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Code Davinci 001 vs gpt-oss-120b

Code Davinci 001 (2021) and gpt-oss-120b (2025) are agentic coding models from OpenAI. Code Davinci 001 ships a not-yet-sourced context window, while gpt-oss-120b ships a 131K-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-oss-120b is safer overall; choose Code Davinci 001 when coding workflow support matters.

Decision scorecard

Local evidence first
SignalCode Davinci 001gpt-oss-120b
Decision fitCodingRAG, Agents, and Long context
Context window131K
Cheapest output-$0.18/1M tokens
Provider routes0 tracked7 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Code Davinci 001 when...
  • Local decision data tags Code Davinci 001 for Coding.
Choose gpt-oss-120b when...
  • gpt-oss-120b has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • gpt-oss-120b has broader tracked provider coverage for fallback and procurement flexibility.
  • gpt-oss-120b uniquely exposes Function calling, Tool use, and Structured outputs in local model data.
  • Local decision data tags gpt-oss-120b for RAG, Agents, and Long context.

Monthly cost at traffic

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

Code Davinci 001

Unavailable

No complete token price in local provider data

gpt-oss-120b

$76.20

Cheapest tracked route: OpenRouter

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

Switch friction

Code Davinci 001 -> gpt-oss-120b
  • No overlapping tracked provider route is sourced for Code Davinci 001 and gpt-oss-120b; plan for SDK, billing, or endpoint changes.
  • gpt-oss-120b adds Function calling, Tool use, and Structured outputs in local capability data.
gpt-oss-120b -> Code Davinci 001
  • No overlapping tracked provider route is sourced for gpt-oss-120b and Code Davinci 001; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.

Specs

Specification
Released2021-07-012025-08-05
Context window131K
Parameters120B
Architecturedecoder onlydecoder only
LicenseProprietaryOpen Source
Knowledge cutoff-2025-08

Pricing and availability

Pricing attributeCode Davinci 001gpt-oss-120b
Input price-$0.04/1M tokens
Output price-$0.18/1M tokens
Providers-

Capabilities

CapabilityCode Davinci 001gpt-oss-120b
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on function calling: gpt-oss-120b, tool use: gpt-oss-120b, and structured outputs: gpt-oss-120b. 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: Code Davinci 001 has no token price sourced yet and gpt-oss-120b has $0.04/1M input tokens. Provider availability is 0 tracked routes versus 7. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Code Davinci 001 when coding workflow support are central to the workload. Choose gpt-oss-120b 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

Is Code Davinci 001 or gpt-oss-120b open source?

Code Davinci 001 is listed under Proprietary. gpt-oss-120b is listed under Open Source. 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 function calling, Code Davinci 001 or gpt-oss-120b?

gpt-oss-120b 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.

Which is better for tool use, Code Davinci 001 or gpt-oss-120b?

gpt-oss-120b has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for structured outputs, Code Davinci 001 or gpt-oss-120b?

gpt-oss-120b has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Code Davinci 001 and gpt-oss-120b?

Code Davinci 001 is available on the tracked providers still being sourced. gpt-oss-120b is available on OpenRouter, Together AI, Fireworks AI, GCP Vertex AI, and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Code Davinci 001 over gpt-oss-120b?

gpt-oss-120b is safer overall; choose Code Davinci 001 when coding workflow support matters. If your workload also depends on coding workflow support, start with Code Davinci 001; if it depends on provider fit, run the same evaluation with gpt-oss-120b.

Continue comparing

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