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
- ▸Context window: GLM 5.2 holds 7.6× more — 1M (~1,500 pages) vs 131K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: GLM 5.2 is the newer model by about 11 months (released June 16, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | GLM 5.2 | gpt-oss-120b |
|---|---|---|
| Provider | Z.ai (China) | OpenAI (US) |
| Released | June 16, 2026 | August 5, 2025 |
| Context window | 1M (~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 |
| Modalities | text, code | text, code |
| SWE-Bench Verified | Not published | 62.4% |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Long-horizon agentic coding
GLM 5.2
Its 1M window holds about 7.6× more than gpt-oss-120b's 131K in a single prompt.
Project-level software engineering
GLM 5.2
An open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap — and it carries the larger 1M context.
Tool use across long-running tasks
GLM 5.2
An open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap — and it is the newer of the two.
Self-hostable on a single 80GB H100 GPU via MXFP4
gpt-oss-120b
gpt-oss-120b lists self-hostable on a single 80GB H100 GPU via MXFP4 among its strengths; GLM 5.2 does not.
Configurable reasoning depth (low/medium/high)
gpt-oss-120b
gpt-oss-120b lists configurable reasoning depth (low/medium/high) among its strengths; GLM 5.2 does not.
Agentic tool use, function calling, and code execution
gpt-oss-120b
gpt-oss-120b lists agentic tool use, function calling, and code execution among its strengths; GLM 5.2 does not.
Lowest cost at scale
gpt-oss-120b
Its weights are open, so at volume you pay for your own hardware instead of GLM 5.2's $1.4/$4.4 per 1M tokens.
Largest single-prompt input
GLM 5.2
Its 1M window is about 7.6× larger than gpt-oss-120b's 131K, 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 16, 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 pricingFrequently 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 16, 2026, about 11 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.