Code Davinci 002 vs Gemma 4 E2B
Code Davinci 002 (2021) and Gemma 4 E2B (2026) are agentic coding models from OpenAI and Google DeepMind. Code Davinci 002 ships a not-yet-sourced context window, while Gemma 4 E2B 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.
Gemma 4 E2B is safer overall; choose Code Davinci 002 when coding workflow support matters.
Decision scorecard
Local evidence first| Signal | Code Davinci 002 | Gemma 4 E2B |
|---|---|---|
| Decision fit | Coding | RAG, Agents, and Long context |
| Context window | — | 128k |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Code Davinci 002 for Coding.
- Gemma 4 E2B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemma 4 E2B has broader tracked provider coverage for fallback and procurement flexibility.
- Gemma 4 E2B uniquely exposes Multimodal and Function calling in local model data.
- Local decision data tags Gemma 4 E2B 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 002
Unavailable
No complete token price in local provider data
Gemma 4 E2B
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 002 and Gemma 4 E2B; plan for SDK, billing, or endpoint changes.
- Gemma 4 E2B adds Multimodal and Function calling in local capability data.
- No overlapping tracked provider route is sourced for Gemma 4 E2B and Code Davinci 002; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Multimodal and Function calling before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2021-08-16 | 2026-03-31 |
| Context window | — | 128k |
| Parameters | — | 2B |
| Architecture | decoder only | - |
| License | Proprietary | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Code Davinci 002 | Gemma 4 E2B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Code Davinci 002 | Gemma 4 E2B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | Yes |
| 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 multimodal input: Gemma 4 E2B and function calling: Gemma 4 E2B. 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 Gemma 4 E2B 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 Code Davinci 002 when coding workflow support are central to the workload. Choose Gemma 4 E2B 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 002 or Gemma 4 E2B open source?
Code Davinci 002 is listed under Proprietary. Gemma 4 E2B 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 multimodal input, Code Davinci 002 or Gemma 4 E2B?
Gemma 4 E2B 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 function calling, Code Davinci 002 or Gemma 4 E2B?
Gemma 4 E2B 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.
Where can I run Code Davinci 002 and Gemma 4 E2B?
Code Davinci 002 is available on the tracked providers still being sourced. Gemma 4 E2B is available on GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Code Davinci 002 over Gemma 4 E2B?
Gemma 4 E2B is safer overall; choose Code Davinci 002 when coding workflow support matters. If your workload also depends on coding workflow support, start with Code Davinci 002; if it depends on provider fit, run the same evaluation with Gemma 4 E2B.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.