GPT-5.2 Codex vs Qwen3-105B
GPT-5.2 Codex (2025) and Qwen3-105B (2025) are agentic coding models from OpenAI and Alibaba. GPT-5.2 Codex ships a not-yet-sourced context window, while Qwen3-105B 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.
GPT-5.2 Codex is safer overall; choose Qwen3-105B when provider fit matters.
Decision scorecard
Local evidence first| Signal | GPT-5.2 Codex | Qwen3-105B |
|---|---|---|
| Decision fit | Coding, Agents, and Vision | RAG, Agents, and Long context |
| Context window | — | 128k |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- 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.
- Qwen3-105B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Qwen3-105B for RAG, Agents, and Long context.
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
Qwen3-105B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for GPT-5.2 Codex and Qwen3-105B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
- No overlapping tracked provider route is sourced for Qwen3-105B 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 | ||
|---|---|---|
| Released | 2025-12-18 | 2025-12-15 |
| Context window | — | 128k |
| Parameters | — | 105B |
| Architecture | decoder only | - |
| License | Proprietary | Open Source |
| Knowledge cutoff | 2025-08 | 2025-02 |
Pricing and availability
| Pricing attribute | GPT-5.2 Codex | Qwen3-105B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | GPT-5.2 Codex | Qwen3-105B |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | No | No |
| Code execution | Yes | No |
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, 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.
Pricing coverage is uneven: GPT-5.2 Codex has no token price sourced yet and Qwen3-105B has no token price sourced yet. Provider availability is 0 tracked routes versus 0. 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 Qwen3-105B 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. 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 Qwen3-105B open source?
GPT-5.2 Codex is listed under Proprietary. Qwen3-105B 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 vision, GPT-5.2 Codex or Qwen3-105B?
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 Qwen3-105B?
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 Qwen3-105B?
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 Qwen3-105B?
Both GPT-5.2 Codex and Qwen3-105B 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.
When should I pick GPT-5.2 Codex over Qwen3-105B?
GPT-5.2 Codex is safer overall; choose Qwen3-105B when provider fit matters. If your workload also depends on coding workflow support, start with GPT-5.2 Codex; if it depends on provider fit, run the same evaluation with Qwen3-105B.
Continue comparing
Last reviewed: 2026-05-10. Data sourced from public model cards and provider documentation.