GLM 5.2 vs Llama 4 Maverick
Z.ai · China | Meta · US · Updated June 2026
Quick verdict
Pick GLM 5.2 for long-horizon agentic coding or project-level software engineering. Pick Llama 4 Maverick for open weights, 1m context or strong image + text understanding. On a tight budget at scale, Llama 4 Maverick is the value pick.
GLM 5.2 (Z.ai, China) and Llama 4 Maverick (Meta, 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. Llama 4 Maverick is meta's open-weight 1M-context multimodal model for self-hosted deployments. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: GLM 5.2 is the newer model by about 15 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 | Llama 4 Maverick |
|---|---|---|
| Provider | Z.ai (China) | Meta (US) |
| Released | June 16, 2026 | April 2025 |
| Context window | 1M (~1,500 pages) | 1M (~1,500 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, image, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Long-horizon agentic coding
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.
Project-level software engineering
GLM 5.2
GLM 5.2 lists project-level software engineering among its strengths; Llama 4 Maverick does not.
Tool use across long-running tasks
GLM 5.2
GLM 5.2 lists tool use across long-running tasks among its strengths; Llama 4 Maverick does not.
Open weights, 1M context
Llama 4 Maverick
Llama 4 Maverick lists open weights, 1M context among its strengths; GLM 5.2 does not.
Strong image + text understanding
Llama 4 Maverick
Llama 4 Maverick lists strong image + text understanding among its strengths; GLM 5.2 does not.
Self-hostable
Llama 4 Maverick
Llama 4 Maverick lists self-hostable among its strengths; GLM 5.2 does not.
Lowest cost at scale
Llama 4 Maverick
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.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Llama 4 Maverick
At Open weight (self-host / free) it undercuts GLM 5.2, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is long-horizon agentic coding
→ GLM 5.2
It is specifically built for that.
Anyone whose priority is open weights, 1m context
→ Llama 4 Maverick
That is its strongest area.
An enterprise with regional data-residency rules
→ Llama 4 Maverick 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.
Llama 4 Maverick: where it fits
Meta's open-weight 1M-context multimodal model for self-hosted deployments. Released April 2025 by Meta, it is built for open weights, 1M context, strong image + text understanding, self-hostable, and 400B MoE, 17B active.
Its trade-offs: needs serious hardware to self-host, and trails closed frontier on reasoning. 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 Llama 4 Maverick (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Llama 4 Maverick 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 Llama 4 Maverick 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 Llama 4 Maverick 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 5.2 leans toward long-horizon agentic coding while Llama 4 Maverick leans toward open weights, 1m context, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5.2 or Llama 4 Maverick?
Llama 4 Maverick is cheaper — $1.4/$4.4 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GLM 5.2 and Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you GLM 5.2, Llama 4 Maverick 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 Llama 4 Maverick?
GLM 5.2 — released June 16, 2026, about 15 months after Llama 4 Maverick.
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.