GLM 5.1 vs GPT-5.2

Z.ai · China  |  OpenAI · US · Updated June 2026

Quick verdict

Pick GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). Pick GPT-5.2 for strong all-round reasoning or reliable structured output. Choose GLM 5.1 if you need self-hosting or data privacy; GPT-5.2 if you want a managed API.

GLM 5.1 (Z.ai, China) and GPT-5.2 (OpenAI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. GLM 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. GPT-5.2 is a capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecGLM 5.1GPT-5.2
ProviderZ.ai (China) OpenAI (US)
ReleasedApril 7, 2026 December 11, 2025
Context window200K (~300 pages) 400K (~600 pages)
Price (in/out)$1.4/$4.4 per 1M tokens $1.75/$14 per 1M tokens
Open weight?Yes — self-hostable No — API only
Modalitiestext, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Long-horizon autonomous agentic engineering (up to 8-hour runs)

GLM 5.1

A core design strength of GLM 5.1.

State-of-the-art open-weight coding (topped SWE-Bench Pro at launch)

GLM 5.1

A core design strength of GLM 5.1.

Sustained tool use across thousands of calls

GLM 5.1

A core design strength of GLM 5.1.

Strong all-round reasoning

GPT-5.2

A core design strength of GPT-5.2.

Reliable structured output

GPT-5.2

A core design strength of GPT-5.2.

Broad ecosystem and tooling

GPT-5.2

A core design strength of GPT-5.2.

Lowest cost at scale

GLM 5.1

At $1.4/$4.4 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

GPT-5.2

Its 400K window is about 2× larger, fitting roughly 600 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

GLM 5.1

At $1.4/$4.4 per 1M tokens it undercuts GPT-5.2, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

GPT-5.2

Larger 400K window fits more in one prompt.

A team with data-privacy or self-hosting needs

GLM 5.1

Open weights let you run it on your own hardware; GPT-5.2 is API-only.

Anyone whose priority is long-horizon autonomous agentic engineering (up to 8-hour runs)

GLM 5.1

It is specifically built for that.

Anyone whose priority is strong all-round reasoning

GPT-5.2

That is its strongest area.

An enterprise with regional data-residency rules

GPT-5.2 or GLM 5.1

Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

GLM 5.1: where it fits

An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.

Its trade-offs are real: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. At $1.4 in / $4.4 out per million tokens, it sits in the mid price band.

GPT-5.2: where it fits

A capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. Released December 11, 2025 by OpenAI, it is built for strong all-round reasoning, reliable structured output, broad ecosystem and tooling, and professional workflows.

Its trade-offs: superseded by GPT-5.5, and smaller context than flagships. At $1.75 in / $14 out per million tokens, it sits in the mid price band.

The bottom line for this matchup

The defining split here is open vs. closed. GLM 5.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.2 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.

Want both GLM 5.1 and GPT-5.2 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.

See pricing

Frequently asked questions

Is GLM 5.1 or GPT-5.2 better for coding?

Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs) while GPT-5.2 leans toward strong all-round reasoning, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GLM 5.1 or GPT-5.2?

GLM 5.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.2 is API-metered at $1.75/$14 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.

Which has the bigger context window?

GPT-5.2 — 400K vs 200K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both GLM 5.1 and GPT-5.2 together?

Yes — a multi-model platform like LumiChats gives you GLM 5.1, GPT-5.2 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.

Which is newer, GLM 5.1 or GPT-5.2?

GLM 5.1 — released April 7, 2026, about 4 months after GPT-5.2.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.