LLM Reference

GPT-5.2 Codex vs Qwen3-235B-A22B

GPT-5.2 Codex (2025) and Qwen3-235B-A22B (2025) compare a coding-specialized model against a standalone API model. GPT-5.2 Codex ships a 400k-token context window, while Qwen3-235B-A22B ships a 128k-token context window. On pricing, Qwen3-235B-A22B costs $0.09/1M 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 Qwen3-235B-A22B 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 CodexQwen3-235B-A22B
Product typeCoding-specialized modelStandalone API model
Best forcustom coding agents, code generation, and tool loopsprovider-routed production
Decision fitCoding, RAG, and AgentsCoding, RAG, and Long context
Context window400k128k
Cheapest output$14/1M tokens$0.58/1M tokens
Provider routes2 tracked5 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose GPT-5.2 Codex when...
  • GPT-5.2 Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • GPT-5.2 Codex uniquely exposes Vision, Multimodal, and Reasoning in local model data.
  • Local decision data tags GPT-5.2 Codex for Coding, RAG, and Agents.
Choose Qwen3-235B-A22B when...
  • Qwen3-235B-A22B has the lower cheapest tracked output price at $0.58/1M tokens.
  • Qwen3-235B-A22B has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Qwen3-235B-A22B for Coding, RAG, 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 Qwen3-235B-A22B

GPT-5.2 Codex

$4,900

Cheapest tracked route/tier: Vercel AI Gateway

Qwen3-235B-A22B

$217

Cheapest tracked route/tier: Novita AI

Estimated monthly gap: $4,683. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

GPT-5.2 Codex -> Qwen3-235B-A22B
  • No overlapping tracked provider route is sourced for GPT-5.2 Codex and Qwen3-235B-A22B; plan for SDK, billing, or endpoint changes.
  • Qwen3-235B-A22B is $13.42/1M 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.
Qwen3-235B-A22B -> GPT-5.2 Codex
  • No overlapping tracked provider route is sourced for Qwen3-235B-A22B and GPT-5.2 Codex; plan for SDK, billing, or endpoint changes.
  • GPT-5.2 Codex is $13.42/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • GPT-5.2 Codex adds Vision, Multimodal, and Reasoning in local capability data.

Specs

Specification
Released2025-12-182025-04-29
Context window400k128k
Parameters235B
ArchitectureDecoder OnlyDecoder Only
LicenseProprietaryApache 2.0OSI-approved
OpennessProprietaryOpen source
WeightsNot releasedUnknown
CodeUnknownUnknown
Commercial useCommercial use: conditionalCommercial use: permitted
Knowledge cutoff2025-08-

Pricing and availability

Pricing attributeGPT-5.2 CodexQwen3-235B-A22B
Input price$1.75/1M tokens$0.09/1M tokens
Output price$14/1M tokens$0.58/1M tokens
Providers

Capabilities

CapabilityGPT-5.2 CodexQwen3-235B-A22B
VisionYesNo
MultimodalYesNo
ReasoningYesNo
Function callingYesNo
Tool useYesNo
Structured outputsYesYes
Code executionYesNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available 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, function calling: GPT-5.2 Codex, tool use: GPT-5.2 Codex, and code execution: GPT-5.2 Codex. Both models share structured outputs, 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 Qwen3-235B-A22B lists $0.09/1M input and $0.58/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3-235B-A22B lower by about $5.19 per million blended tokens. Availability is 2 providers versus 5, so concentration risk also matters.

Choose GPT-5.2 Codex when coding workflow support and larger context windows are central to the workload. Choose Qwen3-235B-A22B 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.

FAQ

Which has a larger context window, GPT-5.2 Codex or Qwen3-235B-A22B?

GPT-5.2 Codex supports 400k tokens, while Qwen3-235B-A22B supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is cheaper, GPT-5.2 Codex or Qwen3-235B-A22B?

Qwen3-235B-A22B is cheaper on tracked token pricing. GPT-5.2 Codex costs $1.75/1M input and $14/1M output tokens. Qwen3-235B-A22B costs $0.09/1M input and $0.58/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GPT-5.2 Codex or Qwen3-235B-A22B open source?

GPT-5.2 Codex is listed under Proprietary. Qwen3-235B-A22B 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 Qwen3-235B-A22B?

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 Qwen3-235B-A22B?

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.

Where can I run GPT-5.2 Codex and Qwen3-235B-A22B?

GPT-5.2 Codex is available on Vercel AI Gateway and OpenAI API. Qwen3-235B-A22B is available on Fireworks AI, AWS Bedrock, OpenRouter, Venice AI, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-30. Data sourced from public model cards and provider documentation.