Both are Google models. Gemma 4 26B A4B 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.
Gemma 4 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. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. 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
Context window: Gemma 4 26B A4B holds 1× more — 256K (~393 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.
Specifications
Spec
Gemma 4
Gemma 4 26B A4B
Provider
Google (US)
Google (US)
Released
April 2, 2026
April 2, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.15/$0.6 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Self-hosted, data-private deployment: Gemma 4 — A core design strength of Gemma 4.
Running locally or on edge devices: Gemma 4 — A core design strength of Gemma 4.
Fine-tuning on your own data: Gemma 4 — A core design strength of Gemma 4.
Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total): Gemma 4 26B A4B — A core design strength of Gemma 4 26B A4B.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost: Gemma 4 26B A4B — A core design strength of Gemma 4 26B A4B.
Strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6): Gemma 4 26B A4B — A core design strength of Gemma 4 26B A4B.
Lowest cost at scale: Gemma 4 — At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Gemma 4 26B A4B — Its 256K window is about 1× larger, fitting roughly 393 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 Gemma 4 26B A4B, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemma 4 26B A4B — Larger 256K window fits more in one prompt.
Anyone whose priority is self-hosted, data-private deployment: Gemma 4 — 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.
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 are real: 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.
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 $0.15 in / $0.6 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because Gemma 4 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. Gemma 4 26B A4B 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 Gemma 4 26B A4B and drop down only with a concrete reason.
Frequently asked questions
Is Gemma 4 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, Gemma 4 leans toward self-hosted, data-private deployment 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, Gemma 4 or Gemma 4 26B A4B?
Gemma 4 is cheaper — Open weight (self-host / free) vs $0.15/$0.6 per 1M tokens.
Which has the bigger context window?
Gemma 4 26B A4B — 256K vs 256K, about 1× 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 Gemma 4?
Since both are Google models, the newer one (Gemma 4 26B A4B) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Gemma 4 or Gemma 4 26B A4B?
They were released around the same time (April 2, 2026 and April 2, 2026).
Gemma 4 vs Gemma 4 26B A4B
Google · US | Google · US · Updated June 2026
Quick verdict
Both are Google models. Gemma 4 26B A4B 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.
Gemma 4 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. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. 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
▸Context window: Gemma 4 26B A4B holds 1× more — 256K (~393 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.
Side-by-side specs
Spec
Gemma 4
Gemma 4 26B A4B
Provider
Google (US)
Google (US)
Released
April 2, 2026
April 2, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.15/$0.6 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Self-hosted, data-private deployment
Gemma 4
A core design strength of Gemma 4.
Running locally or on edge devices
Gemma 4
A core design strength of Gemma 4.
Fine-tuning on your own data
Gemma 4
A core design strength of Gemma 4.
Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total)
Gemma 4 26B A4B
A core design strength of Gemma 4 26B A4B.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost
At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Gemma 4 26B A4B
Its 256K window is about 1× larger, fitting roughly 393 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 Gemma 4 26B A4B, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemma 4 26B A4B
Larger 256K window fits more in one prompt.
Anyone whose priority is self-hosted, data-private deployment
→ Gemma 4
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.
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 are real: 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.
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 $0.15 in / $0.6 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because Gemma 4 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. Gemma 4 26B A4B 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 Gemma 4 26B A4B and drop down only with a concrete reason.
Want both Gemma 4 and Gemma 4 26B A4B 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.
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, Gemma 4 leans toward self-hosted, data-private deployment 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, Gemma 4 or Gemma 4 26B A4B?
Gemma 4 is cheaper — Open weight (self-host / free) vs $0.15/$0.6 per 1M tokens.
Which has the bigger context window?
Gemma 4 26B A4B — 256K vs 256K, about 1× 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 Gemma 4?
Since both are Google models, the newer one (Gemma 4 26B A4B) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Gemma 4 or Gemma 4 26B A4B?
They were released around the same time (April 2, 2026 and April 2, 2026).
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.