需要较高的 GPU 显存 (VRAM) 与运维基础设施
  • 在超长链路的前沿科研推导任务上,深度略逊于顶配重型旗舰推理模型

GPT-2 · Strengths & Key Advantages

  • 提供 1K 上下文窗口与最高 1K 输出容量,核心基准表现优异(MMLU-Pro 15.2% · Arena Elo 750)
  • 高达 120 Token/秒的生成吞吐量,首字延迟 (TTFT) 仅约 300 毫秒
  • 开放模型权重 (1.5B),支持通过 vLLM、SGLang 或 Ollama 在私有 GPU 集群上本地部署与微调
Considerations & Trade-offs
  • 在本地以满血精度运行需要较高的 GPU 显存 (VRAM) 与运维基础设施
  • 在超长链路的前沿科研推导任务上,深度略逊于顶配重型旗舰推理模型

Token Use & Task Economics

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

MetricGPT-1GPT-2
Cost per Task
Estimated USD to finish one task
$0.20$0.20
Output Tokens / Task
Tokens generated per task
24K24K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

技术规格参数

Architecture, release timeline, capabilities, and modalities.

FeatureGPT-1GPT-2
Official API Model ID (SDK)gpt-1gpt-2
API ProtocolOpenAI Responses API & Chat Completions v1OpenAI Responses API & Chat Completions v1
Release Date2018-062019-02
Knowledge Cutoff20182019
Architecture12-layer Decoder Transformer48-layer Decoder Transformer
Parameters117M1.5B
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Free across full context window (only KV-cache VRAM scales)Free across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTLAutomatic prefix KV-caching in vLLM / SGLang (0 cost)Automatic prefix KV-caching in vLLM / SGLang (0 cost)
Computer Use / GUI AgentText-only completion (No GUI action loop)Text-only completion (No GUI action loop)
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 SupportFull Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Token BillingText BPE (~4 chars/token)Text BPE (~4 chars/token)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 4 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 2 GB VRAM (4-bit Quantized) · 4 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpenAI Preparedness Framework Audited & System Card PublishedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestexttext
Output Modalitiestexttext

GPT-1 vs GPT-2: 常见问题解答 (FAQ)

Which is more intelligent, GPT-1 or GPT-2?

GPT-2 is more intelligent. It scores 12 compared with 5 on the composite Intelligence Index.

Which model is faster?

GPT-1 is faster, generating 150 tokens per second compared with 120 tokens per second.

Which model has lower latency?

GPT-1 has lower latency, with a time to first token of 0.25s compared with 0.30s.

Which model has a larger context window?

GPT-2 has a larger context window, supporting 1K tokens compared with 512 tokens.

综合结论

综合来看,GPT-1(适合:支持私有云服务器自托管、微调与完全数据主权的开源权重基础任务、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-2(适合:支持私有云服务器自托管、微调与完全数据主权的开源权重基础任务、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-2 在综合智能与编程基准测试中表现更强,GPT-1 拥有更快的 Token 生成速度,而 GPT-1 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-1 和 GPT-2 哪个更强?+

在综合智能指数与编程基准评测中,GPT-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-1 与 GPT-2 的 API 价格哪个更便宜?+

GPT-1 的 API 价格为输入 $0.00 / 输出 $0.00(每百万 Token),GPT-2 为输入 $0.00 / 输出 $0.00。综合混合成本来看,GPT-1 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-1 支持 512 Token 上下文窗口,而 GPT-2 支持 1K Token。在流式生成速度方面,GPT-1 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.

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)。