Gemini 4 Argon vs Gemma 4
Google · US | Google · US · Updated June 2026
Quick verdict
Both are Google models. Gemini 4 Argon is the newer, generally stronger default; reach for Gemma 4 when its lower price or a specific cost or latency profile matters more than the latest capabilities.
Gemini 4 Argon and Gemma 4 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). Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. 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
- ▸Cost model: Gemma 4 ships open weights you can self-host (hardware cost only, no per-token fee), while Gemini 4 Argon is API-metered at $2/$10 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
- ▸Context window: Gemini 4 Argon holds 4.1× more — 1M tokens (~1,573 pages) vs 256K (~384 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 Argon is the newer model by about 6 months (released October 13, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Gemini 4 Argon | Gemma 4 |
|---|---|---|
| Provider | Google (US) | Google (US) |
| Released | October 13, 2026 | April 2, 2026 |
| Context window | 1M tokens (~1,573 pages) | 256K (~384 pages) |
| Price (in/out) | $2/$10 per 1M tokens | Open weight (self-host / free) |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, image, audio, video, code | text, image, 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
Its 1M tokens window holds about 4.1× more than Gemma 4's 256K in a single prompt.
Google-reported DeepSWE v1.1 of 77.9% and LVBench long-video understanding of 91.7%
Gemini 4 Argon
Google's Gemini 4 Argon, broadly available October 13, 2026 - a 1M-context model at $2/$10 introductory pricing (doubling December 1) — and it carries the larger 1M tokens context.
Artificial Analysis Intelligence Index of 53 at high effort (AI Weekly)
Gemini 4 Argon
Google's Gemini 4 Argon, broadly available October 13, 2026 - a 1M-context model at $2/$10 introductory pricing (doubling December 1) — and it is the newer of the two.
Self-hosted, data-private deployment
Gemma 4
Open weights make this possible at all — Gemini 4 Argon is API-only, so it cannot leave the vendor's servers.
Running locally or on edge devices
Gemma 4
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting — and its weights are open while Gemini 4 Argon is API-only.
Fine-tuning on your own data
Gemma 4
Gemma 4 lists fine-tuning on your own data among its strengths; Gemini 4 Argon does not.
Lowest cost at scale
Gemma 4
Its weights are open, so at volume you pay for your own hardware instead of Gemini 4 Argon's $2/$10 per 1M tokens.
Largest single-prompt input
Gemini 4 Argon
Its 1M tokens window is about 4.1× larger than Gemma 4's 256K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemma 4
At Open weight (self-host / free) it undercuts Gemini 4 Argon, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 4 Argon
Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Gemma 4
Open weights let you run it on your own hardware; Gemini 4 Argon is API-only.
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 self-hosted, data-private deployment
→ Gemma 4
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.
Gemma 4: where it fits
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Released April 2, 2026 by Google, it is built for self-hosted, data-private deployment, running locally or on edge devices, fine-tuning on your own data, and multimodal tasks over a 256K context.
Its trade-offs: trails frontier closed models on the hardest tasks, and needs your own hardware to run. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Because Gemini 4 Argon and Gemma 4 come from the same lab (Google), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Gemini 4 Argon 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 Argon and drop down only with a concrete reason.
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See pricingFrequently asked questions
Is Gemini 4 Argon or Gemma 4 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 Gemma 4 leans toward self-hosted, data-private deployment, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 4 Argon or Gemma 4?
Gemma 4 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 4 Argon 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 Argon — 1M tokens vs 256K, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from Gemma 4 to Gemini 4 Argon?
Since both are Google models, the newer one (Gemini 4 Argon) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Gemini 4 Argon or Gemma 4?
Gemini 4 Argon — released October 13, 2026, about 6 months after Gemma 4.
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.