GLM 5.2 vs gpt-oss-120b

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

Quick verdict

Pick GLM 5.2 for long-horizon agentic coding or project-level software engineering. Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high). On a tight budget at scale, gpt-oss-120b is the value pick.

GLM 5.2 (Z.ai, China) and gpt-oss-120b (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 5.2 is an open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. gpt-oss-120b is openAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. They diverge most on price and context window — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecGLM 5.2gpt-oss-120b
ProviderZ.ai (China) OpenAI (US)
ReleasedJune 13, 2026 August 5, 2025
Context window1M (~1,500 pages) 131K (~197 pages)
Price (in/out)$1.4/$4.4 per 1M tokens Open weight (self-host / free)
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, code text, code
SWE-Bench VerifiedNot published 62.4%
MRCR v2 @ 1MNot published Not published

Who wins what

Long-horizon agentic coding

GLM 5.2

A core design strength of GLM 5.2.

Project-level software engineering

GLM 5.2

A core design strength of GLM 5.2.

Tool use across long-running tasks

GLM 5.2

A core design strength of GLM 5.2.

Self-hostable on a single 80GB H100 GPU via MXFP4

gpt-oss-120b

A core design strength of gpt-oss-120b.

Configurable reasoning depth (low/medium/high)

gpt-oss-120b

A core design strength of gpt-oss-120b.

Agentic tool use, function calling, and code execution

gpt-oss-120b

A core design strength of gpt-oss-120b.

Lowest cost at scale

gpt-oss-120b

At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

GLM 5.2

Its 1M window is about 7.6× larger, fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

gpt-oss-120b

At Open weight (self-host / free) it undercuts GLM 5.2, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

GLM 5.2

Larger 1M window fits more in one prompt.

Anyone whose priority is long-horizon agentic coding

GLM 5.2

It is specifically built for that.

Anyone whose priority is self-hostable on a single 80gb h100 gpu via mxfp4

gpt-oss-120b

That is its strongest area.

An enterprise with regional data-residency rules

gpt-oss-120b or GLM 5.2

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

GLM 5.2: where it fits

An open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. Released June 13, 2026 by Z.ai, it is built for long-horizon agentic coding, project-level software engineering, tool use across long-running tasks, and tops the open-weight intelligence index (SWE-bench Pro 62.1).

Its trade-offs are real: text-only — no native multimodal input, and new release with a limited third-party track record. At $1.4 in / $4.4 out per million tokens, it sits in the mid price band.

gpt-oss-120b: where it fits

OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. Released August 5, 2025 by OpenAI, it is built for self-hostable on a single 80GB H100 GPU via MXFP4, configurable reasoning depth (low/medium/high), agentic tool use, function calling, and code execution, and full chain-of-thought visibility for debugging.

Its trade-offs: text-only, no image, audio, or video input, and 131K context and 5.1B active params trail the largest frontier closed models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

The bottom line for this matchup

This is less "which is smarter" and more "which ecosystem fits." GLM 5.2 (China) and gpt-oss-120b (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. gpt-oss-120b is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.

Want both GLM 5.2 and gpt-oss-120b 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 5.2 or gpt-oss-120b better for coding?

Public SWE-Bench figures are not available for GLM 5.2, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5.2 leans toward long-horizon agentic coding while gpt-oss-120b leans toward self-hostable on a single 80gb h100 gpu via mxfp4, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GLM 5.2 or gpt-oss-120b?

gpt-oss-120b is cheaper — $1.4/$4.4 per 1M tokens vs Open weight (self-host / free).

Which has the bigger context window?

GLM 5.2 — 1M vs 131K, about 7.6× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both GLM 5.2 and gpt-oss-120b together?

Yes — a multi-model platform like LumiChats gives you GLM 5.2, gpt-oss-120b 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 5.2 or gpt-oss-120b?

GLM 5.2 — released June 13, 2026, about 10 months after gpt-oss-120b.

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.