LFM3-1.7B vs Llama 4 Maverick
Liquid AI · US | Meta · US · 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 Llama 4 Maverick for open weights, 1m context or strong image + text understanding.
LFM3-1.7B (Liquid AI) and Llama 4 Maverick (Meta) are two of the models people most often weigh against each other in 2026. 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. Llama 4 Maverick is meta's open-weight 1M-context multimodal model for self-hosted deployments. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Context window: Llama 4 Maverick holds 3.9× more — 1M (~1,500 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 19 months (released October 27, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | LFM3-1.7B | Llama 4 Maverick |
|---|---|---|
| Provider | Liquid AI (US) | Meta (US) |
| Released | October 27, 2026 | April 2025 |
| Context window | 256K tokens (~384 pages) | 1M (~1,500 pages) |
| Price (in/out) | Open weight (self-host / free) | Open weight (self-host / free) |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text | text, image, code |
| 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
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.
Liquid says it can power agentic applications that used to need 9B parameters
LFM3-1.7B
LFM3-1.7B lists liquid says it can power agentic applications that used to need 9B parameters among its strengths; Llama 4 Maverick does not.
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; Llama 4 Maverick does not.
Open weights, 1M context
Llama 4 Maverick
Its 1M window holds about 3.9× more than LFM3-1.7B's 256K tokens in a single prompt.
Strong image + text understanding
Llama 4 Maverick
Meta's open-weight 1M-context multimodal model for self-hosted deployments — and it carries the larger 1M context.
Self-hostable
Llama 4 Maverick
Llama 4 Maverick lists self-hostable among its strengths; LFM3-1.7B does not.
Largest single-prompt input
Llama 4 Maverick
Its 1M window is about 3.9× larger than LFM3-1.7B's 256K tokens, fitting roughly 1,500 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ Llama 4 Maverick
Larger 1M 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 open weights, 1m context
→ Llama 4 Maverick
That is its strongest area.
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.
Llama 4 Maverick: where it fits
Meta's open-weight 1M-context multimodal model for self-hosted deployments. Released April 2025 by Meta, it is built for open weights, 1M context, strong image + text understanding, self-hostable, and 400B MoE, 17B active.
Its trade-offs: needs serious hardware to self-host, and trails closed frontier on reasoning. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
LFM3-1.7B and Llama 4 Maverick overlap enough that the right pick depends on your specific job. Llama 4 Maverick holds the larger context; and each leads in its own area — LFM3-1.7B for very small open-weight text model - about 1.73b parameters with a 256k-token context for on-device use, Llama 4 Maverick for open weights, 1m context. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both LFM3-1.7B and Llama 4 Maverick 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 Llama 4 Maverick 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 Llama 4 Maverick leans toward open weights, 1m context, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, LFM3-1.7B or Llama 4 Maverick?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Llama 4 Maverick — 1M vs 256K tokens, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both LFM3-1.7B and Llama 4 Maverick together?
Yes — a multi-model platform like LumiChats gives you LFM3-1.7B, Llama 4 Maverick 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 Llama 4 Maverick?
LFM3-1.7B — released October 27, 2026, about 19 months after Llama 4 Maverick.
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.