LLM Reference

GLM-5 vs Qwen2.5-72B

GLM-5 (2026) and Qwen2.5-72B (2025) are frontier reasoning models from Zhipu AI and Alibaba. GLM-5 ships a 200k-token context window, while Qwen2.5-72B ships a 128k-token context window. On MMLU PRO, GLM-5 leads by 14 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.

GLM-5 is safer overall; choose Qwen2.5-72B when provider fit matters.

Decision scorecard

Local evidence first
SignalGLM-5Qwen2.5-72B
Best forreasoning-heavy apps, tool-calling agents, and provider-routed productiontool-calling agents
Decision fitCoding, RAG, and AgentsRAG, Agents, and Long context
Context window200k128k
Cheapest output$2.08/1M tokens-
Provider routes7 tracked0 tracked
Shared benchmarksMMLU PRO leader1 rows

Decision tradeoffs

Choose GLM-5 when...
  • GLM-5 holds a shared-benchmark lead on MMLU PRO, ahead by 14 points.
  • GLM-5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • GLM-5 has broader tracked provider coverage for fallback and procurement flexibility.
  • GLM-5 uniquely exposes Reasoning and Structured outputs in local model data.
  • Local decision data tags GLM-5 for Coding, RAG, and Agents.
Choose Qwen2.5-72B when...
  • Local decision data tags Qwen2.5-72B for RAG, Agents, and Long context.

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

Qwen2.5-72B

Unavailable

No complete token price in local provider data

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

GLM-5 -> Qwen2.5-72B
  • No overlapping tracked provider route is sourced for GLM-5 and Qwen2.5-72B; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Reasoning and Structured outputs before moving production traffic.
Qwen2.5-72B -> GLM-5
  • No overlapping tracked provider route is sourced for Qwen2.5-72B and GLM-5; plan for SDK, billing, or endpoint changes.
  • GLM-5 adds Reasoning and Structured outputs in local capability data.

Specs

Specification
Released2026-02-112025-10-10
Context window200k128k
Parameters744B total, 40B active72B
Architecturemixture of experts-
LicenseMIT(OSI)Apache 2.0(OSI)
OpennessOpen sourceOpen source
Commercial useCommercial use allowedCommercial use allowed
Knowledge cutoff2025-112024-09

Pricing and availability

Pricing attributeGLM-5Qwen2.5-72B
Input price$0.60/1M tokens-
Output price$2.08/1M tokens-
Providers-

Capabilities

CapabilityGLM-5Qwen2.5-72B
VisionNoNo
MultimodalNoNo
ReasoningYesNo
Function callingYesYes
Tool useYesYes
Structured outputsYesNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkGLM-5Qwen2.5-72B
MMLU PRO86.072.0

Deep dive

On shared benchmark coverage, MMLU PRO has GLM-5 at 86 and Qwen2.5-72B at 72, with GLM-5 ahead by 14 points. The largest visible gap is 14 points on MMLU 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 reasoning mode: GLM-5 and structured outputs: GLM-5. Both models share 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-5 has $0.60/1M input tokens and Qwen2.5-72B has no token price sourced yet. Provider availability is 7 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose GLM-5 when reasoning depth, larger context windows, and broader provider choice are central to the workload. Choose Qwen2.5-72B when provider fit 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.

FAQ

Which has a larger context window, GLM-5 or Qwen2.5-72B?

GLM-5 supports 200k tokens, while Qwen2.5-72B 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.

Is GLM-5 or Qwen2.5-72B open source?

GLM-5 is listed under MIT. Qwen2.5-72B 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 or Qwen2.5-72B?

GLM-5 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 or Qwen2.5-72B?

Both GLM-5 and Qwen2.5-72B expose function calling. 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 tool use, GLM-5 or Qwen2.5-72B?

Both GLM-5 and Qwen2.5-72B expose tool use. 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.

Where can I run GLM-5 and Qwen2.5-72B?

GLM-5 is available on Fireworks AI, OpenRouter, Together AI, GCP Vertex AI, and NVIDIA NIM. Qwen2.5-72B is available on the tracked providers still being sourced. 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.