LLM Reference

Codex 1 vs GPT-2

Codex 1 (2025) and GPT-2 (2019) compare a coding-specialized model against a standalone API model. Codex 1 ships a 192K-token context window, while GPT-2 ships a 1K-token context window. This page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: Codex 1 is coding-specialized model, while GPT-2 is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalCodex 1GPT-2
Product typeCoding-specialized modelStandalone API model
Best forcustom coding agents and code generationgeneral production evaluation
Decision fitCoding, Agents, and Long contextGeneral
Context window192K1K
Cheapest output--
Provider routes0 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Codex 1 when...
  • Codex 1 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Codex 1 uniquely exposes Reasoning and Code execution in local model data.
  • Local decision data tags Codex 1 for Coding, Agents, and Long context.
Choose GPT-2 when...
  • GPT-2 has broader tracked provider coverage for fallback and procurement flexibility.

Monthly cost at traffic

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

Codex 1

Unavailable

No complete token price in local provider data

GPT-2

Unavailable

No complete token price in local provider data

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

Switch friction

Codex 1 -> GPT-2
  • No overlapping tracked provider route is sourced for Codex 1 and GPT-2; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Reasoning and Code execution before moving production traffic.
GPT-2 -> Codex 1
  • No overlapping tracked provider route is sourced for GPT-2 and Codex 1; plan for SDK, billing, or endpoint changes.
  • Codex 1 adds Reasoning and Code execution in local capability data.

Specs

Specification
Released2025-05-162019-02-14
Context window192K1K
Parameters124M
Architecturedecoder onlydecoder only
LicenseProprietaryUnknown
Knowledge cutoff-2017-12

Pricing and availability

Pricing attributeCodex 1GPT-2
Input price--
Output price--
Providers-

Pricing not yet sourced for either model.

Capabilities

CapabilityCodex 1GPT-2
VisionNoNo
MultimodalNoNo
ReasoningYesNo
Function callingNoNo
Tool useNoNo
Structured outputsNoNo
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 reasoning mode: Codex 1 and code execution: Codex 1. 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: Codex 1 has no token price sourced yet and GPT-2 has no token price sourced yet. Provider availability is 0 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Codex 1 when coding workflow support and larger context windows are central to the workload. Choose GPT-2 when provider fit 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, Codex 1 or GPT-2?

Codex 1 supports 192K tokens, while GPT-2 supports 1K 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 Codex 1 or GPT-2 open source?

Codex 1 is listed under Proprietary. GPT-2 is listed under Unknown. 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 reasoning mode, Codex 1 or GPT-2?

Codex 1 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for code execution, Codex 1 or GPT-2?

Codex 1 has the clearer documented code execution signal in this comparison. If code execution is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Codex 1 and GPT-2?

Codex 1 is available on the tracked providers still being sourced. GPT-2 is available on Azure OpenAI. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

When should I pick Codex 1 over GPT-2?

Treat this as a product-type comparison: Codex 1 is coding-specialized model, while GPT-2 is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive. If your workload also depends on coding workflow support, start with Codex 1; if it depends on provider fit, run the same evaluation with GPT-2.

Continue comparing

Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.