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GPT-1 vs GPT-4

GPT-1 (2018) and GPT-4 (2023) are compact production models from OpenAI. GPT-1 ships a 512-token context window, while GPT-4 ships a 8K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

GPT-4 fits 16x more tokens; pick it for long-context work and GPT-1 for tighter calls.

Decision scorecard

Local evidence first
SignalGPT-1GPT-4
Decision fitGeneralCoding, Agents, and Vision
Context window5128K
Cheapest output-$60/1M tokens
Provider routes0 tracked4 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose GPT-1 when...
  • Use GPT-1 when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
Choose GPT-4 when...
  • GPT-4 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • GPT-4 has broader tracked provider coverage for fallback and procurement flexibility.
  • GPT-4 uniquely exposes Vision, Multimodal, and Function calling in local model data.
  • Local decision data tags GPT-4 for Coding, Agents, and Vision.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

GPT-1

Unavailable

No complete token price in local provider data

GPT-4

$39,000

Cheapest tracked route: OpenAI API

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

Switch friction

GPT-1 -> GPT-4
  • No overlapping tracked provider route is sourced for GPT-1 and GPT-4; plan for SDK, billing, or endpoint changes.
  • GPT-4 adds Vision, Multimodal, and Function calling in local capability data.
GPT-4 -> GPT-1
  • No overlapping tracked provider route is sourced for GPT-4 and GPT-1; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.

Specs

Specification
Released2018-06-112023-03-14
Context window5128K
Parameters120M1.76T (8x222B MoE)*
Architecturedecoder onlymixture of experts
LicenseUnknownProprietary
Knowledge cutoff-2021-09

Pricing and availability

Pricing attributeGPT-1GPT-4
Input price-$30/1M tokens
Output price-$60/1M tokens
Providers-

Capabilities

CapabilityGPT-1GPT-4
VisionNoYes
MultimodalNoYes
ReasoningNoNo
Function callingNoYes
Tool useNoNo
Structured outputsNoYes
Code executionNoYes

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: GPT-4, multimodal input: GPT-4, function calling: GPT-4, structured outputs: GPT-4, and code execution: GPT-4. 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-1 has no token price sourced yet and GPT-4 has $30/1M input tokens. Provider availability is 0 tracked routes versus 4. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose GPT-1 when provider fit are central to the workload. Choose GPT-4 when coding workflow support, larger context windows, and broader provider choice 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Which has a larger context window, GPT-1 or GPT-4?

GPT-4 supports 8K tokens, while GPT-1 supports 512 tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Is GPT-1 or GPT-4 open source?

GPT-1 is listed under Unknown. GPT-4 is listed under Proprietary. 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-1 or GPT-4?

GPT-4 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-1 or GPT-4?

GPT-4 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-1 or GPT-4?

GPT-4 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-1 and GPT-4?

GPT-1 is available on the tracked providers still being sourced. GPT-4 is available on OpenAI API, Azure OpenAI, Salesforce Einstein Generative AI, and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.