Pick Gemini 2.5 Flash for cheapest 1m-context option or very fast. Pick GLM 4.7 for genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions or strong agentic coding for the price — 73.8% on swe-bench verified undercut most closed frontier models at launch. Choose GLM 4.7 if you need self-hosting or data privacy; Gemini 2.5 Flash if you want a managed API.
Gemini 2.5 Flash (Google, US) and GLM 4.7 (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 Flash is google's ultra-cheap, fast 1M-context model for high-volume multimodal work. GLM 4.7 is an MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: Gemini 2.5 Flash is about 2× cheaper on input ($0.3/$2.5 per 1M tokens vs $0.6/$2.2 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: Gemini 2.5 Flash holds 4.9× more — 1M (~1,500 pages) vs 200K (~304 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 4.7 is the newer model by about 7 months (released December 22, 2025), 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 Flash
GLM 4.7
Provider
Google (US)
Z.ai (China)
Released
June 2025
December 22, 2025
Context window
1M (~1,500 pages)
200K (~304 pages)
Price (in/out)
$0.3/$2.5 per 1M tokens
$0.6/$2.2 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, audio, video, code
text, code
SWE-Bench Verified
Not published
73.8%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheapest 1M-context option: Gemini 2.5 Flash — At $0.3/$2.5 per 1M tokens it undercuts GLM 4.7 ($0.6/$2.2 per 1M tokens), and that gap compounds at volume.
Very fast: Gemini 2.5 Flash — Google's ultra-cheap, fast 1M-context model for high-volume multimodal work — and it runs cheaper at $0.3/$2.5 per 1M tokens.
High-volume multimodal: Gemini 2.5 Flash — Google's ultra-cheap, fast 1M-context model for high-volume multimodal work — and it carries the larger 1M context.
Genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions: GLM 4.7 — Open weights make this possible at all — Gemini 2.5 Flash is API-only, so it cannot leave the vendor's servers.
Strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch: GLM 4.7 — An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2 — and its weights are open while Gemini 2.5 Flash is API-only.
An unusually generous 128K maximum output, which suits bulk refactors and long generation: GLM 4.7 — An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2 — and it is the newer of the two.
Lowest cost at scale: Gemini 2.5 Flash — At $0.3/$2.5 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 Flash — Its 1M window is about 4.9× larger than GLM 4.7's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Gemini 2.5 Flash — At $0.3/$2.5 per 1M tokens it undercuts GLM 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemini 2.5 Flash — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: GLM 4.7 — Open weights let you run it on your own hardware; Gemini 2.5 Flash is API-only.
Anyone whose priority is cheapest 1m-context option: Gemini 2.5 Flash — It is specifically built for that.
Anyone whose priority is genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions: GLM 4.7 — That is its strongest area.
An enterprise with regional data-residency rules: Gemini 2.5 Flash or GLM 4.7 — 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 Flash: where it fits
Google's ultra-cheap, fast 1M-context model for high-volume multimodal work. Released June 2025 by Google, it is built for cheapest 1M-context option, very fast, high-volume multimodal, and workspace integration.
Its trade-offs are real: lighter reasoning than Pro tiers, and superseded by 3.5 Flash. At $0.3 in / $2.5 out per million tokens, it sits in the budget price band.
GLM 4.7: where it fits
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. Released December 22, 2025 by Z.ai, it is built for genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions, strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch, an unusually generous 128K maximum output, which suits bulk refactors and long generation, and cheap long-running agent loops thanks to aggressive prompt caching.
Its trade-offs: two generations behind — GLM 5, 5.1 and 5.2 have all shipped since, and new builds should default to those, its Verified lead narrows sharply on harder evaluations like SWE-Bench Pro, and text-only with no vision, and self-hosting a 358B model is a serious hardware commitment. At $0.6 in / $2.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 4.7 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Gemini 2.5 Flash 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 Flash or GLM 4.7 better for coding?
Public SWE-Bench figures are not available for Gemini 2.5 Flash, so the honest test is your own repository — run an identical real bug through both. By design, Gemini 2.5 Flash leans toward cheapest 1m-context option while GLM 4.7 leans toward genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 2.5 Flash or GLM 4.7?
GLM 4.7 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 2.5 Flash is API-metered at $0.3/$2.5 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 Flash — 1M vs 200K, about 4.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemini 2.5 Flash and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you Gemini 2.5 Flash, GLM 4.7 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 Flash or GLM 4.7?
GLM 4.7 — released December 22, 2025, about 7 months after Gemini 2.5 Flash.
Gemini 2.5 Flash vs GLM 4.7
Google · US | Z.ai · China · Updated June 2026
Quick verdict
Pick Gemini 2.5 Flash for cheapest 1m-context option or very fast. Pick GLM 4.7 for genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions or strong agentic coding for the price — 73.8% on swe-bench verified undercut most closed frontier models at launch. Choose GLM 4.7 if you need self-hosting or data privacy; Gemini 2.5 Flash if you want a managed API.
Gemini 2.5 Flash (Google, US) and GLM 4.7 (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 Flash is google's ultra-cheap, fast 1M-context model for high-volume multimodal work. GLM 4.7 is an MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. 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: Gemini 2.5 Flash is about 2× cheaper on input ($0.3/$2.5 per 1M tokens vs $0.6/$2.2 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Gemini 2.5 Flash holds 4.9× more — 1M (~1,500 pages) vs 200K (~304 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 4.7 is the newer model by about 7 months (released December 22, 2025), 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 Flash
GLM 4.7
Provider
Google (US)
Z.ai (China)
Released
June 2025
December 22, 2025
Context window
1M (~1,500 pages)
200K (~304 pages)
Price (in/out)
$0.3/$2.5 per 1M tokens
$0.6/$2.2 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, audio, video, code
text, code
SWE-Bench Verified
Not published
73.8%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheapest 1M-context option
Gemini 2.5 Flash
At $0.3/$2.5 per 1M tokens it undercuts GLM 4.7 ($0.6/$2.2 per 1M tokens), and that gap compounds at volume.
Very fast
Gemini 2.5 Flash
Google's ultra-cheap, fast 1M-context model for high-volume multimodal work — and it runs cheaper at $0.3/$2.5 per 1M tokens.
High-volume multimodal
Gemini 2.5 Flash
Google's ultra-cheap, fast 1M-context model for high-volume multimodal work — and it carries the larger 1M context.
Genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions
GLM 4.7
Open weights make this possible at all — Gemini 2.5 Flash is API-only, so it cannot leave the vendor's servers.
Strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch
GLM 4.7
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2 — and its weights are open while Gemini 2.5 Flash is API-only.
An unusually generous 128K maximum output, which suits bulk refactors and long generation
GLM 4.7
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2 — and it is the newer of the two.
Lowest cost at scale
Gemini 2.5 Flash
At $0.3/$2.5 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 Flash
Its 1M window is about 4.9× larger than GLM 4.7's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemini 2.5 Flash
At $0.3/$2.5 per 1M tokens it undercuts GLM 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 2.5 Flash
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 4.7
Open weights let you run it on your own hardware; Gemini 2.5 Flash is API-only.
Anyone whose priority is cheapest 1m-context option
→ Gemini 2.5 Flash
It is specifically built for that.
Anyone whose priority is genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions
→ GLM 4.7
That is its strongest area.
An enterprise with regional data-residency rules
→ Gemini 2.5 Flash or GLM 4.7
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 Flash: where it fits
Google's ultra-cheap, fast 1M-context model for high-volume multimodal work. Released June 2025 by Google, it is built for cheapest 1M-context option, very fast, high-volume multimodal, and workspace integration.
Its trade-offs are real: lighter reasoning than Pro tiers, and superseded by 3.5 Flash. At $0.3 in / $2.5 out per million tokens, it sits in the budget price band.
GLM 4.7: where it fits
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. Released December 22, 2025 by Z.ai, it is built for genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions, strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch, an unusually generous 128K maximum output, which suits bulk refactors and long generation, and cheap long-running agent loops thanks to aggressive prompt caching.
Its trade-offs: two generations behind — GLM 5, 5.1 and 5.2 have all shipped since, and new builds should default to those, its Verified lead narrows sharply on harder evaluations like SWE-Bench Pro, and text-only with no vision, and self-hosting a 358B model is a serious hardware commitment. At $0.6 in / $2.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 4.7 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Gemini 2.5 Flash 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 Flash and GLM 4.7 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 Gemini 2.5 Flash, so the honest test is your own repository — run an identical real bug through both. By design, Gemini 2.5 Flash leans toward cheapest 1m-context option while GLM 4.7 leans toward genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 2.5 Flash or GLM 4.7?
GLM 4.7 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 2.5 Flash is API-metered at $0.3/$2.5 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 Flash — 1M vs 200K, about 4.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemini 2.5 Flash and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you Gemini 2.5 Flash, GLM 4.7 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 Flash or GLM 4.7?
GLM 4.7 — released December 22, 2025, about 7 months after Gemini 2.5 Flash.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.