LFM3-1.7B vs MiMo-V2.6-Pro
Liquid AI · US | Xiaomi · China · Updated June 2026
Quick verdict
Pick LFM3-1.7B for very small open-weight text model - about 1.73b parameters with a 256k-token context for on-device use or liquid says it can power agentic applications that used to need 9b parameters. 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, LFM3-1.7B is the value pick.
LFM3-1.7B (Liquid AI, 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. LFM3-1.7B is liquid AI's October 27, 2026 on-device text model - about 1.73B parameters and 256K context, with open weights under a license capped at $10M annual revenue. 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: MiMo-V2.6-Pro holds 4.1× more — 1M tokens (~1,573 pages) vs 256K tokens (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: LFM3-1.7B is the newer model by about 35 days (released October 27, 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 | LFM3-1.7B | MiMo-V2.6-Pro |
|---|---|---|
| Provider | Liquid AI (US) | Xiaomi (China) |
| Released | October 27, 2026 | September 22, 2026 |
| Context window | 256K tokens (~384 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 | text, image, video, audio |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Very small open-weight text model - about 1.73B parameters with a 256K-token context for on-device use
LFM3-1.7B
MiMo-V2.6-Pro is comparatively weak here — an Artificial Analysis Index score of 46 trails several established frontier models
Liquid says it can power agentic applications that used to need 9B parameters
LFM3-1.7B
Liquid AI's October 27, 2026 on-device text model - about 1.73B parameters and 256K context, with open weights under a license capped at $10M annual revenue — and it is the newer of the two.
Part of a six-model LFM3 family covering text, vision, audio, omni and decision tasks
LFM3-1.7B
LFM3-1.7B lists part of a six-model LFM3 family covering text, vision, audio, omni and decision tasks 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
LFM3-1.7B is comparatively weak here — text-only; vision and audio need other LFM3 checkpoints
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 4.1× more than LFM3-1.7B's 256K tokens 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
LFM3-1.7B
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
MiMo-V2.6-Pro
Its 1M tokens window is about 4.1× larger than LFM3-1.7B's 256K tokens, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ LFM3-1.7B
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
→ MiMo-V2.6-Pro
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is very small open-weight text model - about 1.73b parameters with a 256k-token context for on-device use
→ LFM3-1.7B
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
→ LFM3-1.7B 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.
LFM3-1.7B: where it fits
Liquid AI's October 27, 2026 on-device text model - about 1.73B parameters and 256K context, with open weights under a license capped at $10M annual revenue. Released October 27, 2026 by Liquid AI, it is built for very small open-weight text model - about 1.73B parameters with a 256K-token context for on-device use, liquid says it can power agentic applications that used to need 9B parameters, part of a six-model LFM3 family covering text, vision, audio, omni and decision tasks, and supports 16 languages.
Its trade-offs are real: lFM Open License v1.0 covers commercial use only below $10M annual revenue; larger firms need a paid license, liquid says it is not recommended for agentic coding or complex multi-step reasoning because of its size, text-only; vision and audio need other LFM3 checkpoints, and no published per-token API price found. 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." LFM3-1.7B (US) and MiMo-V2.6-Pro (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. LFM3-1.7B 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 LFM3-1.7B 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 LFM3-1.7B 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, LFM3-1.7B leans toward very small open-weight text model - about 1.73b parameters with a 256k-token context for on-device use 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, LFM3-1.7B or MiMo-V2.6-Pro?
LFM3-1.7B is cheaper — Open weight (self-host / free) vs $0.435/$0.87 per 1M tokens.
Which has the bigger context window?
MiMo-V2.6-Pro — 1M tokens vs 256K tokens, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both LFM3-1.7B and MiMo-V2.6-Pro together?
Yes — a multi-model platform like LumiChats gives you LFM3-1.7B, 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, LFM3-1.7B or MiMo-V2.6-Pro?
LFM3-1.7B — released October 27, 2026, about 35 days after MiMo-V2.6-Pro.
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.