Hunyuan Hy4 vs Muse Glimmer

Tencent · China  |  Meta · 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 Muse Glimmer for runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit or open weights (apache 2.0), free to self-host and offline-capable - data never leaves your machine. Choose Muse Glimmer if you need self-hosting or data privacy; Hunyuan Hy4 if you want a managed API.

Hunyuan Hy4 (Tencent, China) and Muse Glimmer (Meta, 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. Muse Glimmer is meta's open ~30B agentic model - runs tool-using AI agents locally on a single consumer GPU, offline and free, though it trails frontier cloud models. 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 Hy4Muse Glimmer
ProviderTencent (China) Meta (US)
ReleasedNovember 4, 2026 August 10, 2026
Context window1M tokens (~1,573 pages) 128K (~197 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, image, code
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

Muse Glimmer is comparatively weak here — a distilled ~30B model - ceiling below its closed teacher (Muse Spark) and cloud flagships

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.

Runs real agentic tasks locally on one consumer GPU - fits 24GB of VRAM in 4-bit

Muse Glimmer

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

Open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine

Muse Glimmer

Hunyuan Hy4 is comparatively weak here — 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

Agentic by design: tool use, coding, file and screenshot reading, multi-step failure recovery

Muse Glimmer

Meta's open ~30B agentic model - runs tool-using AI agents locally on a single consumer GPU, offline and free, though it trails frontier cloud models — and its weights are open while Hunyuan Hy4 is API-only.

Lowest cost at scale

Muse Glimmer

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 8× larger than Muse Glimmer's 128K, fitting roughly 1,573 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Muse Glimmer

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

→ Muse Glimmer

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 runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit

→ Muse Glimmer

That is its strongest area.

An enterprise with regional data-residency rules

→ Muse Glimmer 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.

Muse Glimmer: where it fits

Meta's open ~30B agentic model - runs tool-using AI agents locally on a single consumer GPU, offline and free, though it trails frontier cloud models. Released August 10, 2026 by Meta, it is built for runs real agentic tasks locally on one consumer GPU - fits 24GB of VRAM in 4-bit, open weights (Apache 2.0), free to self-host and offline-capable - data never leaves your machine, agentic by design: tool use, coding, file and screenshot reading, multi-step failure recovery, and 128K context, text and image input, trained on 100+ languages.

Its trade-offs: a distilled ~30B model - ceiling below its closed teacher (Muse Spark) and cloud flagships, no independent Artificial Analysis intelligence score published yet, published benchmarks (e.g. SWE-Bench Verified 76.0) are Meta's own, and 4-bit quantization to fit consumer GPUs trades away some accuracy. 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. Muse Glimmer 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 Muse Glimmer 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 Muse Glimmer 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 Muse Glimmer leans toward runs real agentic tasks locally on one consumer gpu - fits 24gb of vram in 4-bit, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Hunyuan Hy4 or Muse Glimmer?

Muse Glimmer 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 128K, about 8× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Hunyuan Hy4 and Muse Glimmer together?

Yes — a multi-model platform like LumiChats gives you Hunyuan Hy4, Muse Glimmer 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 Muse Glimmer?

Hunyuan Hy4 — released November 4, 2026, about 3 months after Muse Glimmer.

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.