Gemma 4 26B A4B vs MiMo-V2.6-Pro
Google · US | Xiaomi · China · 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 MiMo-V2.6-Pro for natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters or 1.02 trillion total parameters, 42b active per token (sparse moe), mit-licensed and self-hostable. On a tight budget at scale, Gemma 4 26B A4B is the value pick.
Gemma 4 26B A4B (Google, US) and MiMo-V2.6-Pro (Xiaomi, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. MiMo-V2.6-Pro is xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: Gemma 4 26B A4B is about 3.6× cheaper on input ($0.12/$0.37 per 1M tokens vs $0.435/$0.87 per 1M tokens) — meaningful once you are processing millions of tokens a month.
- ▸Context window: MiMo-V2.6-Pro holds 4× more — 1M tokens (~1,573 pages) vs 256K (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: MiMo-V2.6-Pro is the newer model by about 6 months (released September 22, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | Gemma 4 26B A4B | MiMo-V2.6-Pro |
|---|---|---|
| Provider | Google (US) | Xiaomi (China) |
| Released | April 2, 2026 | September 22, 2026 |
| Context window | 256K (~393 pages) | 1M tokens (~1,573 pages) |
| Price (in/out) | $0.12/$0.37 per 1M tokens | $0.435/$0.87 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, image, video, code | text, image, video, audio |
| 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
At $0.12/$0.37 per 1M tokens it undercuts MiMo-V2.6-Pro ($0.435/$0.87 per 1M tokens), and that gap compounds at volume.
Near-31B-dense quality at a fraction of the compute and memory-bandwidth cost
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 runs cheaper at $0.12/$0.37 per 1M tokens.
Strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6)
Gemma 4 26B A4B
Gemma 4 26B A4B lists strong reasoning and coding (88.3% AIME 2026 no-tools, 77.1% LiveCodeBench v6) among its strengths; MiMo-V2.6-Pro does not.
Natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters
MiMo-V2.6-Pro
Gemma 4 26B A4B is comparatively weak here — 256K context trails 1M-token frontier rivals, and this variant has no audio input (audio is E2B/E4B/12B only)
1.02 trillion total parameters, 42B active per token (sparse MoE), MIT-licensed and self-hostable
MiMo-V2.6-Pro
Its 1M tokens window holds about 4× more than Gemma 4 26B A4B's 256K in a single prompt.
Reported Artificial Analysis Intelligence Index score of 46
MiMo-V2.6-Pro
Xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026 — and it carries the larger 1M tokens context.
Lowest cost at scale
Gemma 4 26B A4B
At $0.12/$0.37 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
MiMo-V2.6-Pro
Its 1M tokens window is about 4× larger than Gemma 4 26B A4B's 256K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemma 4 26B A4B
At $0.12/$0.37 per 1M tokens it undercuts MiMo-V2.6-Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ MiMo-V2.6-Pro
Larger 1M tokens window fits more in one prompt.
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 natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters
→ MiMo-V2.6-Pro
That is its strongest area.
An enterprise with regional data-residency rules
→ Gemma 4 26B A4B or MiMo-V2.6-Pro
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
MiMo-V2.6-Pro: where it fits
Xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026. Released September 22, 2026 by Xiaomi, it is built for natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters, 1.02 trillion total parameters, 42B active per token (sparse MoE), MIT-licensed and self-hostable, reported Artificial Analysis Intelligence Index score of 46, and a separate 'UltraSpeed' variant reportedly delivers up to 20x faster output than Pro at similar quality for high-throughput use cases.
Its trade-offs: first-generation omnimodal release from Xiaomi's MiMo line — benchmark claims are largely Xiaomi's own reporting, not yet widely independently verified, an Artificial Analysis Index score of 46 trails several established frontier models, and no official API pricing from Xiaomi directly — the listed price reflects third-party inference providers (e.g. OpenRouter), which can change independently of Xiaomi's own terms. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Gemma 4 26B A4B (US) and MiMo-V2.6-Pro (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Gemma 4 26B A4B is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Gemma 4 26B A4B and MiMo-V2.6-Pro 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 pricingFrequently asked questions
Is Gemma 4 26B A4B or MiMo-V2.6-Pro 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 MiMo-V2.6-Pro leans toward natively omnimodal — text, image, video and audio in one model family, not bolted-on modality adapters, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemma 4 26B A4B or MiMo-V2.6-Pro?
Gemma 4 26B A4B is cheaper — $0.12/$0.37 per 1M tokens vs $0.435/$0.87 per 1M tokens, roughly 3.6× apart on input.
Which has the bigger context window?
MiMo-V2.6-Pro — 1M tokens vs 256K, about 4× 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 MiMo-V2.6-Pro together?
Yes — a multi-model platform like LumiChats gives you Gemma 4 26B A4B, MiMo-V2.6-Pro 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 MiMo-V2.6-Pro?
MiMo-V2.6-Pro — released September 22, 2026, about 6 months after Gemma 4 26B A4B.
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.