Code Davinci 001 vs Kimi K2 Turbo Preview
Code Davinci 001 (2021) and Kimi K2 Turbo Preview (2025) are agentic coding models from OpenAI and Moonshot AI. Code Davinci 001 ships a not-yet-sourced context window, while Kimi K2 Turbo Preview ships a 262K-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.
Kimi K2 Turbo Preview is safer overall; choose Code Davinci 001 when coding workflow support matters.
Decision scorecard
Local evidence first| Signal | Code Davinci 001 | Kimi K2 Turbo Preview |
|---|---|---|
| Decision fit | Coding | RAG, Agents, and Long context |
| Context window | — | 262K |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Code Davinci 001 for Coding.
- Kimi K2 Turbo Preview has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Kimi K2 Turbo Preview uniquely exposes Function calling in local model data.
- Local decision data tags Kimi K2 Turbo Preview 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
Kimi K2 Turbo Preview
Unavailable
No complete token price in local provider data
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 Kimi K2 Turbo Preview; plan for SDK, billing, or endpoint changes.
- Kimi K2 Turbo Preview adds Function calling in local capability data.
- No overlapping tracked provider route is sourced for Kimi K2 Turbo Preview and Code Davinci 001; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2021-07-01 | 2025-08-01 |
| Context window | — | 262K |
| Parameters | — | 1K |
| Architecture | decoder only | - |
| License | Proprietary | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Code Davinci 001 | Kimi K2 Turbo Preview |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Code Davinci 001 | Kimi K2 Turbo Preview |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on function calling: Kimi K2 Turbo Preview. 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 Kimi K2 Turbo Preview has no token price sourced yet. Provider availability is 0 tracked routes versus 0. 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 Kimi K2 Turbo Preview 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. 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 Kimi K2 Turbo Preview open source?
Code Davinci 001 is listed under Proprietary. Kimi K2 Turbo Preview 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 function calling, Code Davinci 001 or Kimi K2 Turbo Preview?
Kimi K2 Turbo Preview 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.
When should I pick Code Davinci 001 over Kimi K2 Turbo Preview?
Kimi K2 Turbo Preview 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 Kimi K2 Turbo Preview.
What is the main difference between Code Davinci 001 and Kimi K2 Turbo Preview?
Code Davinci 001 and Kimi K2 Turbo Preview differ most on context, provider coverage, capabilities, or pricing depending on the data currently sourced. Use the specs table first, then validate the model behavior with your own prompts.
Continue comparing
Last reviewed: 2026-05-10. Data sourced from public model cards and provider documentation.