GLM-5 vs Qwen3-Max
GLM-5 (2026) and Qwen3-Max (2026) are frontier reasoning models from Zhipu AI and Alibaba. GLM-5 ships a 200k-token context window, while Qwen3-Max ships a 128K-token context window. On SWE-bench Verified, Qwen3-Max leads by 1 pts. On pricing, GLM-5 costs $0.72/1M input tokens versus $0.78/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
GLM-5 is safer overall; choose Qwen3-Max when vision-heavy evaluation matters.
Specs
Pricing and availability
| GLM-5 | Qwen3-Max | |
|---|---|---|
| Input price | $0.72/1M tokens | $0.78/1M tokens |
| Output price | $2.3/1M tokens | $3.9/1M tokens |
| Providers |
Capabilities
| GLM-5 | Qwen3-Max | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | GLM-5 | Qwen3-Max |
|---|---|---|
| SWE-bench Verified | 77.8 | 78.8 |
| τ-bench | 82.1 | 76.8 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has GLM-5 at 77.8 and Qwen3-Max at 78.8, with Qwen3-Max ahead by 1 points; τ-bench has GLM-5 at 82.1 and Qwen3-Max at 76.8, with GLM-5 ahead by 5.3 points. The largest visible gap is 5.3 points on τ-bench, 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: Qwen3-Max, multimodal input: Qwen3-Max, and reasoning mode: GLM-5. 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 $0.72/1M input and $2.3/1M output tokens, while Qwen3-Max lists $0.78/1M input and $3.9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GLM-5 lower by about $0.52 per million blended tokens. Availability is 5 providers versus 1, so concentration risk also matters.
Choose GLM-5 when reasoning depth, larger context windows, and lower input-token cost are central to the workload. Choose Qwen3-Max when vision-heavy evaluation 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 Qwen3-Max?
GLM-5 supports 200k tokens, while Qwen3-Max supports 128K 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 Qwen3-Max?
GLM-5 is cheaper on tracked token pricing. GLM-5 costs $0.72/1M input and $2.3/1M output tokens. Qwen3-Max costs $0.78/1M input and $3.9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5 or Qwen3-Max open source?
GLM-5 is listed under MIT. Qwen3-Max 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 Qwen3-Max?
Qwen3-Max 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 Qwen3-Max?
Qwen3-Max 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 Qwen3-Max?
GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. Qwen3-Max is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.