GLM 5.1 vs Hunyuan Hy4

Z.ai · China  |  Tencent · China · Updated June 2026

Quick verdict

Pick GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). 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. Choose GLM 5.1 if you need self-hosting or data privacy; Hunyuan Hy4 if you want a managed API.

GLM 5.1 (Z.ai) and Hunyuan Hy4 (Tencent) are two of the models people most often weigh against each other in 2026. GLM 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. 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. 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

SpecGLM 5.1Hunyuan Hy4
ProviderZ.ai (China) Tencent (China)
ReleasedApril 7, 2026 November 4, 2026
Context window200K (~300 pages) 1M tokens (~1,573 pages)
Price (in/out)$1.4/$4.4 per 1M tokens $0.9/$2.7 per 1M tokens
Open weight?Yes — self-hostable No — API only
Modalitiestext, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Long-horizon autonomous agentic engineering (up to 8-hour runs)

GLM 5.1

An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours — and its weights are open while Hunyuan Hy4 is API-only.

State-of-the-art open-weight coding (topped SWE-Bench Pro at launch)

GLM 5.1

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

Sustained tool use across thousands of calls

GLM 5.1

GLM 5.1 lists sustained tool use across thousands of calls among its strengths; Hunyuan Hy4 does not.

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

Hunyuan Hy4

GLM 5.1 is comparatively weak here — text-only, with no image, audio, or video input

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 runs cheaper at $0.9/$2.7 per 1M tokens.

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 carries the larger 1M tokens context.

Lowest cost at scale

Hunyuan Hy4

At $0.9/$2.7 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

Hunyuan Hy4

Its 1M tokens window is about 5.2× larger than GLM 5.1's 200K, fitting roughly 1,573 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Hunyuan Hy4

At $0.9/$2.7 per 1M tokens it undercuts GLM 5.1, 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

→ GLM 5.1

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

Anyone whose priority is long-horizon autonomous agentic engineering (up to 8-hour runs)

→ GLM 5.1

It is specifically built for that.

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

→ Hunyuan Hy4

That is its strongest area.

GLM 5.1: where it fits

An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.

Its trade-offs are real: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. At $1.4 in / $4.4 out per million tokens, it sits in the mid price band.

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: 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.

The bottom line for this matchup

The defining split here is open vs. closed. GLM 5.1 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 GLM 5.1 and Hunyuan Hy4 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 GLM 5.1 or Hunyuan Hy4 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, GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs) while Hunyuan Hy4 leans toward first hunyuan model with vision and computer use, adding image input to the text-only hy4 preview, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GLM 5.1 or Hunyuan Hy4?

GLM 5.1 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 200K, about 5.2× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both GLM 5.1 and Hunyuan Hy4 together?

Yes — a multi-model platform like LumiChats gives you GLM 5.1, Hunyuan Hy4 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, GLM 5.1 or Hunyuan Hy4?

Hunyuan Hy4 — released November 4, 2026, about 7 months after GLM 5.1.

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.