Gemini 4 Argon vs MAI-1-preview

Google · US  |  Microsoft · US · Updated June 2026

Quick verdict

Pick Gemini 4 Argon for 1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses or google-reported deepswe v1.1 of 77.9% and lvbench long-video understanding of 91.7%. 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. On a tight budget at scale, MAI-1-preview is the value pick.

Gemini 4 Argon (Google) and MAI-1-preview (Microsoft) are two of the models people most often weigh against each other in 2026. 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). 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 and context window — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecGemini 4 ArgonMAI-1-preview
ProviderGoogle (US) Microsoft (US)
ReleasedOctober 13, 2026 August 28, 2025
Context window1M tokens (~1,573 pages) 128K (~192 pages)
Price (in/out)$2/$10 per 1M tokens Not published
Open weight?No — API only No — API only
Modalitiestext, image, audio, video, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot 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 8.2× more than MAI-1-preview's 128K 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.

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; Gemini 4 Argon 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; Gemini 4 Argon 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; Gemini 4 Argon does not.

Lowest cost at scale

MAI-1-preview

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 8.2× larger than MAI-1-preview's 128K, fitting roughly 1,573 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ MAI-1-preview

At Not published 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.

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 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.

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.

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

Gemini 4 Argon and MAI-1-preview overlap enough that the right pick depends on your specific job. MAI-1-preview costs less per token; Gemini 4 Argon holds the larger context; and each leads in its own area — Gemini 4 Argon for 1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses, MAI-1-preview for microsoft's first fully in-house, end-to-end foundation model - a historic break from relying solely on openai. Rather than crowning one, run the same hard task through both once and let the results decide.

Want both Gemini 4 Argon 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.

See pricing

Frequently asked questions

Is Gemini 4 Argon 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, 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 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, Gemini 4 Argon or MAI-1-preview?

MAI-1-preview is cheaper — $2/$10 per 1M tokens vs Not published.

Which has the bigger context window?

Gemini 4 Argon — 1M tokens vs 128K, about 8.2× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Gemini 4 Argon and MAI-1-preview together?

Yes — a multi-model platform like LumiChats gives you Gemini 4 Argon, 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, Gemini 4 Argon or MAI-1-preview?

Gemini 4 Argon — released October 13, 2026, about 14 months after MAI-1-preview.

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.