Hunyuan Hy4 vs LFM3-1.7B

Tencent · China  |  Liquid AI · US · Updated June 2026

Quick verdict

Pick Hunyuan Hy4 for first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview or tencent-reported gains over the preview of 19.1% on gamedev and 9.8% on gamelogic. 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. Choose LFM3-1.7B if you need self-hosting or data privacy; Hunyuan Hy4 if you want a managed API.

Hunyuan Hy4 (Tencent, China) and LFM3-1.7B (Liquid AI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Hunyuan Hy4 is tencent's November 4, 2026 full Hy4 release - a 1M-context model that adds vision and computer use at about $0.90/$2.70, with weights promised but not yet public. 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. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecHunyuan Hy4LFM3-1.7B
ProviderTencent (China) Liquid AI (US)
ReleasedNovember 4, 2026 October 27, 2026
Context window1M tokens (~1,573 pages) 256K tokens (~384 pages)
Price (in/out)$0.9/$2.7 per 1M tokens Open weight (self-host / free)
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, code text
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

First Hunyuan model with vision and computer use, adding image input to the text-only Hy4 Preview

Hunyuan Hy4

LFM3-1.7B is comparatively weak here — text-only; vision and audio need other LFM3 checkpoints

Tencent-reported gains over the preview of 19.1% on GameDev and 9.8% on GameLogic

Hunyuan Hy4

Tencent's November 4, 2026 full Hy4 release - a 1M-context model that adds vision and computer use at about $0.90/$2.70, with weights promised but not yet public — and it carries the larger 1M tokens context.

Tencent-reported financial evaluation of 3.04, ahead of DeepSeek V4.1 Flash 1017 at 2.97

Hunyuan Hy4

Tencent's November 4, 2026 full Hy4 release - a 1M-context model that adds vision and computer use at about $0.90/$2.70, with weights promised but not yet public — and it is the newer of the two.

Very small open-weight text model - about 1.73B parameters with a 256K-token context for on-device use

LFM3-1.7B

Open weights make this possible at all — Hunyuan Hy4 is API-only, so it cannot leave the vendor's servers.

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 its weights are open while Hunyuan Hy4 is API-only.

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; Hunyuan Hy4 does not.

Lowest cost at scale

LFM3-1.7B

Its weights are open, so at volume you pay for your own hardware instead of Hunyuan Hy4's $0.9/$2.7 per 1M tokens.

Largest single-prompt input

Hunyuan Hy4

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 Hunyuan Hy4, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ Hunyuan Hy4

Larger 1M tokens window fits more in one prompt.

A team with data-privacy or self-hosting needs

→ LFM3-1.7B

Open weights let you run it on your own hardware; Hunyuan Hy4 is API-only.

Anyone whose priority is first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview

→ Hunyuan Hy4

It is specifically built for that.

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

That is its strongest area.

An enterprise with regional data-residency rules

→ LFM3-1.7B or Hunyuan Hy4

Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

Hunyuan Hy4: where it fits

Tencent's November 4, 2026 full Hy4 release - a 1M-context model that adds vision and computer use at about $0.90/$2.70, with weights promised but not yet public. Released November 4, 2026 by Tencent, it is built for first Hunyuan model with vision and computer use, adding image input to the text-only Hy4 Preview, tencent-reported gains over the preview of 19.1% on GameDev and 9.8% on GameLogic, tencent-reported financial evaluation of 3.04, ahead of DeepSeek V4.1 Flash 1017 at 2.97, and about $0.90/$2.70 per million tokens, with 50% off on Tencent Cloud TokenHub through December 31, 2026 (OpenRouter lists $0.417/$1.25 with that discount).

Its trade-offs are real: weights not public as of November 5, 2026 - Tencent says weights and system cards will come in the coming days, and no license is announced yet, only the earlier Hy4 Preview is downloadable today (Apache 2.0), published improvements are Tencent's own and mostly relative to the preview, with no SWE-bench Verified figure, and sources differ on list price: Tencent says about $0.90/$2.70, while OpenRouter and Vals show $0.83/$2.50. At $0.9 in / $2.7 out per million tokens, it sits in the budget price band.

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: 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.

The bottom line for this matchup

The defining split here is open vs. closed. LFM3-1.7B gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Hunyuan Hy4 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.

Want both Hunyuan Hy4 and LFM3-1.7B 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 Hunyuan Hy4 or LFM3-1.7B 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, Hunyuan Hy4 leans toward first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview while LFM3-1.7B leans toward very small open-weight text model - about 1.73b parameters with a 256k-token context for on-device use, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Hunyuan Hy4 or LFM3-1.7B?

LFM3-1.7B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Hunyuan Hy4 is API-metered at $0.9/$2.7 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.

Which has the bigger context window?

Hunyuan Hy4 — 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 Hunyuan Hy4 and LFM3-1.7B together?

Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4, LFM3-1.7B 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, Hunyuan Hy4 or LFM3-1.7B?

Hunyuan Hy4 — released November 4, 2026, about 8 days after LFM3-1.7B.

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.