GLM-5 Turbo vs GPT-5.2 Codex
GLM-5 Turbo (2026) and GPT-5.2 Codex (2025) compare a standalone API model against a coding-specialized model. GLM-5 Turbo ships a 200k-token context window, while GPT-5.2 Codex ships a not-yet-sourced context window. On pricing, GLM-5 Turbo costs $1.20/1M 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: GLM-5 Turbo is standalone API model, while GPT-5.2 Codex is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | GLM-5 Turbo | GPT-5.2 Codex |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | custom coding agents, code generation, and tool loops |
| Decision fit | RAG, Agents, and Long context | Coding, Agents, and Vision |
| Context window | 200k | — |
| Cheapest output | $4/1M tokens | $14/1M tokens |
| Provider routes | 2 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GLM-5 Turbo has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5 Turbo has the lower cheapest tracked output price at $4/1M tokens.
- GLM-5 Turbo has broader tracked provider coverage for fallback and procurement flexibility.
- GLM-5 Turbo uniquely exposes Structured outputs in local model data.
- Local decision data tags GLM-5 Turbo for RAG, Agents, and Long context.
- GPT-5.2 Codex uniquely exposes Vision, Multimodal, and Code execution in local model data.
- Local decision data tags GPT-5.2 Codex for Coding, Agents, and Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GLM-5 Turbo
$1,960
Cheapest tracked route/tier: OpenRouter
GPT-5.2 Codex
$4,900
Cheapest tracked route/tier: Vercel AI Gateway
Estimated monthly gap: $2,940. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- GPT-5.2 Codex is $10/1M 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 Vision, Multimodal, and Code execution in local capability data.
- Provider overlap exists on Vercel AI Gateway; start route-level A/B tests there.
- GLM-5 Turbo is $10/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Code execution before moving production traffic.
- GLM-5 Turbo adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-01 | 2025-12-18 |
| Context window | 200k | — |
| Parameters | 744B total, 40B active | — |
| Architecture | mixture of experts | decoder only |
| License | MIT(OSI) | Proprietary |
| Openness | Open source | Proprietary |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | 2025-11 | 2025-08 |
Pricing and availability
| Pricing attribute | GLM-5 Turbo | GPT-5.2 Codex |
|---|---|---|
| Input price | $1.20/1M tokens | $1.75/1M tokens |
| Output price | $4/1M tokens | $14/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5 Turbo | GPT-5.2 Codex |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| Code execution | No | Yes |
| 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 vision: GPT-5.2 Codex, multimodal input: GPT-5.2 Codex, structured outputs: GLM-5 Turbo, and code execution: GPT-5.2 Codex. Both models share reasoning mode, 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, GLM-5 Turbo lists $1.20/1M input and $4/1M output tokens on the cheapest tracked provider, while GPT-5.2 Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GLM-5 Turbo lower by about $3.38 per million blended tokens. Availability is 2 providers versus 1, so concentration risk also matters.
Choose GLM-5 Turbo when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose GPT-5.2 Codex when coding workflow support 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, GLM-5 Turbo or GPT-5.2 Codex?
GLM-5 Turbo is cheaper on tracked token pricing. GLM-5 Turbo costs $1.20/1M input and $4/1M output tokens. GPT-5.2 Codex costs $1.75/1M input and $14/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5 Turbo or GPT-5.2 Codex open source?
GLM-5 Turbo is listed under MIT. GPT-5.2 Codex 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, GLM-5 Turbo or GPT-5.2 Codex?
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, GLM-5 Turbo or GPT-5.2 Codex?
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, GLM-5 Turbo or GPT-5.2 Codex?
Both GLM-5 Turbo and GPT-5.2 Codex expose reasoning mode. 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 GLM-5 Turbo and GPT-5.2 Codex?
GLM-5 Turbo is available on OpenRouter and Vercel AI Gateway. GPT-5.2 Codex is available on Vercel AI Gateway. 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.