LLM Reference

GPT-5.2 Codex vs Qwen2-7B-Instruct

GPT-5.2 Codex (2025) and Qwen2-7B-Instruct (2024) compare a coding-specialized model against a standalone API model. GPT-5.2 Codex ships a 400k-token context window, while Qwen2-7B-Instruct ships a 128k-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: GPT-5.2 Codex is coding-specialized model, while Qwen2-7B-Instruct 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 CodexQwen2-7B-Instruct
Product typeCoding-specialized modelStandalone API model
Best forcustom coding agents, code generation, and tool loopsgeneral production evaluation
Decision fitCoding, RAG, and AgentsLong context
Context window400k128k
Cheapest output$14/1M tokens-
Provider routes2 tracked1 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 has broader tracked provider coverage for fallback and procurement flexibility.
  • 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 Qwen2-7B-Instruct when...
  • Local decision data tags Qwen2-7B-Instruct for Long context.

Monthly cost at traffic

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

GPT-5.2 Codex

$4,900

Cheapest tracked route/tier: Vercel AI Gateway

Qwen2-7B-Instruct

Unavailable

No complete token price in local provider data

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

Switch friction

GPT-5.2 Codex -> Qwen2-7B-Instruct
  • No overlapping tracked provider route is sourced for GPT-5.2 Codex and Qwen2-7B-Instruct; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
Qwen2-7B-Instruct -> GPT-5.2 Codex
  • No overlapping tracked provider route is sourced for Qwen2-7B-Instruct and GPT-5.2 Codex; plan for SDK, billing, or endpoint changes.
  • GPT-5.2 Codex adds Vision, Multimodal, and Reasoning in local capability data.

Specs

Specification
Released2025-12-182024-06-07
Context window400k128k
Parameters7B
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 CodexQwen2-7B-Instruct
Input price$1.75/1M tokens-
Output price$14/1M tokens-
Providers

Capabilities

CapabilityGPT-5.2 CodexQwen2-7B-Instruct
VisionYesNo
MultimodalYesNo
ReasoningYesNo
Function callingYesNo
Tool useYesNo
Structured outputsYesNo
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, structured outputs: GPT-5.2 Codex, and code execution: GPT-5.2 Codex. 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: GPT-5.2 Codex has $1.75/1M input tokens and Qwen2-7B-Instruct has no token price sourced yet. Provider availability is 2 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, larger context windows, and broader provider choice are central to the workload. Choose Qwen2-7B-Instruct when provider fit 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 has a larger context window, GPT-5.2 Codex or Qwen2-7B-Instruct?

GPT-5.2 Codex supports 400k tokens, while Qwen2-7B-Instruct 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.

Is GPT-5.2 Codex or Qwen2-7B-Instruct open source?

GPT-5.2 Codex is listed under Proprietary. Qwen2-7B-Instruct 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 Qwen2-7B-Instruct?

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 Qwen2-7B-Instruct?

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 Qwen2-7B-Instruct?

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 Qwen2-7B-Instruct?

GPT-5.2 Codex is available on Vercel AI Gateway and OpenAI API. Qwen2-7B-Instruct is available on NVIDIA NIM. 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: 2026-06-30. Data sourced from public model cards and provider documentation.