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Code Cushman 001 vs GLM-5.1

Code Cushman 001 (2021) and GLM-5.1 (2026) are agentic coding models from OpenAI and Zhipu AI. Code Cushman 001 ships a not-yet-sourced context window, while GLM-5.1 ships a 200k-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

GLM-5.1 is safer overall; choose Code Cushman 001 when coding workflow support matters.

Specs

Released2021-11-032026-03-27
Context window200k
Parameters744B total, 40-44B active
Architecturedecoder onlymixture of experts
LicenseProprietaryProprietary
Knowledge cutoff--

Pricing and availability

Code Cushman 001GLM-5.1
Input price-$0.95/1M tokens
Output price-$3.15/1M tokens
Providers-

Capabilities

Code Cushman 001GLM-5.1
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-5.1, function calling: GLM-5.1, tool use: GLM-5.1, structured outputs: GLM-5.1, and code execution: GLM-5.1. Both models share the core language-model surface, 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: Code Cushman 001 has no token price sourced yet and GLM-5.1 has $0.95/1M input tokens. Provider availability is 0 tracked routes versus 2. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Code Cushman 001 when coding workflow support are central to the workload. Choose GLM-5.1 when coding workflow support 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Is Code Cushman 001 or GLM-5.1 open source?

Code Cushman 001 is listed under Proprietary. GLM-5.1 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 reasoning mode, Code Cushman 001 or GLM-5.1?

GLM-5.1 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, Code Cushman 001 or GLM-5.1?

GLM-5.1 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.

Which is better for tool use, Code Cushman 001 or GLM-5.1?

GLM-5.1 has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for structured outputs, Code Cushman 001 or GLM-5.1?

GLM-5.1 has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Code Cushman 001 and GLM-5.1?

Code Cushman 001 is available on the tracked providers still being sourced. GLM-5.1 is available on Z.ai and 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.