Gemini 3.5 Flash-Lite vs Hunyuan Hy4 Preview

Google · US  |  Tencent · China · Updated June 2026

Quick verdict

Pick Gemini 3.5 Flash-Lite for the cheapest gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work or simple classification, extraction and routing where flagship reasoning is wasted spend. Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). Choose Hunyuan Hy4 Preview if you need self-hosting or data privacy; Gemini 3.5 Flash-Lite if you want a managed API.

Gemini 3.5 Flash-Lite (Google, US) and Hunyuan Hy4 Preview (Tencent, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Gemini 3.5 Flash-Lite is google's cheapest July 2026 model at $0.30/$2.50 — a high-volume, low-cost Lite tier for simple work, not frontier reasoning. Hunyuan Hy4 Preview is tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecGemini 3.5 Flash-LiteHunyuan Hy4 Preview
ProviderGoogle (US) Tencent (China)
ReleasedJuly 21, 2026 August 28, 2026
Context window1M (~1,500 pages) 1M+ tokens (~1,500 pages)
Price (in/out)$0.3/$2.5 per 1M tokens $0.834/$2.501 per 1M tokens
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

The cheapest Gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work

Gemini 3.5 Flash-Lite

At $0.3/$2.5 per 1M tokens it undercuts Hunyuan Hy4 Preview ($0.834/$2.501 per 1M tokens), and that gap compounds at volume.

Simple classification, extraction and routing where flagship reasoning is wasted spend

Gemini 3.5 Flash-Lite

Hunyuan Hy4 Preview is comparatively weak here — labeled a 'preview', not yet Tencent's finalized GA flagship

Latency-sensitive pipelines that call a model on every request

Gemini 3.5 Flash-Lite

Google's cheapest July 2026 model at $0.30/$2.50 — a high-volume, low-cost Lite tier for simple work, not frontier reasoning — and it runs cheaper at $0.3/$2.5 per 1M tokens.

GPQA Diamond (92.3)

Hunyuan Hy4 Preview

Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and its weights are open while Gemini 3.5 Flash-Lite is API-only.

Terminal-Bench (85.4)

Hunyuan Hy4 Preview

Gemini 3.5 Flash-Lite is comparatively weak here — no published SWE-Bench Verified score

SWE-bench Multilingual (82.9)

Hunyuan Hy4 Preview

Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and it is the newer of the two.

Lowest cost at scale

Gemini 3.5 Flash-Lite

At $0.3/$2.5 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Which should you pick?

A cost-sensitive startup shipping high volume

Gemini 3.5 Flash-Lite

At $0.3/$2.5 per 1M tokens it undercuts Hunyuan Hy4 Preview, and on millions of tokens that margin decides the monthly bill.

A team with data-privacy or self-hosting needs

Hunyuan Hy4 Preview

Open weights let you run it on your own hardware; Gemini 3.5 Flash-Lite is API-only.

Anyone whose priority is the cheapest gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work

Gemini 3.5 Flash-Lite

It is specifically built for that.

Anyone whose priority is gpqa diamond (92.3)

Hunyuan Hy4 Preview

That is its strongest area.

An enterprise with regional data-residency rules

Gemini 3.5 Flash-Lite or Hunyuan Hy4 Preview

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

Gemini 3.5 Flash-Lite: where it fits

Google's cheapest July 2026 model at $0.30/$2.50 — a high-volume, low-cost Lite tier for simple work, not frontier reasoning. Released July 21, 2026 by Google, it is built for the cheapest Gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work, simple classification, extraction and routing where flagship reasoning is wasted spend, latency-sensitive pipelines that call a model on every request, and pairing with a stronger model as the cheap first pass in a cascade.

Its trade-offs are real: a Lite model — the weakest of the July 2026 Gemini line on hard reasoning and coding, google did not publish its exact context window, so 1M is inferred from the family, no published SWE-Bench Verified score, and outclassed by 3.6 Flash whenever a task needs real capability rather than raw throughput. At $0.3 in / $2.5 out per million tokens, it sits in the budget price band.

Hunyuan Hy4 Preview: where it fits

Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. Released August 28, 2026 by Tencent, it is built for gPQA Diamond (92.3), terminal-Bench (85.4), sWE-bench Multilingual (82.9), and large jump in long-horizon coding vs prior Hunyuan model (DeepSWE 28.0 to 64.3).

Its trade-offs: text-only, no native vision support, labeled a 'preview', not yet Tencent's finalized GA flagship, and sWE-Marathon score still low in absolute terms (31.9) despite a large relative jump. At $0.834 in / $2.501 out per million tokens, it sits in the budget price band.

The bottom line for this matchup

The defining split here is open vs. closed. Hunyuan Hy4 Preview gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Gemini 3.5 Flash-Lite 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 Gemini 3.5 Flash-Lite and Hunyuan Hy4 Preview 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 Gemini 3.5 Flash-Lite or Hunyuan Hy4 Preview 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, Gemini 3.5 Flash-Lite leans toward the cheapest gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work while Hunyuan Hy4 Preview leans toward gpqa diamond (92.3), and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Gemini 3.5 Flash-Lite or Hunyuan Hy4 Preview?

Hunyuan Hy4 Preview is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 3.5 Flash-Lite is API-metered at $0.3/$2.5 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?

Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Gemini 3.5 Flash-Lite and Hunyuan Hy4 Preview together?

Yes — a multi-model platform like LumiChats gives you Gemini 3.5 Flash-Lite, Hunyuan Hy4 Preview 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, Gemini 3.5 Flash-Lite or Hunyuan Hy4 Preview?

Hunyuan Hy4 Preview — released August 28, 2026, about 38 days after Gemini 3.5 Flash-Lite.

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.