LLM Reference

GPT-5.2 Codex vs Trinity-Large-Preview

GPT-5.2 Codex (2025) and Trinity-Large-Preview (2026) compare a coding-specialized model against a standalone API model. GPT-5.2 Codex ships a not-yet-sourced context window, while Trinity-Large-Preview ships a 128k-token context window. On pricing, Trinity-Large-Preview costs $0.15/1M input tokens versus $1.75/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.

Treat this as a product-type comparison: GPT-5.2 Codex is coding-specialized model, while Trinity-Large-Preview is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.

Decision scorecard

Local evidence first
SignalGPT-5.2 CodexTrinity-Large-Preview
Product typeCoding-specialized modelStandalone API model
Best forcustom coding agents, code generation, and tool loopstool-calling agents and provider-routed production
Decision fitCoding, Agents, and VisionRAG, Agents, and Long context
Context window128k
Cheapest output$14/1M tokens$0.45/1M tokens
Provider routes1 tracked3 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose GPT-5.2 Codex when...
  • GPT-5.2 Codex uniquely exposes Vision, Multimodal, and Reasoning in local model data.
  • Local decision data tags GPT-5.2 Codex for Coding, Agents, and Vision.
Choose Trinity-Large-Preview when...
  • Trinity-Large-Preview has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Trinity-Large-Preview has the lower cheapest tracked output price at $0.45/1M tokens.
  • Trinity-Large-Preview has broader tracked provider coverage for fallback and procurement flexibility.
  • Trinity-Large-Preview uniquely exposes Structured outputs in local model data.
  • Local decision data tags Trinity-Large-Preview for RAG, Agents, and Long context.

Monthly cost at traffic

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

Lower estimate Trinity-Large-Preview

GPT-5.2 Codex

$4,900

Cheapest tracked route/tier: Vercel AI Gateway

Trinity-Large-Preview

$233

Cheapest tracked route/tier: OpenRouter

Estimated monthly gap: $4,668. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GPT-5.2 Codex -> Trinity-Large-Preview
  • Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
  • Trinity-Large-Preview is $13.55/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
  • Trinity-Large-Preview adds Structured outputs in local capability data.
Trinity-Large-Preview -> GPT-5.2 Codex
  • Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
  • GPT-5.2 Codex is $13.55/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Check replacement coverage for Structured outputs before moving production traffic.
  • GPT-5.2 Codex adds Vision, Multimodal, and Reasoning in local capability data.

Specs

Specification
Released2025-12-182026-01-27
Context window128k
Parameters400B
Architecturedecoder onlySparse Mixture of Experts (MoE)
LicenseProprietaryApache 2.0(OSI)
OpennessProprietaryOpen source
Commercial useCommercial use with conditionsCommercial use allowed
Knowledge cutoff2025-08-

Pricing and availability

Pricing attributeGPT-5.2 CodexTrinity-Large-Preview
Input price$1.75/1M tokens$0.15/1M tokens
Output price$14/1M tokens$0.45/1M tokens
Providers

Capabilities

CapabilityGPT-5.2 CodexTrinity-Large-Preview
VisionYesNo
MultimodalYesNo
ReasoningYesNo
Function callingYesYes
Tool useYesYes
Structured outputsNoYes
Code executionYesNo
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 vision: GPT-5.2 Codex, multimodal input: GPT-5.2 Codex, reasoning mode: GPT-5.2 Codex, structured outputs: Trinity-Large-Preview, and code execution: GPT-5.2 Codex. Both models share function calling and tool use, 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.

For cost, GPT-5.2 Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider, while Trinity-Large-Preview lists $0.15/1M input and $0.45/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Trinity-Large-Preview lower by about $5.18 per million blended tokens. Availability is 1 providers versus 3, so concentration risk also matters.

Choose GPT-5.2 Codex when coding workflow support are central to the workload. Choose Trinity-Large-Preview when provider fit, lower input-token cost, 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

Which is cheaper, GPT-5.2 Codex or Trinity-Large-Preview?

Trinity-Large-Preview is cheaper on tracked token pricing. GPT-5.2 Codex costs $1.75/1M input and $14/1M output tokens. Trinity-Large-Preview costs $0.15/1M input and $0.45/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GPT-5.2 Codex or Trinity-Large-Preview open source?

GPT-5.2 Codex is listed under Proprietary. Trinity-Large-Preview 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.

Which is better for vision, GPT-5.2 Codex or Trinity-Large-Preview?

GPT-5.2 Codex 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, GPT-5.2 Codex or Trinity-Large-Preview?

GPT-5.2 Codex 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 reasoning mode, GPT-5.2 Codex or Trinity-Large-Preview?

GPT-5.2 Codex has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run GPT-5.2 Codex and Trinity-Large-Preview?

GPT-5.2 Codex is available on Vercel AI Gateway. Trinity-Large-Preview is available on OpenRouter, Arcee AI, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.