LLM Reference

GPT-4 Turbo vs GPT-2 XL

GPT-4 Turbo (2024) and GPT-2 XL (2019) are compact production models from OpenAI. GPT-4 Turbo ships a 128k-token context window, while GPT-2 XL ships a 1k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.

GPT-4 Turbo fits 128x more tokens; pick it for long-context work and GPT-2 XL for tighter calls.

Decision scorecard

Local evidence first
SignalGPT-4 TurboGPT-2 XL
Best formultimodal apps, tool-calling agents, and provider-routed productiongeneral production evaluation
Decision fitCoding, RAG, and AgentsGeneral
Context window128k1k
Cheapest output$15/1M tokens-
Provider routes6 tracked0 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose GPT-4 Turbo when...
  • GPT-4 Turbo has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • GPT-4 Turbo has broader tracked provider coverage for fallback and procurement flexibility.
  • GPT-4 Turbo uniquely exposes Vision, Multimodal, and Function calling in local model data.
  • Local decision data tags GPT-4 Turbo for Coding, RAG, and Agents.
Choose GPT-2 XL when...
  • Use GPT-2 XL when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

GPT-4 Turbo

$7,750

Cheapest tracked route/tier: Replicate API

GPT-2 XL

Unavailable

No complete token price in local provider data

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

GPT-4 Turbo -> GPT-2 XL
  • No overlapping tracked provider route is sourced for GPT-4 Turbo and GPT-2 XL; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
GPT-2 XL -> GPT-4 Turbo
  • No overlapping tracked provider route is sourced for GPT-2 XL and GPT-4 Turbo; plan for SDK, billing, or endpoint changes.
  • GPT-4 Turbo adds Vision, Multimodal, and Function calling in local capability data.

Specs

Specification
Released2024-04-092019-11-05
Context window128k1k
Parameters1.76T (8x222B MoE)*1.5B
Architecturemixture of expertsdecoder only
LicenseProprietaryMIT(OSI)
OpennessProprietaryOpen source
Commercial useCommercial use with conditionsCommercial use allowed
Knowledge cutoff2023-122017-12

Pricing and availability

Pricing attributeGPT-4 TurboGPT-2 XL
Input price$5/1M tokens-
Output price$15/1M tokens-
Providers-

Capabilities

CapabilityGPT-4 TurboGPT-2 XL
VisionYesNo
MultimodalYesNo
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesNo
Code executionYesNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: GPT-4 Turbo, multimodal input: GPT-4 Turbo, function calling: GPT-4 Turbo, tool use: GPT-4 Turbo, structured outputs: GPT-4 Turbo, and code execution: GPT-4 Turbo. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: GPT-4 Turbo has $5/1M input tokens and GPT-2 XL has no token price sourced yet. Provider availability is 6 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose GPT-4 Turbo when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose GPT-2 XL when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.

FAQ

Which has a larger context window, GPT-4 Turbo or GPT-2 XL?

GPT-4 Turbo supports 128k tokens, while GPT-2 XL supports 1k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is GPT-4 Turbo or GPT-2 XL open source?

GPT-4 Turbo is listed under Proprietary. GPT-2 XL is listed under MIT. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for vision, GPT-4 Turbo or GPT-2 XL?

GPT-4 Turbo has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, GPT-4 Turbo or GPT-2 XL?

GPT-4 Turbo has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for function calling, GPT-4 Turbo or GPT-2 XL?

GPT-4 Turbo has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run GPT-4 Turbo and GPT-2 XL?

GPT-4 Turbo is available on OpenAI API, Azure OpenAI, Salesforce Einstein Generative AI, OpenRouter, and Replicate API. GPT-2 XL is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.