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GLM-5.1 vs GPT-5.5 Pro

GLM-5.1 (2026) and GPT-5.5 Pro (2026) are frontier-tier reasoning models from Zhipu AI and OpenAI. GLM-5.1 ships a 200k-token context window, while GPT-5.5 Pro ships a 1M-token context window. On pricing, GLM-5.1 costs $0.95/1M input tokens versus $30/1M 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-5.1 is ~3058% cheaper at $0.95/1M; pay for GPT-5.5 Pro only for coding workflow support.

Specs

Released2026-03-272026-04-23
Context window200k1M
Parameters744B total, 40-44B active
Architecturemixture of expertsdecoder only
LicenseProprietaryProprietary
Knowledge cutoff--

Pricing and availability

GLM-5.1GPT-5.5 Pro
Input price$0.95/1M tokens$30/1M tokens
Output price$3.15/1M tokens$180/1M tokens
Providers

Capabilities

GLM-5.1GPT-5.5 Pro
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 vision: GPT-5.5 Pro and multimodal input: GPT-5.5 Pro. Both models share reasoning mode, 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-5.1 lists $0.95/1M input and $3.15/1M output tokens, while GPT-5.5 Pro lists $30/1M input and $180/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GLM-5.1 lower by about $73.39 per million blended tokens. Availability is 2 providers versus 1, so concentration risk also matters.

Choose GLM-5.1 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose GPT-5.5 Pro 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. 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-5.1 or GPT-5.5 Pro?

GPT-5.5 Pro supports 1M tokens, while GLM-5.1 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-5.1 or GPT-5.5 Pro?

GLM-5.1 is cheaper on tracked token pricing. GLM-5.1 costs $0.95/1M input and $3.15/1M output tokens. GPT-5.5 Pro costs $30/1M input and $180/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is GLM-5.1 or GPT-5.5 Pro open source?

GLM-5.1 is listed under Proprietary. GPT-5.5 Pro 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-5.1 or GPT-5.5 Pro?

GPT-5.5 Pro 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-5.1 or GPT-5.5 Pro?

GPT-5.5 Pro 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-5.1 and GPT-5.5 Pro?

GLM-5.1 is available on Z.ai and OpenRouter. GPT-5.5 Pro is available on OpenAI API. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Continue comparing

Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.