Gemini 4 Carbon vs Kimi K2.7 Code
Google · US | Moonshot 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 Kimi K2.7 Code for long-horizon agentic software engineering or token-efficient reasoning (~30% fewer than k2.6). Choose Kimi K2.7 Code if you need self-hosting or data privacy; Gemini 4 Carbon if you want a managed API.
Gemini 4 Carbon (Google, US) and Kimi K2.7 Code (Moonshot 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. Kimi K2.7 Code is moonshot AI's open-weight 1T-parameter MoE model (32B active) tuned for long-horizon agentic coding, always reasoning yet ~30% more token-efficient than K2.6. 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: Kimi K2.7 Code is about 2.1× cheaper on input ($0.95/$4 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 3.8× more — 1M tokens (~1,500 pages) vs 256K (~393 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 5 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 | Kimi K2.7 Code |
|---|---|---|
| Provider | Google (US) | Moonshot AI (China) |
| Released | October 28, 2026 | June 12, 2026 |
| Context window | 1M tokens (~1,500 pages) | 256K (~393 pages) |
| Price (in/out) | $2/$10 per 1M tokens | $0.95/$4 per 1M tokens |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, image, audio, video, code | text, image, video, code |
| SWE-Bench Verified | Not published | Not published |
| 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
Kimi K2.7 Code is comparatively weak here — only self-reported benchmarks; no SWE-Bench Verified
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.
Long-horizon agentic software engineering
Kimi K2.7 Code
Moonshot AI's open-weight 1T-parameter MoE model (32B active) tuned for long-horizon agentic coding, always reasoning yet ~30% more token-efficient than K2.6 — and it runs cheaper at $0.95/$4 per 1M tokens.
Token-efficient reasoning (~30% fewer than K2.6)
Kimi K2.7 Code
Moonshot AI's open-weight 1T-parameter MoE model (32B active) tuned for long-horizon agentic coding, always reasoning yet ~30% more token-efficient than K2.6 — and its weights are open while Gemini 4 Carbon is API-only.
Open-weight 1T MoE, self-hostable
Kimi K2.7 Code
Open weights make this possible at all — Gemini 4 Carbon is API-only, so it cannot leave the vendor's servers.
Lowest cost at scale
Kimi K2.7 Code
At $0.95/$4 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 3.8× larger than Kimi K2.7 Code's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Kimi K2.7 Code
At $0.95/$4 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
→ Kimi K2.7 Code
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 long-horizon agentic software engineering
→ Kimi K2.7 Code
That is its strongest area.
An enterprise with regional data-residency rules
→ Gemini 4 Carbon or Kimi K2.7 Code
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.
Kimi K2.7 Code: where it fits
Moonshot AI's open-weight 1T-parameter MoE model (32B active) tuned for long-horizon agentic coding, always reasoning yet ~30% more token-efficient than K2.6. Released June 12, 2026 by Moonshot AI, it is built for long-horizon agentic software engineering, token-efficient reasoning (~30% fewer than K2.6), open-weight 1T MoE, self-hostable, and multi-turn tool use with preserved reasoning.
Its trade-offs: only self-reported benchmarks; no SWE-Bench Verified, and thinking mode and sampling params can't be disabled. At $0.95 in / $4 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. Kimi K2.7 Code 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 Kimi K2.7 Code 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 Kimi K2.7 Code 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 4 Carbon leans toward ranked first on the artificial analysis intelligence index v5.0 with 59 at launch (artificial analysis now shows 60) while Kimi K2.7 Code leans toward long-horizon agentic software engineering, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 4 Carbon or Kimi K2.7 Code?
Kimi K2.7 Code 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 256K, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemini 4 Carbon and Kimi K2.7 Code together?
Yes — a multi-model platform like LumiChats gives you Gemini 4 Carbon, Kimi K2.7 Code 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 Kimi K2.7 Code?
Gemini 4 Carbon — released October 28, 2026, about 5 months after Kimi K2.7 Code.
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.