GPT-5.2 Codex vs Qwen3.5-9B
GPT-5.2 Codex (2025) and Qwen3.5-9B (2026) compare a coding-specialized model against a standalone API model. GPT-5.2 Codex ships a not-yet-sourced context window, while Qwen3.5-9B ships a 262k-token context window. On pricing, Qwen3.5-9B costs $0.10/1M 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 Qwen3.5-9B is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | GPT-5.2 Codex | Qwen3.5-9B |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, Agents, and Vision | Coding, RAG, and Agents |
| Context window | — | 262k |
| Cheapest output | $14/1M tokens | $0.15/1M tokens |
| Provider routes | 1 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- 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.
- Qwen3.5-9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-9B has the lower cheapest tracked output price at $0.15/1M tokens.
- Qwen3.5-9B has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen3.5-9B uniquely exposes Structured outputs in local model data.
- Local decision data tags Qwen3.5-9B for Coding, RAG, and Agents.
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
Qwen3.5-9B
$118
Cheapest tracked route/tier: Together AI
Estimated monthly gap: $4,783. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for GPT-5.2 Codex and Qwen3.5-9B; plan for SDK, billing, or endpoint changes.
- Qwen3.5-9B is $13.85/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning and Code execution before moving production traffic.
- Qwen3.5-9B adds Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-9B and GPT-5.2 Codex; plan for SDK, billing, or endpoint changes.
- GPT-5.2 Codex is $13.85/1M 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 Reasoning and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-18 | 2026-03-02 |
| Context window | — | 262k |
| Parameters | — | 9B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Apache 2.0(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| Pricing attribute | GPT-5.2 Codex | Qwen3.5-9B |
|---|---|---|
| Input price | $1.75/1M tokens | $0.10/1M tokens |
| Output price | $14/1M tokens | $0.15/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.2 Codex | Qwen3.5-9B |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | No | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
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: Qwen3.5-9B, 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.
For cost, GPT-5.2 Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider, while Qwen3.5-9B lists $0.10/1M input and $0.15/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen3.5-9B lower by about $5.31 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 Qwen3.5-9B when vision-heavy evaluation, 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 Qwen3.5-9B?
Qwen3.5-9B is cheaper on tracked token pricing. GPT-5.2 Codex costs $1.75/1M input and $14/1M output tokens. Qwen3.5-9B costs $0.10/1M input and $0.15/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.2 Codex or Qwen3.5-9B open source?
GPT-5.2 Codex is listed under Proprietary. Qwen3.5-9B 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 Qwen3.5-9B?
Both GPT-5.2 Codex and Qwen3.5-9B 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 Qwen3.5-9B?
Both GPT-5.2 Codex and Qwen3.5-9B 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 Qwen3.5-9B?
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 Qwen3.5-9B?
GPT-5.2 Codex is available on Vercel AI Gateway. Qwen3.5-9B is available on Together AI, OpenRouter, and Alibaba Cloud PAI-EAS. 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.