Both are Z.ai models. GLM 5.2 is the newer, generally stronger default; reach for GLM 5 when its lower price or a specific cost or latency profile matters more than the latest capabilities.
GLM 5 and GLM 5.2 are both Z.ai models, so the real question is not which lab to trust but which tier fits your workload and budget. GLM 5 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. GLM 5.2 is an open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences
Price: GLM 5 is about 1.4× cheaper on input ($1/$3.2 per 1M tokens vs $1.4/$4.4 per 1M tokens) — modest, but it adds up at steady volume.
Context window: GLM 5.2 holds 5× more — 1M (~1,500 pages) vs 200K (~300 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 4 months (released June 13, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GLM 5
GLM 5.2
Provider
Z.ai (China)
Z.ai (China)
Released
February 11, 2026
June 13, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1/$3.2 per 1M tokens
$1.4/$4.4 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
77.8%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Agentic planning and long-horizon coding workflows: GLM 5 — A core design strength of GLM 5.
Complex systems design and backend reasoning: GLM 5 — A core design strength of GLM 5.
Iterative self-correction on autonomous tasks: GLM 5 — A core design strength of GLM 5.
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.
Lowest cost at scale: GLM 5 — At $1/$3.2 per 1M tokens, 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 5× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GLM 5 — At $1/$3.2 per 1M tokens 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 agentic planning and long-horizon coding workflows: GLM 5 — It is specifically built for that.
Anyone whose priority is long-horizon agentic coding: GLM 5.2 — That is its strongest area.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 11, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs are real: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 out per million tokens, it sits in the budget price band.
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: 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
Because GLM 5 and GLM 5.2 come from the same lab (Z.ai), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GLM 5.2 is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to GLM 5.2 and drop down only with a concrete reason.
Frequently asked questions
Is GLM 5 or GLM 5.2 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 leans toward agentic planning and long-horizon coding workflows while GLM 5.2 leans toward long-horizon agentic coding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or GLM 5.2?
GLM 5 is cheaper — $1/$3.2 per 1M tokens vs $1.4/$4.4 per 1M tokens, roughly 1.4× apart on input.
Which has the bigger context window?
GLM 5.2 — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from GLM 5 to GLM 5.2?
Since both are Z.ai models, the newer one (GLM 5.2) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GLM 5 or GLM 5.2?
GLM 5.2 — released June 13, 2026, about 4 months after GLM 5.
GLM 5 vs GLM 5.2
Z.ai · China | Z.ai · China · Updated June 2026
Quick verdict
Both are Z.ai models. GLM 5.2 is the newer, generally stronger default; reach for GLM 5 when its lower price or a specific cost or latency profile matters more than the latest capabilities.
GLM 5 and GLM 5.2 are both Z.ai models, so the real question is not which lab to trust but which tier fits your workload and budget. GLM 5 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. GLM 5.2 is an open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences at a glance
▸Price: GLM 5 is about 1.4× cheaper on input ($1/$3.2 per 1M tokens vs $1.4/$4.4 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: GLM 5.2 holds 5× more — 1M (~1,500 pages) vs 200K (~300 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 4 months (released June 13, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GLM 5
GLM 5.2
Provider
Z.ai (China)
Z.ai (China)
Released
February 11, 2026
June 13, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1/$3.2 per 1M tokens
$1.4/$4.4 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
77.8%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Agentic planning and long-horizon coding workflows
GLM 5
A core design strength of GLM 5.
Complex systems design and backend reasoning
GLM 5
A core design strength of GLM 5.
Iterative self-correction on autonomous tasks
GLM 5
A core design strength of GLM 5.
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.
Lowest cost at scale
GLM 5
At $1/$3.2 per 1M tokens, 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 5× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GLM 5
At $1/$3.2 per 1M tokens 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 agentic planning and long-horizon coding workflows
→ GLM 5
It is specifically built for that.
Anyone whose priority is long-horizon agentic coding
→ GLM 5.2
That is its strongest area.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 11, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs are real: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 out per million tokens, it sits in the budget price band.
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: 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
Because GLM 5 and GLM 5.2 come from the same lab (Z.ai), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GLM 5.2 is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to GLM 5.2 and drop down only with a concrete reason.
Want both GLM 5 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.
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 leans toward agentic planning and long-horizon coding workflows while GLM 5.2 leans toward long-horizon agentic coding, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or GLM 5.2?
GLM 5 is cheaper — $1/$3.2 per 1M tokens vs $1.4/$4.4 per 1M tokens, roughly 1.4× apart on input.
Which has the bigger context window?
GLM 5.2 — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from GLM 5 to GLM 5.2?
Since both are Z.ai models, the newer one (GLM 5.2) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GLM 5 or GLM 5.2?
GLM 5.2 — released June 13, 2026, about 4 months after GLM 5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.