Gemini 4 Argon vs Gemini 4 Carbon
Google · US | Google · US · Updated June 2026
Quick verdict
Both are Google models. Gemini 4 Carbon is the newer, generally stronger default; reach for Gemini 4 Argon when a specific cost or latency profile matters more than the latest capabilities.
Gemini 4 Argon and Gemini 4 Carbon are both Google models, so the real question is not which lab to trust but which tier fits your workload and budget. Gemini 4 Argon is google's Gemini 4 Argon, broadly available October 13, 2026 - a 1M-context model at $2/$10 introductory pricing (doubling December 1). 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. 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
- ▸Context window: 1M tokens vs 1M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
- ▸Recency: Gemini 4 Carbon is the newer model by about 15 days (released October 28, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Gemini 4 Argon | Gemini 4 Carbon |
|---|---|---|
| Provider | Google (US) | Google (US) |
| Released | October 13, 2026 | October 28, 2026 |
| Context window | 1M tokens (~1,573 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | $2/$10 per 1M tokens | $2/$10 per 1M tokens |
| Open weight? | No — API only | No — API only |
| Modalities | text, image, audio, video, code | text, image, audio, video, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses
Gemini 4 Argon
Gemini 4 Carbon is comparatively weak here — google has not published context or modality specs - the 1M window and modalities shown come from Artificial Analysis and Vals
Google-reported DeepSWE v1.1 of 77.9% and LVBench long-video understanding of 91.7%
Gemini 4 Argon
Gemini 4 Carbon is comparatively weak here — introductory pricing rises to $4/$20 afterward, and Google has not said when that happens
Artificial Analysis Intelligence Index of 53 at high effort (AI Weekly)
Gemini 4 Argon
Gemini 4 Argon lists artificial Analysis Intelligence Index of 53 at high effort (AI Weekly) among its strengths; Gemini 4 Carbon does not.
Ranked first on the Artificial Analysis Intelligence Index v5.0 with 59 at launch (Artificial Analysis now shows 60)
Gemini 4 Carbon
Gemini 4 Argon is comparatively weak here — verbose: about 62K output tokens per Artificial Analysis task, so cost per task is high
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; Gemini 4 Argon does not.
Which should you pick?
Someone analysing very long documents or codebases
→ Gemini 4 Argon
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is 1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses
→ Gemini 4 Argon
It is specifically built for that.
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
That is its strongest area.
Gemini 4 Argon: where it fits
Google's Gemini 4 Argon, broadly available October 13, 2026 - a 1M-context model at $2/$10 introductory pricing (doubling December 1). Released October 13, 2026 by Google, it is built for 1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses, google-reported DeepSWE v1.1 of 77.9% and LVBench long-video understanding of 91.7%, and artificial Analysis Intelligence Index of 53 at high effort (AI Weekly).
Its trade-offs are real: introductory $2/$10 pricing ends November 30; from December 1 it doubles to $4/$20, verbose: about 62K output tokens per Artificial Analysis task, so cost per task is high, and announced September 30 for trusted cyber defenders only; broad paid-tier availability followed October 13 (not on the free tier). At $2 in / $10 out per million tokens, it sits in the mid price band.
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: 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.
The bottom line for this matchup
Because Gemini 4 Argon and Gemini 4 Carbon 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 Argon or Gemini 4 Carbon 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 Argon leans toward 1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses while Gemini 4 Carbon leans toward ranked first on the artificial analysis intelligence index v5.0 with 59 at launch (artificial analysis now shows 60), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 4 Argon or Gemini 4 Carbon?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Effectively neither — 1M tokens vs 1M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from Gemini 4 Argon 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 Argon or Gemini 4 Carbon?
Gemini 4 Carbon — released October 28, 2026, about 15 days after Gemini 4 Argon.
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.