Pick Gemini 2.5 Pro for 1m context via api or strong multimodal reasoning. Pick GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). Choose GLM 5.1 if you need self-hosting or data privacy; Gemini 2.5 Pro if you want a managed API.
Gemini 2.5 Pro (Google, US) and GLM 5.1 (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. Gemini 2.5 Pro is google's previous-gen 2M flagship — still a strong long-context multimodal option. 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. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: nearly identical — $1.25/$10 per 1M tokens vs $1.4/$4.4 per 1M tokens. Cost will not be the deciding factor here.
Context window: Gemini 2.5 Pro 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 5.1 is the newer model by about 10 months (released April 7, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Gemini 2.5 Pro
GLM 5.1
Provider
Google (US)
Z.ai (China)
Released
June 2025
April 7, 2026
Context window
1M (~1,500 pages)
200K (~300 pages)
Price (in/out)
$1.25/$10 per 1M tokens
$1.4/$4.4 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, audio, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
1M context via API: Gemini 2.5 Pro — A core design strength of Gemini 2.5 Pro.
Strong multimodal reasoning: Gemini 2.5 Pro — A core design strength of Gemini 2.5 Pro.
Science and maths benchmarks: Gemini 2.5 Pro — A core design strength of Gemini 2.5 Pro.
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: Gemini 2.5 Pro — At $1.25/$10 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Gemini 2.5 Pro — 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: Gemini 2.5 Pro — At $1.25/$10 per 1M tokens it undercuts GLM 5.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemini 2.5 Pro — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: GLM 5.1 — Open weights let you run it on your own hardware; Gemini 2.5 Pro is API-only.
Anyone whose priority is 1m context via api: Gemini 2.5 Pro — 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.
An enterprise with regional data-residency rules: Gemini 2.5 Pro or GLM 5.1 — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Gemini 2.5 Pro: where it fits
Google's previous-gen 2M flagship — still a strong long-context multimodal option. Released June 2025 by Google, it is built for 1M context via API, strong multimodal reasoning, science and maths benchmarks, and whole-book and video analysis.
Its trade-offs are real: superseded by 3.x for newest features, and recall degrades on very long inputs. At $1.25 in / $10 out per million tokens, it sits in the mid 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
The defining split here is open vs. closed. GLM 5.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Gemini 2.5 Pro 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 Gemini 2.5 Pro or GLM 5.1 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, Gemini 2.5 Pro leans toward 1m context via api 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, Gemini 2.5 Pro or GLM 5.1?
GLM 5.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 2.5 Pro is API-metered at $1.25/$10 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?
Gemini 2.5 Pro — 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 Gemini 2.5 Pro and GLM 5.1 together?
Yes — a multi-model platform like LumiChats gives you Gemini 2.5 Pro, GLM 5.1 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, Gemini 2.5 Pro or GLM 5.1?
GLM 5.1 — released April 7, 2026, about 10 months after Gemini 2.5 Pro.
Gemini 2.5 Pro vs GLM 5.1
Google · US | Z.ai · China · Updated June 2026
Quick verdict
Pick Gemini 2.5 Pro for 1m context via api or strong multimodal reasoning. Pick GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). Choose GLM 5.1 if you need self-hosting or data privacy; Gemini 2.5 Pro if you want a managed API.
Gemini 2.5 Pro (Google, US) and GLM 5.1 (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. Gemini 2.5 Pro is google's previous-gen 2M flagship — still a strong long-context multimodal option. 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. 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: nearly identical — $1.25/$10 per 1M tokens vs $1.4/$4.4 per 1M tokens. Cost will not be the deciding factor here.
▸Context window: Gemini 2.5 Pro 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 5.1 is the newer model by about 10 months (released April 7, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Gemini 2.5 Pro
GLM 5.1
Provider
Google (US)
Z.ai (China)
Released
June 2025
April 7, 2026
Context window
1M (~1,500 pages)
200K (~300 pages)
Price (in/out)
$1.25/$10 per 1M tokens
$1.4/$4.4 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, audio, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
1M context via API
Gemini 2.5 Pro
A core design strength of Gemini 2.5 Pro.
Strong multimodal reasoning
Gemini 2.5 Pro
A core design strength of Gemini 2.5 Pro.
Science and maths benchmarks
Gemini 2.5 Pro
A core design strength of Gemini 2.5 Pro.
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
Gemini 2.5 Pro
At $1.25/$10 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Gemini 2.5 Pro
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
→ Gemini 2.5 Pro
At $1.25/$10 per 1M tokens it undercuts GLM 5.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 2.5 Pro
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 5.1
Open weights let you run it on your own hardware; Gemini 2.5 Pro is API-only.
Anyone whose priority is 1m context via api
→ Gemini 2.5 Pro
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.
An enterprise with regional data-residency rules
→ Gemini 2.5 Pro or GLM 5.1
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Gemini 2.5 Pro: where it fits
Google's previous-gen 2M flagship — still a strong long-context multimodal option. Released June 2025 by Google, it is built for 1M context via API, strong multimodal reasoning, science and maths benchmarks, and whole-book and video analysis.
Its trade-offs are real: superseded by 3.x for newest features, and recall degrades on very long inputs. At $1.25 in / $10 out per million tokens, it sits in the mid 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
The defining split here is open vs. closed. GLM 5.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Gemini 2.5 Pro 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 Gemini 2.5 Pro 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 either model, so the honest test is your own repository — run an identical real bug through both. By design, Gemini 2.5 Pro leans toward 1m context via api 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, Gemini 2.5 Pro or GLM 5.1?
GLM 5.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 2.5 Pro is API-metered at $1.25/$10 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?
Gemini 2.5 Pro — 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 Gemini 2.5 Pro and GLM 5.1 together?
Yes — a multi-model platform like LumiChats gives you Gemini 2.5 Pro, GLM 5.1 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, Gemini 2.5 Pro or GLM 5.1?
GLM 5.1 — released April 7, 2026, about 10 months after Gemini 2.5 Pro.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.