GLM 4.5V vs GPT-5.3-Codex
GLM 4.5V (2026) and GPT-5.3-Codex (2026) are agentic coding models from Tsinghua Knowledge Engineering Group (THUDM) and OpenAI. GLM 4.5V ships a 64K-token context window, while GPT-5.3-Codex ships a 400K-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-5.3-Codex fits 6x more tokens; pick it for long-context work and GLM 4.5V for tighter calls.
Decision scorecard
Local evidence first| Signal | GLM 4.5V | GPT-5.3-Codex |
|---|---|---|
| Decision fit | Agents, Vision, and JSON / Tool use | Coding, RAG, and Agents |
| Context window | 64K | 400K |
| Cheapest output | - | $14/1M tokens |
| Provider routes | 0 tracked | 2 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GLM 4.5V uniquely exposes Multimodal in local model data.
- Local decision data tags GLM 4.5V for Agents, Vision, and JSON / Tool use.
- GPT-5.3-Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.3-Codex has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5.3-Codex uniquely exposes Reasoning, Structured outputs, and Code execution in local model data.
- Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
GLM 4.5V
Unavailable
No complete token price in local provider data
GPT-5.3-Codex
$4,900
Cheapest tracked route: OpenRouter
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for GLM 4.5V and GPT-5.3-Codex; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Multimodal before moving production traffic.
- GPT-5.3-Codex adds Reasoning, Structured outputs, and Code execution in local capability data.
- No overlapping tracked provider route is sourced for GPT-5.3-Codex and GLM 4.5V; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning, Structured outputs, and Code execution before moving production traffic.
- GLM 4.5V adds Multimodal in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-01-01 | 2026-02-05 |
| Context window | 64K | 400K |
| Parameters | — | — |
| Architecture | moe | decoder only |
| License | Proprietary | Proprietary |
| Knowledge cutoff | - | 2025-08 |
Pricing and availability
| Pricing attribute | GLM 4.5V | GPT-5.3-Codex |
|---|---|---|
| Input price | - | $1.75/1M tokens |
| Output price | - | $14/1M tokens |
| Providers | - |
Capabilities
| Capability | GLM 4.5V | GPT-5.3-Codex |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | No |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | No | Yes |
| Code execution | No | Yes |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on multimodal input: GLM 4.5V, reasoning mode: GPT-5.3-Codex, structured outputs: GPT-5.3-Codex, and code execution: GPT-5.3-Codex. Both models share vision, 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: GLM 4.5V has no token price sourced yet and GPT-5.3-Codex has $1.75/1M input tokens. Provider availability is 0 tracked routes versus 2. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GLM 4.5V when vision-heavy evaluation are central to the workload. Choose GPT-5.3-Codex when coding workflow support, larger context windows, 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, GLM 4.5V or GPT-5.3-Codex?
GPT-5.3-Codex supports 400K tokens, while GLM 4.5V supports 64K 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 GLM 4.5V or GPT-5.3-Codex open source?
GLM 4.5V is listed under Proprietary. GPT-5.3-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 4.5V or GPT-5.3-Codex?
Both GLM 4.5V and GPT-5.3-Codex 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, GLM 4.5V or GPT-5.3-Codex?
GLM 4.5V 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 4.5V or GPT-5.3-Codex?
GPT-5.3-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 GLM 4.5V and GPT-5.3-Codex?
GLM 4.5V is available on the tracked providers still being sourced. GPT-5.3-Codex is available on OpenRouter and OpenAI API. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.