Code Davinci 001 vs GPT-4o (08-06)
Code Davinci 001 (2021) and GPT-4o (08-06) (2024) are agentic coding models from OpenAI. Code Davinci 001 ships a not-yet-sourced context window, while GPT-4o (08-06) ships a 128K-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-4o (08-06) is safer overall; choose Code Davinci 001 when coding workflow support matters.
Decision scorecard
Local evidence first| Signal | Code Davinci 001 | GPT-4o (08-06) |
|---|---|---|
| Decision fit | Coding | Coding, RAG, and Agents |
| Context window | — | 128K |
| Cheapest output | - | $10/1M tokens |
| Provider routes | 0 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Code Davinci 001 for Coding.
- GPT-4o (08-06) has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-4o (08-06) has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-4o (08-06) uniquely exposes Vision, Multimodal, and Structured outputs in local model data.
- Local decision data tags GPT-4o (08-06) for Coding, RAG, and Agents.
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-4o (08-06)
$4,500
Cheapest tracked route: OpenAI API
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Code Davinci 001 and GPT-4o (08-06); plan for SDK, billing, or endpoint changes.
- GPT-4o (08-06) adds Vision, Multimodal, and Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for GPT-4o (08-06) and Code Davinci 001; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision, Multimodal, and Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2021-07-01 | 2024-08-06 |
| Context window | — | 128K |
| Parameters | — | 1.76T (8x222B MoE)* |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | Proprietary |
| Knowledge cutoff | - | 2023-10 |
Pricing and availability
| Pricing attribute | Code Davinci 001 | GPT-4o (08-06) |
|---|---|---|
| Input price | - | $2.5/1M tokens |
| Output price | - | $10/1M tokens |
| Providers | - |
Capabilities
| Capability | Code Davinci 001 | GPT-4o (08-06) |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | No | Yes |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: GPT-4o (08-06), multimodal input: GPT-4o (08-06), structured outputs: GPT-4o (08-06), and code execution: GPT-4o (08-06). 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-4o (08-06) has $2.5/1M input tokens. Provider availability is 0 tracked routes versus 3. 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-4o (08-06) when coding workflow support 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.
FAQ
Is Code Davinci 001 or GPT-4o (08-06) open source?
Code Davinci 001 is listed under Proprietary. GPT-4o (08-06) 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, Code Davinci 001 or GPT-4o (08-06)?
GPT-4o (08-06) 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, Code Davinci 001 or GPT-4o (08-06)?
GPT-4o (08-06) 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 structured outputs, Code Davinci 001 or GPT-4o (08-06)?
GPT-4o (08-06) 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.
Which is better for code execution, Code Davinci 001 or GPT-4o (08-06)?
GPT-4o (08-06) 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 Code Davinci 001 and GPT-4o (08-06)?
Code Davinci 001 is available on the tracked providers still being sourced. GPT-4o (08-06) is available on OpenAI API, 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.