Code Davinci 002 vs DeepSeek V3.1
Code Davinci 002 (2021) and DeepSeek V3.1 (2026) are agentic coding models from OpenAI and DeepSeek. Code Davinci 002 ships a not-yet-sourced context window, while DeepSeek V3.1 ships a 64K-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.
DeepSeek V3.1 is safer overall; choose Code Davinci 002 when coding workflow support matters.
Specs
| Released | 2021-08-16 | 2026-03-01 |
| Context window | — | 64K |
| Parameters | — | — |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Code Davinci 002 | DeepSeek V3.1 | |
|---|---|---|
| Input price | - | $0.56/1M tokens |
| Output price | - | $1.68/1M tokens |
| Providers | - |
Capabilities
| Code Davinci 002 | DeepSeek V3.1 | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: DeepSeek V3.1, multimodal input: DeepSeek V3.1, structured outputs: DeepSeek V3.1, and code execution: DeepSeek V3.1. 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: Code Davinci 002 has no token price sourced yet and DeepSeek V3.1 has $0.56/1M input tokens. Provider availability is 0 tracked routes versus 6. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Code Davinci 002 when coding workflow support are central to the workload. Choose DeepSeek V3.1 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 002 or DeepSeek V3.1 open source?
Code Davinci 002 is listed under Proprietary. DeepSeek V3.1 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 vision, Code Davinci 002 or DeepSeek V3.1?
DeepSeek V3.1 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 002 or DeepSeek V3.1?
DeepSeek V3.1 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 002 or DeepSeek V3.1?
DeepSeek V3.1 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 002 or DeepSeek V3.1?
DeepSeek V3.1 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 Code Davinci 002 and DeepSeek V3.1?
Code Davinci 002 is available on the tracked providers still being sourced. DeepSeek V3.1 is available on Microsoft Foundry, Fireworks AI, NVIDIA NIM, Together AI, and AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.