Gemma 4 vs GLM 5.2

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

Quick verdict

Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. Pick GLM 5.2 for long-horizon agentic coding or project-level software engineering. On a tight budget at scale, Gemma 4 is the value pick.

Gemma 4 (Google, US) and GLM 5.2 (Z.ai, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. GLM 5.2 is an open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. 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

SpecGemma 4GLM 5.2
ProviderGoogle (US) Z.ai (China)
ReleasedApril 2, 2026 June 16, 2026
Context window256K (~384 pages) 1M (~1,500 pages)
Price (in/out)Open weight (self-host / free) $1.4/$4.4 per 1M tokens
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, image, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Self-hosted, data-private deployment

Gemma 4

Gemma 4 lists self-hosted, data-private deployment among its strengths; GLM 5.2 does not.

Running locally or on edge devices

Gemma 4

Gemma 4 lists running locally or on edge devices among its strengths; GLM 5.2 does not.

Fine-tuning on your own data

Gemma 4

Gemma 4 lists fine-tuning on your own data among its strengths; GLM 5.2 does not.

Long-horizon agentic coding

GLM 5.2

Its 1M window holds about 3.9× more than Gemma 4's 256K 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

Gemma 4 is comparatively weak here — trails frontier closed models on the hardest tasks

Lowest cost at scale

Gemma 4

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 3.9× larger than Gemma 4's 256K, fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Gemma 4

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 self-hosted, data-private deployment

→ Gemma 4

It is specifically built for that.

Anyone whose priority is long-horizon agentic coding

→ GLM 5.2

That is its strongest area.

An enterprise with regional data-residency rules

→ Gemma 4 or GLM 5.2

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

Gemma 4: where it fits

Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Released April 2, 2026 by Google, it is built for self-hosted, data-private deployment, running locally or on edge devices, fine-tuning on your own data, and multimodal tasks over a 256K context.

Its trade-offs are real: trails frontier closed models on the hardest tasks, and needs your own hardware to run. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

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: 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.

The bottom line for this matchup

This is less "which is smarter" and more "which ecosystem fits." Gemma 4 (US) and GLM 5.2 (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Gemma 4 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 Gemma 4 and GLM 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 Gemma 4 or GLM 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, Gemma 4 leans toward self-hosted, data-private deployment while GLM 5.2 leans toward long-horizon agentic coding, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Gemma 4 or GLM 5.2?

Gemma 4 is cheaper — Open weight (self-host / free) vs $1.4/$4.4 per 1M tokens.

Which has the bigger context window?

GLM 5.2 — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Gemma 4 and GLM 5.2 together?

Yes — a multi-model platform like LumiChats gives you Gemma 4, GLM 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, Gemma 4 or GLM 5.2?

GLM 5.2 — released June 16, 2026, about 3 months after Gemma 4.

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.