Code Davinci 001 vs Llama 4 Maverick 17B Instruct FP8
Code Davinci 001 (2021) and Llama 4 Maverick 17B Instruct FP8 (2025) compare a coding-specialized model against a standalone API model. Code Davinci 001 ships a not-yet-sourced context window, while Llama 4 Maverick 17B Instruct FP8 ships a 1m-token context window. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: Code Davinci 001 is coding-specialized model, while Llama 4 Maverick 17B Instruct FP8 is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | Code Davinci 001 | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents and code generation | multimodal apps, long-context analysis, and provider-routed production |
| Decision fit | Coding | Coding, RAG, and Agents |
| Context window | — | 1m |
| Cheapest output | - | $0.60/1M tokens |
| Provider routes | 0 tracked | 10 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Code Davinci 001 for Coding.
- Llama 4 Maverick 17B Instruct FP8 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 4 Maverick 17B Instruct FP8 has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 4 Maverick 17B Instruct FP8 uniquely exposes Vision, Multimodal, and Structured outputs in local model data.
- Local decision data tags Llama 4 Maverick 17B Instruct FP8 for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Code Davinci 001
Unavailable
No complete token price in local provider data
Llama 4 Maverick 17B Instruct FP8
$270
Cheapest tracked route/tier: OpenRouter
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 Llama 4 Maverick 17B Instruct FP8; plan for SDK, billing, or endpoint changes.
- Llama 4 Maverick 17B Instruct FP8 adds Vision, Multimodal, and Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Llama 4 Maverick 17B Instruct FP8 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 | 2025-04-05 |
| Context window | — | 1m |
| Parameters | — | 400B (17B active) |
| Architecture | decoder only | mixture of experts |
| License | Proprietary | Llama 4 Community |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | - | 2024-08 |
Pricing and availability
| Pricing attribute | Code Davinci 001 | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Input price | - | $0.15/1M tokens |
| Output price | - | $0.60/1M tokens |
| Providers | - |
Capabilities
| Capability | Code Davinci 001 | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Llama 4 Maverick 17B Instruct FP8, multimodal input: Llama 4 Maverick 17B Instruct FP8, and structured outputs: Llama 4 Maverick 17B Instruct FP8. 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 Llama 4 Maverick 17B Instruct FP8 has $0.15/1M input tokens. Provider availability is 0 tracked routes versus 10. 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 Llama 4 Maverick 17B Instruct FP8 when vision-heavy evaluation 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.
FAQ
Is Code Davinci 001 or Llama 4 Maverick 17B Instruct FP8 open source?
Code Davinci 001 is listed under Proprietary. Llama 4 Maverick 17B Instruct FP8 is listed under Llama 4 Community. 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 Llama 4 Maverick 17B Instruct FP8?
Llama 4 Maverick 17B Instruct FP8 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.
Which is better for multimodal input, Code Davinci 001 or Llama 4 Maverick 17B Instruct FP8?
Llama 4 Maverick 17B Instruct FP8 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 Llama 4 Maverick 17B Instruct FP8?
Llama 4 Maverick 17B Instruct FP8 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 Llama 4 Maverick 17B Instruct FP8?
Code Davinci 001 is available on the tracked providers still being sourced. Llama 4 Maverick 17B Instruct FP8 is available on Microsoft Foundry, Together AI, OpenRouter, Fireworks AI, and DeepInfra. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Code Davinci 001 over Llama 4 Maverick 17B Instruct FP8?
Treat this as a product-type comparison: Code Davinci 001 is coding-specialized model, while Llama 4 Maverick 17B Instruct FP8 is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive. If your workload also depends on coding workflow support, start with Code Davinci 001; if it depends on vision-heavy evaluation, run the same evaluation with Llama 4 Maverick 17B Instruct FP8.
Continue comparing
Last reviewed: 2026-06-07. Data sourced from public model cards and provider documentation.