Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. Pick GPT-5.5 for terminal, cli and computer-use automation or long-horizon tool sequencing. Choose GLM 5 if you need self-hosting or data privacy; GPT-5.5 if you want a managed API.
GLM 5 (Z.ai, China) and GPT-5.5 (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 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. GPT-5.5 is openAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: GLM 5 is about 5× cheaper on input ($1/$3.2 per 1M tokens vs $5/$30 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: GPT-5.5 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: GPT-5.5 is the newer model by about 2 months (released April 23, 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.
Specifications
Spec
GLM 5
GPT-5.5
Provider
Z.ai (China)
OpenAI (US)
Released
February 11, 2026
April 23, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1/$3.2 per 1M tokens
$5/$30 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, 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.
Terminal, CLI and computer-use automation: GPT-5.5 — A core design strength of GPT-5.5.
Long-horizon tool sequencing: GPT-5.5 — A core design strength of GPT-5.5.
Strong agentic coding and reasoning: GPT-5.5 — A core design strength of GPT-5.5.
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: GPT-5.5 — 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 GPT-5.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-5.5 — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: GLM 5 — Open weights let you run it on your own hardware; GPT-5.5 is API-only.
Anyone whose priority is agentic planning and long-horizon coding workflows: GLM 5 — It is specifically built for that.
Anyone whose priority is terminal, cli and computer-use automation: GPT-5.5 — That is its strongest area.
An enterprise with regional data-residency rules: GPT-5.5 or GLM 5 — Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
GPT-5.5: where it fits
OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. Released April 23, 2026 by OpenAI, it is built for terminal, CLI and computer-use automation, long-horizon tool sequencing, strong agentic coding and reasoning, and browser-driving agents.
Its trade-offs: trails Opus 4.8 on hardest coding benchmarks, and tiered long-context pricing above 272K tokens. At $5 in / $30 out per million tokens, it sits in the premium price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.5 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is GLM 5 or GPT-5.5 better for coding?
Public SWE-Bench figures are not available for GPT-5.5, 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 GPT-5.5 leans toward terminal, cli and computer-use automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or GPT-5.5?
GLM 5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.5 is API-metered at $5/$30 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
GPT-5.5 — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 5 and GPT-5.5 together?
Yes — a multi-model platform like LumiChats gives you GLM 5, GPT-5.5 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 or GPT-5.5?
GPT-5.5 — released April 23, 2026, about 2 months after GLM 5.
GLM 5 vs GPT-5.5
Z.ai · China | OpenAI · US · Updated June 2026
Quick verdict
Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. Pick GPT-5.5 for terminal, cli and computer-use automation or long-horizon tool sequencing. Choose GLM 5 if you need self-hosting or data privacy; GPT-5.5 if you want a managed API.
GLM 5 (Z.ai, China) and GPT-5.5 (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 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. GPT-5.5 is openAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GLM 5 is about 5× cheaper on input ($1/$3.2 per 1M tokens vs $5/$30 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: GPT-5.5 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: GPT-5.5 is the newer model by about 2 months (released April 23, 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
GPT-5.5
Provider
Z.ai (China)
OpenAI (US)
Released
February 11, 2026
April 23, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1/$3.2 per 1M tokens
$5/$30 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, 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.
Terminal, CLI and computer-use automation
GPT-5.5
A core design strength of GPT-5.5.
Long-horizon tool sequencing
GPT-5.5
A core design strength of GPT-5.5.
Strong agentic coding and reasoning
GPT-5.5
A core design strength of GPT-5.5.
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
GPT-5.5
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 GPT-5.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-5.5
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 5
Open weights let you run it on your own hardware; GPT-5.5 is API-only.
Anyone whose priority is agentic planning and long-horizon coding workflows
→ GLM 5
It is specifically built for that.
Anyone whose priority is terminal, cli and computer-use automation
→ GPT-5.5
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-5.5 or GLM 5
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
GPT-5.5: where it fits
OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. Released April 23, 2026 by OpenAI, it is built for terminal, CLI and computer-use automation, long-horizon tool sequencing, strong agentic coding and reasoning, and browser-driving agents.
Its trade-offs: trails Opus 4.8 on hardest coding benchmarks, and tiered long-context pricing above 272K tokens. At $5 in / $30 out per million tokens, it sits in the premium price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.5 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both GLM 5 and GPT-5.5 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 GPT-5.5, 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 GPT-5.5 leans toward terminal, cli and computer-use automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or GPT-5.5?
GLM 5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.5 is API-metered at $5/$30 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
GPT-5.5 — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 5 and GPT-5.5 together?
Yes — a multi-model platform like LumiChats gives you GLM 5, GPT-5.5 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 or GPT-5.5?
GPT-5.5 — released April 23, 2026, about 2 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.