Both are Z.ai models. GLM 5.1 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 5.1 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 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. 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: both advertise 200K (~300 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: GLM 5.1 is the newer model by about 55 days (released April 7, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GLM 5
GLM 5.1
Provider
Z.ai (China)
Z.ai (China)
Released
February 11, 2026
April 7, 2026
Context window
200K (~300 pages)
200K (~300 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 autonomous agentic engineering (up to 8-hour runs): GLM 5.1 — A core design strength of GLM 5.1.
State-of-the-art open-weight coding (topped SWE-Bench Pro at launch): GLM 5.1 — A core design strength of GLM 5.1.
Sustained tool use across thousands of calls: GLM 5.1 — A core design strength of GLM 5.1.
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.
Which should you pick?
A cost-sensitive startup shipping high volume: GLM 5 — At $1/$3.2 per 1M tokens it undercuts GLM 5.1, and on millions of tokens that margin decides the monthly bill.
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 autonomous agentic engineering (up to 8-hour runs): GLM 5.1 — 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 5.1: where it fits
An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.
Its trade-offs: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. 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 5.1 come from the same lab (Z.ai), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GLM 5.1 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 5.1 and drop down only with a concrete reason.
Frequently asked questions
Is GLM 5 or GLM 5.1 better for coding?
Public SWE-Bench figures are not available for GLM 5.1, 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 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or GLM 5.1?
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?
Both advertise 200K (~300 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from GLM 5 to GLM 5.1?
Since both are Z.ai models, the newer one (GLM 5.1) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GLM 5 or GLM 5.1?
GLM 5.1 — released April 7, 2026, about 55 days after GLM 5.
GLM 5 vs GLM 5.1
Z.ai · China | Z.ai · China · Updated June 2026
Quick verdict
Both are Z.ai models. GLM 5.1 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 5.1 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 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. 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: both advertise 200K (~300 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: GLM 5.1 is the newer model by about 55 days (released April 7, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GLM 5
GLM 5.1
Provider
Z.ai (China)
Z.ai (China)
Released
February 11, 2026
April 7, 2026
Context window
200K (~300 pages)
200K (~300 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 autonomous agentic engineering (up to 8-hour runs)
GLM 5.1
A core design strength of GLM 5.1.
State-of-the-art open-weight coding (topped SWE-Bench Pro at launch)
GLM 5.1
A core design strength of GLM 5.1.
Sustained tool use across thousands of calls
GLM 5.1
A core design strength of GLM 5.1.
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.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GLM 5
At $1/$3.2 per 1M tokens it undercuts GLM 5.1, and on millions of tokens that margin decides the monthly bill.
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 autonomous agentic engineering (up to 8-hour runs)
→ GLM 5.1
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 5.1: where it fits
An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.
Its trade-offs: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. 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 5.1 come from the same lab (Z.ai), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GLM 5.1 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 5.1 and drop down only with a concrete reason.
Want both GLM 5 and GLM 5.1 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 5.1, 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 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or GLM 5.1?
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?
Both advertise 200K (~300 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from GLM 5 to GLM 5.1?
Since both are Z.ai models, the newer one (GLM 5.1) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GLM 5 or GLM 5.1?
GLM 5.1 — released April 7, 2026, about 55 days 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.