Pick Gemma 4 26B A4B for fast, cheap inference from a sparse moe (3.8b active of 25.2b total) or near-31b-dense quality at a fraction of the compute and memory-bandwidth cost. Pick MAI-1-preview for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai or ranked in the top 15 on lm arena at launch. Choose Gemma 4 26B A4B if you need self-hosting or data privacy; MAI-1-preview if you want a managed API.
Gemma 4 26B A4B (Google) and MAI-1-preview (Microsoft) are two of the models people most often weigh against each other in 2026. 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. MAI-1-preview is microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Gemma 4 26B A4B ships open weights you can self-host (hardware cost only, no per-token fee), while MAI-1-preview is API-metered at Not published. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: Gemma 4 26B A4B holds 2× more — 256K (~393 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Gemma 4 26B A4B is the newer model by about 7 months (released April 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Gemma 4 26B A4B
MAI-1-preview
Provider
Google (US)
Microsoft (US)
Released
April 2, 2026
August 28, 2025
Context window
256K (~393 pages)
128K (~192 pages)
Price (in/out)
$0.12/$0.37 per 1M tokens
Not published
Open weight?
Yes — self-hostable
No — API only
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total): 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 carries the larger 256K context.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost: Gemma 4 26B A4B — Its 256K window holds about 2× more than MAI-1-preview's 128K in a single prompt.
Strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6): Gemma 4 26B A4B — MAI-1-preview is comparatively weak here — distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry
Microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI: MAI-1-preview — MAI-1-preview lists microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI among its strengths; Gemma 4 26B A4B does not.
Ranked in the top 15 on LM Arena at launch: MAI-1-preview — MAI-1-preview lists ranked in the top 15 on LM Arena at launch among its strengths; Gemma 4 26B A4B does not.
Trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment: MAI-1-preview — MAI-1-preview lists trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment among its strengths; Gemma 4 26B A4B does not.
Lowest cost at scale: MAI-1-preview — Its weights are open, so at volume you pay for your own hardware instead of Gemma 4 26B A4B's $0.12/$0.37 per 1M tokens.
Largest single-prompt input: Gemma 4 26B A4B — Its 256K window is about 2× larger than MAI-1-preview's 128K, fitting roughly 393 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MAI-1-preview — At Not published 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.
A team with data-privacy or self-hosting needs: Gemma 4 26B A4B — Open weights let you run it on your own hardware; MAI-1-preview is API-only.
Anyone whose priority is fast, cheap inference from a sparse moe (3.8b active of 25.2b total): Gemma 4 26B A4B — It is specifically built for that.
Anyone whose priority is microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai: MAI-1-preview — That is its strongest area.
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 are real: 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.
MAI-1-preview: where it fits
Microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. Released August 28, 2025 by Microsoft, it is built for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI, ranked in the top 15 on LM Arena at launch, trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment, and rolled into Copilot alongside OpenAI models, giving Microsoft a real second option.
Its trade-offs: a 'preview' release, not yet positioned as Microsoft's primary Copilot model, no public per-token API pricing - not sold as a standalone product, and distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry.
The bottom line for this matchup
The defining split here is open vs. closed. Gemma 4 26B A4B gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. MAI-1-preview 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.
Frequently asked questions
Is Gemma 4 26B A4B or MAI-1-preview 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 26B A4B leans toward fast, cheap inference from a sparse moe (3.8b active of 25.2b total) while MAI-1-preview leans toward microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 26B A4B or MAI-1-preview?
Gemma 4 26B A4B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while MAI-1-preview is API-metered at Not published. 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?
Gemma 4 26B A4B — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemma 4 26B A4B and MAI-1-preview together?
Yes — a multi-model platform like LumiChats gives you Gemma 4 26B A4B, MAI-1-preview 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, Gemma 4 26B A4B or MAI-1-preview?
Gemma 4 26B A4B — released April 2, 2026, about 7 months after MAI-1-preview.
Gemma 4 26B A4B vs MAI-1-preview
Google · US | Microsoft · US · Updated June 2026
Quick verdict
Pick Gemma 4 26B A4B for fast, cheap inference from a sparse moe (3.8b active of 25.2b total) or near-31b-dense quality at a fraction of the compute and memory-bandwidth cost. Pick MAI-1-preview for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai or ranked in the top 15 on lm arena at launch. Choose Gemma 4 26B A4B if you need self-hosting or data privacy; MAI-1-preview if you want a managed API.
Gemma 4 26B A4B (Google) and MAI-1-preview (Microsoft) are two of the models people most often weigh against each other in 2026. 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. MAI-1-preview is microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. 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
▸Cost model: Gemma 4 26B A4B ships open weights you can self-host (hardware cost only, no per-token fee), while MAI-1-preview is API-metered at Not published. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: Gemma 4 26B A4B holds 2× more — 256K (~393 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Gemma 4 26B A4B is the newer model by about 7 months (released April 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Gemma 4 26B A4B
MAI-1-preview
Provider
Google (US)
Microsoft (US)
Released
April 2, 2026
August 28, 2025
Context window
256K (~393 pages)
128K (~192 pages)
Price (in/out)
$0.12/$0.37 per 1M tokens
Not published
Open weight?
Yes — self-hostable
No — API only
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Fast, cheap inference from a sparse MoE (3.8B active of 25.2B total)
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 carries the larger 256K context.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost
Gemma 4 26B A4B
Its 256K window holds about 2× more than MAI-1-preview's 128K in a single prompt.
MAI-1-preview is comparatively weak here — distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry
Microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI
MAI-1-preview
MAI-1-preview lists microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI among its strengths; Gemma 4 26B A4B does not.
Ranked in the top 15 on LM Arena at launch
MAI-1-preview
MAI-1-preview lists ranked in the top 15 on LM Arena at launch among its strengths; Gemma 4 26B A4B does not.
Trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment
MAI-1-preview
MAI-1-preview lists trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment among its strengths; Gemma 4 26B A4B does not.
Lowest cost at scale
MAI-1-preview
Its weights are open, so at volume you pay for your own hardware instead of Gemma 4 26B A4B's $0.12/$0.37 per 1M tokens.
Largest single-prompt input
Gemma 4 26B A4B
Its 256K window is about 2× larger than MAI-1-preview's 128K, fitting roughly 393 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MAI-1-preview
At Not published 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.
A team with data-privacy or self-hosting needs
→ Gemma 4 26B A4B
Open weights let you run it on your own hardware; MAI-1-preview is API-only.
Anyone whose priority is fast, cheap inference from a sparse moe (3.8b active of 25.2b total)
→ Gemma 4 26B A4B
It is specifically built for that.
Anyone whose priority is microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai
→ MAI-1-preview
That is its strongest area.
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 are real: 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.
MAI-1-preview: where it fits
Microsoft's first fully in-house foundation model - a strategic break from sole reliance on OpenAI, trained on ~15,000 H100 GPUs. Released August 28, 2025 by Microsoft, it is built for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on OpenAI, ranked in the top 15 on LM Arena at launch, trained on roughly 15,000 NVIDIA H100 GPUs, a genuine internal infrastructure investment, and rolled into Copilot alongside OpenAI models, giving Microsoft a real second option.
Its trade-offs: a 'preview' release, not yet positioned as Microsoft's primary Copilot model, no public per-token API pricing - not sold as a standalone product, and distinct from Microsoft's later MAI-Thinking-1 reasoning model - an earlier, more general-purpose entry.
The bottom line for this matchup
The defining split here is open vs. closed. Gemma 4 26B A4B gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. MAI-1-preview 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 Gemma 4 26B A4B and MAI-1-preview 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.
Is Gemma 4 26B A4B or MAI-1-preview 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 26B A4B leans toward fast, cheap inference from a sparse moe (3.8b active of 25.2b total) while MAI-1-preview leans toward microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 26B A4B or MAI-1-preview?
Gemma 4 26B A4B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while MAI-1-preview is API-metered at Not published. 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?
Gemma 4 26B A4B — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemma 4 26B A4B and MAI-1-preview together?
Yes — a multi-model platform like LumiChats gives you Gemma 4 26B A4B, MAI-1-preview 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, Gemma 4 26B A4B or MAI-1-preview?
Gemma 4 26B A4B — released April 2, 2026, about 7 months after MAI-1-preview.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.