GLM-5 Turbo vs Qwen2.5-72B-Instruct
GLM-5 Turbo (2026) and Qwen2.5-72B-Instruct (2024) are frontier reasoning models from Zhipu AI and Alibaba. GLM-5 Turbo ships a 200k-token context window, while Qwen2.5-72B-Instruct ships a 128K-token context window. On pricing, Qwen2.5-72B-Instruct costs $0.12/1M input tokens versus $1.2/1M 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.
Qwen2.5-72B-Instruct is ~900% cheaper at $0.12/1M; pay for GLM-5 Turbo only for reasoning depth.
Specs
| Released | 2026-03-01 | 2024-06-07 |
| Context window | 200k | 128K |
| Parameters | 744B total, 40B active | 72.7B |
| Architecture | mixture of experts | decoder only |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| GLM-5 Turbo | Qwen2.5-72B-Instruct | |
|---|---|---|
| Input price | $1.2/1M tokens | $0.12/1M tokens |
| Output price | $4/1M tokens | $0.39/1M tokens |
| Providers |
Capabilities
| GLM-5 Turbo | Qwen2.5-72B-Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: GLM-5 Turbo, function calling: GLM-5 Turbo, and tool use: GLM-5 Turbo. Both models share 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 Turbo lists $1.2/1M input and $4/1M output tokens, while Qwen2.5-72B-Instruct lists $0.12/1M input and $0.39/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen2.5-72B-Instruct lower by about $1.84 per million blended tokens. Availability is 1 providers versus 7, so concentration risk also matters.
Choose GLM-5 Turbo when reasoning depth and larger context windows are central to the workload. Choose Qwen2.5-72B-Instruct when provider fit, lower input-token cost, 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.
FAQ
Which has a larger context window, GLM-5 Turbo or Qwen2.5-72B-Instruct?
GLM-5 Turbo supports 200k tokens, while Qwen2.5-72B-Instruct 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 Turbo or Qwen2.5-72B-Instruct?
Qwen2.5-72B-Instruct is cheaper on tracked token pricing. GLM-5 Turbo costs $1.2/1M input and $4/1M output tokens. Qwen2.5-72B-Instruct costs $0.12/1M input and $0.39/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5 Turbo or Qwen2.5-72B-Instruct open source?
GLM-5 Turbo is listed under Proprietary. Qwen2.5-72B-Instruct is listed under Apache 2.0. 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 reasoning mode, GLM-5 Turbo or Qwen2.5-72B-Instruct?
GLM-5 Turbo 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.
Which is better for function calling, GLM-5 Turbo or Qwen2.5-72B-Instruct?
GLM-5 Turbo has the clearer documented function calling signal in this comparison. If function calling 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 Turbo and Qwen2.5-72B-Instruct?
GLM-5 Turbo is available on OpenRouter. Qwen2.5-72B-Instruct is available on DeepInfra, OpenRouter, Fireworks AI, Novita AI, and Chutes AI. 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.