Llama 4 Scout vs MiMo-V2.6-Pro
Meta · US | Xiaomi · China · Updated June 2026
Quick verdict
Pick Llama 4 Scout for largest advertised context (10m) or open weights, single-gpu friendly. 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, Llama 4 Scout is the value pick.
Llama 4 Scout (Meta, 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. Llama 4 Scout is the 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. 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
- ▸Context window: Llama 4 Scout holds 9.5× more — 10M (~15,000 pages) vs 1M tokens (~1,573 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 18 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 | Llama 4 Scout | MiMo-V2.6-Pro |
|---|---|---|
| Provider | Meta (US) | Xiaomi (China) |
| Released | April 2025 | September 22, 2026 |
| Context window | 10M (~15,000 pages) | 1M tokens (~1,573 pages) |
| Price (in/out) | Open weight (self-host / free) | $0.435/$0.87 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, image, code | text, image, video, audio |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | 15% | Not published |
Who wins what
Largest advertised context (10M)
Llama 4 Scout
Its 10M window holds about 9.5× more than MiMo-V2.6-Pro's 1M tokens in a single prompt.
Open weights, single-GPU friendly
Llama 4 Scout
The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller — and it carries the larger 10M context.
Self-hosted, data-private deployment
Llama 4 Scout
Llama 4 Scout lists self-hosted, data-private deployment 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
Xiaomi's flagship omnimodal model — 1.02T parameters, native text/image/video/audio, MIT-licensed, released September 22, 2026 — and it is the newer of the two.
1.02 trillion total parameters, 42B active per token (sparse MoE), MIT-licensed and self-hostable
MiMo-V2.6-Pro
MiMo-V2.6-Pro lists 1.02 trillion total parameters, 42B active per token (sparse MoE), MIT-licensed and self-hostable among its strengths; Llama 4 Scout does not.
Reported Artificial Analysis Intelligence Index score of 46
MiMo-V2.6-Pro
MiMo-V2.6-Pro lists reported Artificial Analysis Intelligence Index score of 46 among its strengths; Llama 4 Scout does not.
Lowest cost at scale
Llama 4 Scout
Its weights are open, so at volume you pay for your own hardware instead of MiMo-V2.6-Pro's $0.435/$0.87 per 1M tokens.
Largest single-prompt input
Llama 4 Scout
Its 10M window is about 9.5× larger than MiMo-V2.6-Pro's 1M tokens, fitting roughly 15,000 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Llama 4 Scout
At Open weight (self-host / free) it undercuts MiMo-V2.6-Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Llama 4 Scout
Larger 10M window fits more in one prompt.
Anyone whose priority is largest advertised context (10m)
→ Llama 4 Scout
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
→ Llama 4 Scout 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.
Llama 4 Scout: where it fits
The 10M-token open-weight giant — enormous on paper, but usable recall is far smaller. Released April 2025 by Meta, it is built for largest advertised context (10M), open weights, single-GPU friendly, self-hosted, data-private deployment, and retrieval over very long inputs.
Its trade-offs are real: effective recall degrades far below 10M, and ~15% on long-context multi-needle reasoning. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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." Llama 4 Scout (US) and MiMo-V2.6-Pro (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Llama 4 Scout 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 Llama 4 Scout 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 Llama 4 Scout 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, Llama 4 Scout leans toward largest advertised context (10m) 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, Llama 4 Scout or MiMo-V2.6-Pro?
Llama 4 Scout is cheaper — Open weight (self-host / free) vs $0.435/$0.87 per 1M tokens.
Which has the bigger context window?
Llama 4 Scout — 10M vs 1M tokens, about 9.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Llama 4 Scout and MiMo-V2.6-Pro together?
Yes — a multi-model platform like LumiChats gives you Llama 4 Scout, 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, Llama 4 Scout or MiMo-V2.6-Pro?
MiMo-V2.6-Pro — released September 22, 2026, about 18 months after Llama 4 Scout.
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.