LLM Reference

Codex Mini Latest vs Llama 2 70B Chat

Codex Mini Latest (2025) and Llama 2 70B Chat (2023) compare a coding-specialized model against a standalone API model. Codex Mini Latest ships a 200K-token context window, while Llama 2 70B Chat ships a 4K-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: Codex Mini Latest is coding-specialized model, while Llama 2 70B Chat is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalCodex Mini LatestLlama 2 70B Chat
Product typeCoding-specialized modelStandalone API model
Best forcustom coding agents and code generationprovider-routed production
Decision fitCoding and Long contextClassification and JSON / Tool use
Context window200K4K
Cheapest output-$1.50/1M tokens
Provider routes0 tracked14 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Codex Mini Latest when...
  • Codex Mini Latest has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Codex Mini Latest for Coding and Long context.
Choose Llama 2 70B Chat when...
  • Llama 2 70B Chat has broader tracked provider coverage for fallback and procurement flexibility.
  • Llama 2 70B Chat uniquely exposes Structured outputs in local model data.
  • Local decision data tags Llama 2 70B Chat for Classification and JSON / Tool use.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Codex Mini Latest

Unavailable

No complete token price in local provider data

Llama 2 70B Chat

$775

Cheapest tracked route/tier: Databricks Foundation Model Serving

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Codex Mini Latest -> Llama 2 70B Chat
  • No overlapping tracked provider route is sourced for Codex Mini Latest and Llama 2 70B Chat; plan for SDK, billing, or endpoint changes.
  • Llama 2 70B Chat adds Structured outputs in local capability data.
Llama 2 70B Chat -> Codex Mini Latest
  • No overlapping tracked provider route is sourced for Llama 2 70B Chat and Codex Mini Latest; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.

Specs

Specification
Released2025-05-162023-07-18
Context window200K4K
Parameters70B
Architecturedecoder onlydecoder only
LicenseProprietaryOpen Source
Knowledge cutoff2024-06-

Pricing and availability

Pricing attributeCodex Mini LatestLlama 2 70B Chat
Input price-$0.50/1M tokens
Output price-$1.50/1M tokens
Providers-

Capabilities

CapabilityCodex Mini LatestLlama 2 70B Chat
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on structured outputs: Llama 2 70B Chat. 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: Codex Mini Latest has no token price sourced yet and Llama 2 70B Chat has $0.50/1M input tokens. Provider availability is 0 tracked routes versus 14. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Codex Mini Latest when coding workflow support and larger context windows are central to the workload. Choose Llama 2 70B Chat 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

Which has a larger context window, Codex Mini Latest or Llama 2 70B Chat?

Codex Mini Latest supports 200K tokens, while Llama 2 70B Chat supports 4K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Codex Mini Latest or Llama 2 70B Chat open source?

Codex Mini Latest is listed under Proprietary. Llama 2 70B Chat 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 structured outputs, Codex Mini Latest or Llama 2 70B Chat?

Llama 2 70B Chat 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 Codex Mini Latest and Llama 2 70B Chat?

Codex Mini Latest is available on the tracked providers still being sourced. Llama 2 70B Chat is available on Databricks Foundation Model Serving, Microsoft Foundry, GCP Vertex AI, Alibaba Cloud PAI-EAS, and AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Codex Mini Latest over Llama 2 70B Chat?

Treat this as a product-type comparison: Codex Mini Latest is coding-specialized model, while Llama 2 70B Chat 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 Codex Mini Latest; if it depends on provider fit, run the same evaluation with Llama 2 70B Chat.

Continue comparing

Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.