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Code Davinci 001 vs Mixtral 8x7B

Code Davinci 001 (2021) and Mixtral 8x7B (2023) are agentic coding models from OpenAI and MistralAI. Code Davinci 001 ships a not-yet-sourced context window, while Mixtral 8x7B ships a 32K-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.

Mixtral 8x7B is safer overall; choose Code Davinci 001 when coding workflow support matters.

Specs

Released2021-07-012023-12-11
Context window32K
Parameters8x7B
Architecturedecoder onlymixture of experts
LicenseProprietaryApache 2.0
Knowledge cutoff-2023-12

Pricing and availability

Code Davinci 001Mixtral 8x7B
Input price-$0.15/1M tokens
Output price-$0.45/1M tokens
Providers-

Capabilities

Code Davinci 001Mixtral 8x7B
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 is close: both models cover the core production surface. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

Pricing coverage is uneven: Code Davinci 001 has no token price sourced yet and Mixtral 8x7B has $0.15/1M input tokens. Provider availability is 0 tracked routes versus 18. 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 Mixtral 8x7B 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 001 or Mixtral 8x7B open source?

Code Davinci 001 is listed under Proprietary. Mixtral 8x7B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Where can I run Code Davinci 001 and Mixtral 8x7B?

Code Davinci 001 is available on the tracked providers still being sourced. Mixtral 8x7B is available on Databricks Foundation Model Serving, NVIDIA NIM, GCP Vertex AI, AWS Bedrock, and OctoAI API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Code Davinci 001 over Mixtral 8x7B?

Mixtral 8x7B 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 Mixtral 8x7B.

What is the main difference between Code Davinci 001 and Mixtral 8x7B?

Code Davinci 001 and Mixtral 8x7B 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: 2026-04-24. Data sourced from public model cards and provider documentation.