GLM-5 vs GPT-4.1
GLM-5 (2026) and GPT-4.1 (2025) are frontier reasoning models from Zhipu AI and OpenAI. GLM-5 ships a 200k-token context window, while GPT-4.1 ships a 1.05m-token context window. On SWE-bench Verified, GLM-5 leads by 23.2 pts. On pricing, GLM-5 costs $0.60/1M input tokens versus $2/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GLM-5 is ~233% cheaper at $0.60/1M; pay for GPT-4.1 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | GLM-5 | GPT-4.1 |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and provider-routed production | multimodal apps, tool-calling agents, and long-context analysis |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 200k | 1.05m |
| Cheapest output | $2.08/1M tokens | $8/1M tokens |
| Provider routes | 7 tracked | 4 tracked |
| Shared benchmarks | SWE-bench Verified leader | 1 rows |
Decision tradeoffs
- GLM-5 leads the largest shared benchmark signal on SWE-bench Verified by 23.2 points.
- GLM-5 has the lower cheapest tracked output price at $2.08/1M tokens.
- GLM-5 has broader tracked provider coverage for fallback and procurement flexibility.
- GLM-5 uniquely exposes Reasoning in local model data.
- Local decision data tags GLM-5 for Coding, RAG, and Agents.
- GPT-4.1 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-4.1 uniquely exposes Vision, Multimodal, and Code execution in local model data.
- Local decision data tags GPT-4.1 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
$1,000
Cheapest tracked route/tier: OpenRouter
GPT-4.1
$3,600
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $2,600. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- GPT-4.1 is $5.92/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Reasoning before moving production traffic.
- GPT-4.1 adds Vision, Multimodal, and Code execution in local capability data.
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- GLM-5 is $5.92/1M 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 adds Reasoning in local capability data.
Specs
Pricing and availability
| Pricing attribute | GLM-5 | GPT-4.1 |
|---|---|---|
| Input price | $0.60/1M tokens | $2/1M tokens |
| Output price | $2.08/1M tokens | $8/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5 | GPT-4.1 |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GLM-5 | GPT-4.1 |
|---|---|---|
| SWE-bench Verified | 77.8 | 54.6 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has GLM-5 at 77.8 and GPT-4.1 at 54.6, with GLM-5 ahead by 23.2 points. The largest visible gap is 23.2 points on SWE-bench Verified, 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-4.1, multimodal input: GPT-4.1, reasoning mode: GLM-5, and code execution: GPT-4.1. Both models share 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 lists $0.60/1M input and $2.08/1M output tokens on the cheapest tracked provider, while GPT-4.1 lists $2/1M input and $8/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GLM-5 lower by about $2.76 per million blended tokens. Availability is 7 providers versus 4, so concentration risk also matters.
Choose GLM-5 when reasoning depth, lower input-token cost, and broader provider choice are central to the workload. Choose GPT-4.1 when coding workflow support and larger context windows 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 or GPT-4.1?
GPT-4.1 supports 1.05m tokens, while GLM-5 supports 200k 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 or GPT-4.1?
GLM-5 is cheaper on tracked token pricing. GLM-5 costs $0.60/1M input and $2.08/1M output tokens. GPT-4.1 costs $2/1M input and $8/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5 or GPT-4.1 open source?
GLM-5 is listed under MIT. GPT-4.1 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 or GPT-4.1?
GPT-4.1 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 or GPT-4.1?
GPT-4.1 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 and GPT-4.1?
GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. GPT-4.1 is available on OpenRouter, Azure OpenAI, OpenAI API, and 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.