Gemini 4 Carbon vs GLM 4.7
Google · US | Z.ai · China · Updated June 2026
Quick verdict
Pick Gemini 4 Carbon for ranked first on the artificial analysis intelligence index v5.0 with 59 at launch (artificial analysis now shows 60) or google-reported 88.2% on sec-bench pro and 54.8% on exploitgym for vulnerability discovery and exploit validation. 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 4 Carbon if you want a managed API.
Gemini 4 Carbon (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 4 Carbon is google's October 28, 2026 limited release for cyber defenders - top of the Artificial Analysis index at launch, priced at $2/$10 introductory, with no public API date yet. 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: GLM 4.7 is about 3.3× cheaper on input ($0.6/$2.2 per 1M tokens vs $2/$10 per 1M tokens) — meaningful once you are processing millions of tokens a month.
- ▸Context window: Gemini 4 Carbon holds 4.9× more — 1M tokens (~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: Gemini 4 Carbon is the newer model by about 10 months (released October 28, 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 4 Carbon | GLM 4.7 |
|---|---|---|
| Provider | Google (US) | Z.ai (China) |
| Released | October 28, 2026 | December 22, 2025 |
| Context window | 1M tokens (~1,500 pages) | 200K (~304 pages) |
| Price (in/out) | $2/$10 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
Ranked first on the Artificial Analysis Intelligence Index v5.0 with 59 at launch (Artificial Analysis now shows 60)
Gemini 4 Carbon
Google's October 28, 2026 limited release for cyber defenders - top of the Artificial Analysis index at launch, priced at $2/$10 introductory, with no public API date yet — and it carries the larger 1M tokens context.
Google-reported 88.2% on SEC-bench Pro and 54.8% on ExploitGym for vulnerability discovery and exploit validation
Gemini 4 Carbon
GLM 4.7 is comparatively weak here — its Verified lead narrows sharply on harder evaluations like SWE-Bench Pro
Google-reported 71.0% on CWE-bench for patching
Gemini 4 Carbon
Google's October 28, 2026 limited release for cyber defenders - top of the Artificial Analysis index at launch, priced at $2/$10 introductory, with no public API date yet — and it is the newer of the two.
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 4 Carbon 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
At $0.6/$2.2 per 1M tokens it undercuts Gemini 4 Carbon ($2/$10 per 1M tokens), and that gap compounds at volume.
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 runs cheaper at $0.6/$2.2 per 1M tokens.
Lowest cost at scale
GLM 4.7
At $0.6/$2.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Gemini 4 Carbon
Its 1M tokens 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
→ GLM 4.7
At $0.6/$2.2 per 1M tokens it undercuts Gemini 4 Carbon, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 4 Carbon
Larger 1M tokens 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 4 Carbon is API-only.
Anyone whose priority is ranked first on the artificial analysis intelligence index v5.0 with 59 at launch (artificial analysis now shows 60)
→ Gemini 4 Carbon
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 4 Carbon 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 4 Carbon: where it fits
Google's October 28, 2026 limited release for cyber defenders - top of the Artificial Analysis index at launch, priced at $2/$10 introductory, with no public API date yet. Released October 28, 2026 by Google, it is built for ranked first on the Artificial Analysis Intelligence Index v5.0 with 59 at launch (Artificial Analysis now shows 60), google-reported 88.2% on SEC-bench Pro and 54.8% on ExploitGym for vulnerability discovery and exploit validation, google-reported 71.0% on CWE-bench for patching, and introductory $2/$10 per million tokens, matching Gemini 4 Argon, with cached input 95% off.
Its trade-offs are real: limited release: rolling out to a subset of cyber defenders, then trusted partners via the Fairwind Program, with no date for developers or consumers, no public API model listing yet, so most users cannot call it today, introductory pricing rises to $4/$20 afterward, and Google has not said when that happens, and google has not published context or modality specs - the 1M window and modalities shown come from Artificial Analysis and Vals. At $2 in / $10 out per million tokens, it sits in the mid 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 4 Carbon 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 4 Carbon 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.
See pricingFrequently asked questions
Is Gemini 4 Carbon or GLM 4.7 better for coding?
Public SWE-Bench figures are not available for Gemini 4 Carbon, so the honest test is your own repository — run an identical real bug through both. By design, Gemini 4 Carbon leans toward ranked first on the artificial analysis intelligence index v5.0 with 59 at launch (artificial analysis now shows 60) 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 4 Carbon 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 4 Carbon is API-metered at $2/$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 4 Carbon — 1M tokens 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 4 Carbon and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you Gemini 4 Carbon, 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 4 Carbon or GLM 4.7?
Gemini 4 Carbon — released October 28, 2026, about 10 months after GLM 4.7.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.