Gemini 4 Carbon vs Gemma 4 26B A4B
Google · US | Google · US · Updated June 2026
Quick verdict
Both are Google models. Gemini 4 Carbon is the newer, generally stronger default; reach for Gemma 4 26B A4B when its lower price or a specific cost or latency profile matters more than the latest capabilities.
Gemini 4 Carbon and Gemma 4 26B A4B are both Google models, so the real question is not which lab to trust but which tier fits your workload and budget. 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. Gemma 4 26B A4B is an Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences at a glance
- ▸Price: Gemma 4 26B A4B is about 17× cheaper on input ($0.12/$0.37 per 1M tokens vs $2/$10 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸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 7 months (released October 28, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Gemini 4 Carbon | Gemma 4 26B A4B |
|---|---|---|
| Provider | Google (US) | Google (US) |
| Released | October 28, 2026 | April 2, 2026 |
| Context window | 1M tokens (~1,500 pages) | 256K (~393 pages) |
| Price (in/out) | $2/$10 per 1M tokens | $0.12/$0.37 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
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.
Google-reported 71.0% on CWE-bench for patching
Gemini 4 Carbon
Gemini 4 Carbon lists google-reported 71.0% on CWE-bench for patching among its strengths; Gemma 4 26B A4B does not.
Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total)
Gemma 4 26B A4B
At $0.12/$0.37 per 1M tokens it undercuts Gemini 4 Carbon ($2/$10 per 1M tokens), and that gap compounds at volume.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost
Gemma 4 26B A4B
An Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost — and it runs cheaper at $0.12/$0.37 per 1M tokens.
Strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6)
Gemma 4 26B A4B
An Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost — and its weights are open while Gemini 4 Carbon is API-only.
Lowest cost at scale
Gemma 4 26B A4B
At $0.12/$0.37 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 Gemma 4 26B A4B's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemma 4 26B A4B
At $0.12/$0.37 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
→ Gemma 4 26B A4B
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 fast, cheap inference from a sparse moe (3.8b active of 25.2b total)
→ Gemma 4 26B A4B
That is its strongest area.
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.
Gemma 4 26B A4B: where it fits
An Apache-2.0 open MoE with 25.2B total but only 3.8B active parameters, delivering near-31B-dense quality at a fraction of the inference cost. Released April 2, 2026 by Google, it is built for fast, cheap inference from a sparse MoE (3.8B active of 25.2B total), near-31B-dense quality at a fraction of the compute and memory-bandwidth cost, strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6), and multimodal input (text/image, plus video processed as frames up to 60s) with native function calling.
Its trade-offs: all 25.2B parameters must be loaded into memory even though only 3.8B are active per token, and 256K context trails 1M-token frontier rivals, and this variant has no audio input (audio is E2B/E4B/12B only). At $0.12 in / $0.37 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because Gemini 4 Carbon and Gemma 4 26B A4B come from the same lab (Google), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Gemini 4 Carbon is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to Gemini 4 Carbon and drop down only with a concrete reason.
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See pricingFrequently asked questions
Is Gemini 4 Carbon or Gemma 4 26B A4B 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 Gemma 4 26B A4B leans toward fast, cheap inference from a sparse moe (3.8b active of 25.2b total), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 4 Carbon or Gemma 4 26B A4B?
Gemma 4 26B A4B 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.
Should I upgrade from Gemma 4 26B A4B to Gemini 4 Carbon?
Since both are Google models, the newer one (Gemini 4 Carbon) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Gemini 4 Carbon or Gemma 4 26B A4B?
Gemini 4 Carbon — released October 28, 2026, about 7 months after Gemma 4 26B A4B.
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.