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GPT-5.2 Codex vs Qwen3-Max

GPT-5.2 Codex (2025) and Qwen3-Max (2026) are agentic coding models from OpenAI and Alibaba. GPT-5.2 Codex ships a not-yet-sourced context window, while Qwen3-Max 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.

Qwen3-Max is safer overall; choose GPT-5.2 Codex when coding workflow support matters.

Decision scorecard

Local evidence first
SignalGPT-5.2 CodexQwen3-Max
Decision fitCoding, Agents, and VisionCoding, RAG, and Agents
Context window128K
Cheapest output-$3.9/1M tokens
Provider routes0 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose GPT-5.2 Codex when...
  • GPT-5.2 Codex uniquely exposes Reasoning and Code execution in local model data.
  • Local decision data tags GPT-5.2 Codex for Coding, Agents, and Vision.
Choose Qwen3-Max when...
  • Qwen3-Max has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3-Max has broader tracked provider coverage for fallback and procurement flexibility.
  • Qwen3-Max uniquely exposes Structured outputs in local model data.
  • Local decision data tags Qwen3-Max for Coding, RAG, and Agents.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

GPT-5.2 Codex

Unavailable

No complete token price in local provider data

Qwen3-Max

$1,599

Cheapest tracked route: OpenRouter

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

Switch friction

GPT-5.2 Codex -> Qwen3-Max
  • No overlapping tracked provider route is sourced for GPT-5.2 Codex and Qwen3-Max; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Reasoning and Code execution before moving production traffic.
  • Qwen3-Max adds Structured outputs in local capability data.
Qwen3-Max -> GPT-5.2 Codex
  • No overlapping tracked provider route is sourced for Qwen3-Max and GPT-5.2 Codex; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.
  • GPT-5.2 Codex adds Reasoning and Code execution in local capability data.

Specs

Specification
Released2025-12-182026-01-15
Context window128K
Parameters
Architecturedecoder onlydecoder only
LicenseProprietaryProprietary
Knowledge cutoff2025-082025-12

Pricing and availability

Pricing attributeGPT-5.2 CodexQwen3-Max
Input price-$0.78/1M tokens
Output price-$3.9/1M tokens
Providers-

Capabilities

CapabilityGPT-5.2 CodexQwen3-Max
VisionYesYes
MultimodalYesYes
ReasoningYesNo
Function callingYesYes
Tool useYesYes
Structured outputsNoYes
Code executionYesNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on reasoning mode: GPT-5.2 Codex, structured outputs: Qwen3-Max, and code execution: GPT-5.2 Codex. Both models share vision, multimodal input, 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.

Pricing coverage is uneven: GPT-5.2 Codex has no token price sourced yet and Qwen3-Max has $0.78/1M input tokens. 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 GPT-5.2 Codex when coding workflow support are central to the workload. Choose Qwen3-Max 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. 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 GPT-5.2 Codex or Qwen3-Max open source?

GPT-5.2 Codex is listed under Proprietary. Qwen3-Max is listed under Proprietary. 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 Qwen3-Max?

Both GPT-5.2 Codex and Qwen3-Max expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. 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 Qwen3-Max?

Both GPT-5.2 Codex and Qwen3-Max expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for reasoning mode, GPT-5.2 Codex or Qwen3-Max?

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.

Which is better for function calling, GPT-5.2 Codex or Qwen3-Max?

Both GPT-5.2 Codex and Qwen3-Max expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Where can I run GPT-5.2 Codex and Qwen3-Max?

GPT-5.2 Codex is available on the tracked providers still being sourced. Qwen3-Max is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.