GLM-5.2 vs GPT-5.4
GLM-5.2 (2026) and GPT-5.4 (2026) are frontier-tier reasoning models from Zhipu AI and OpenAI. GLM-5.2 ships a 1m-token context window, while GPT-5.4 ships a 1.05m-token context window. On SWE-bench Pro, GLM-5.2 leads by 4.4 pts. On pricing, GLM-5.2 costs $1.40/1M input tokens; GPT-5.4 ranges from $2.50 to $5/1M input tokens by tier. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GLM-5.2 is safer overall; choose GPT-5.4 when coding workflow support matters.
Decision scorecard
Local evidence first| Signal | GLM-5.2 | GPT-5.4 |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and long-context analysis | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 1.05m |
| Cheapest output | $4.40/1M tokens | $15/1M tokens |
| Provider routes | 1 tracked | 4 tracked |
| Shared benchmarks | SWE-bench Pro leader | 3 shared |
Decision tradeoffs
- GLM-5.2 holds a shared-benchmark lead on SWE-bench Pro, ahead by 4.4 points.
- GLM-5.2 has the lower cheapest tracked output price at $4.40/1M tokens.
- Local decision data tags GLM-5.2 for Coding, RAG, and Agents.
- GPT-5.4 holds a shared-benchmark lead on Google-Proof Q&A, ahead by 0.8 points.
- GPT-5.4 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.4 has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5.4 uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags GPT-5.4 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.
GLM-5.2
$2,220
Cheapest tracked route/tier: OpenRouter
GPT-5.4
$5,750
Cheapest tracked route/tier: OpenAI API
Estimated monthly gap: $3,530. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-5.4 is $10.60/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.4 adds Vision and Multimodal in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GLM-5.2 is $10.60/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-06-13 | 2026-03-05 |
| Context window | 1m | 1.05m |
| Parameters | 753B total, 40B active | — |
| Architecture | Mixture of Experts | Decoder Only |
| License | MITOSI-approved | Proprietary |
| Openness | Open source | Proprietary |
| Commercial use | Commercial use: permitted | Commercial use: conditional |
| Knowledge cutoff | - | 2025-08 |
Pricing and availability
| Pricing attribute | GLM-5.2 | GPT-5.4 |
|---|---|---|
| Input price | $1.40/1M tokens |
|
| Output price | $4.40/1M tokens |
|
| Providers |
Capabilities
| Capability | GLM-5.2 | GPT-5.4 |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GLM-5.2 | GPT-5.4 |
|---|---|---|
| SWE-bench Pro | 62.1 | 57.7 |
| Google-Proof Q&A | 91.2 | 92.0 |
| Humanity's Last Exam | 40.5 | 41.6 |
Deep dive
On shared benchmark coverage, SWE-bench Pro has GLM-5.2 at 62.1 and GPT-5.4 at 57.7, with GLM-5.2 ahead by 4.4 points; Google-Proof Q&A has GLM-5.2 at 91.2 and GPT-5.4 at 92, with GPT-5.4 ahead by 0.8 points; Humanity's Last Exam has GLM-5.2 at 40.5 and GPT-5.4 at 41.6, with GPT-5.4 ahead by 1.1 points. The largest visible gap is 4.4 points on SWE-bench Pro, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: GPT-5.4 and multimodal input: GPT-5.4. Both models share reasoning mode, function calling, tool use, and structured outputs, 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-5.2 lists $1.40/1M input and $4.40/1M output tokens on the cheapest tracked provider, while GPT-5.4 lists tiered pricing: 0-272,000t is $2.50/1M input and $15/1M output; 272,000t+ is $5/1M input and $22.50/1M output. A 70/30 input-output blend puts GLM-5.2 lower by about $3.95 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 1 providers versus 4, so concentration risk also matters.
Choose GLM-5.2 when coding workflow support and lower input-token cost are central to the workload. Choose GPT-5.4 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.
FAQ
Which has a larger context window, GLM-5.2 or GPT-5.4?
GPT-5.4 supports 1.05m tokens, while GLM-5.2 supports 1m 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.
Which is cheaper, GLM-5.2 or GPT-5.4?
GLM-5.2 lists $1.40/1M input and $4.40/1M output tokens on the cheapest tracked provider. GPT-5.4 lists tiered pricing: 0-272,000t is $2.50/1M input and $15/1M output; 272,000t+ is $5/1M input and $22.50/1M output. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is GLM-5.2 or GPT-5.4 open source?
GLM-5.2 is listed under MIT. GPT-5.4 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-5.2 or GPT-5.4?
GPT-5.4 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-5.2 or GPT-5.4?
GPT-5.4 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.
Where can I run GLM-5.2 and GPT-5.4?
GLM-5.2 is available on OpenRouter. GPT-5.4 is available on OpenAI API, OpenRouter, Vercel AI Gateway, and AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-16. Data sourced from public model cards and provider documentation.