Hunyuan Hy3 vs Palmyra X6

Tencent · China  |  Writer · US · Updated June 2026

Quick verdict

Pick Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost or runs a 295b model at the cost of a 21b — only 21b parameters active per token. Pick Palmyra X6 for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents or writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (writer's own figures). Choose Hunyuan Hy3 if you need self-hosting or data privacy; Palmyra X6 if you want a managed API.

Hunyuan Hy3 (Tencent, China) and Palmyra X6 (Writer, 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 Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Palmyra X6 is writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. They diverge most on 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 Hy3Palmyra X6
ProviderTencent (China) Writer (US)
ReleasedJuly 6, 2026 August 13, 2026
Context window256K (~384 pages) 128K (~192 pages)
Price (in/out)Open weight (self-host / free) Not published
Open weight?Yes — self-hostable No — API only
Modalitiestext, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost

Hunyuan Hy3

A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost — and it carries the larger 256K context.

Runs a 295B model at the cost of a 21B — only 21B parameters active per token

Hunyuan Hy3

Its 256K window holds about 2× more than Palmyra X6's 128K in a single prompt.

Clean, unrestricted Apache-2.0 license with no geographic carve-out

Hunyuan Hy3

A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost — and its weights are open while Palmyra X6 is API-only.

Enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents

Palmyra X6

Writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half — and it is the newer of the two.

Writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures)

Palmyra X6

Palmyra X6 lists writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures) among its strengths; Hunyuan Hy3 does not.

A post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use

Palmyra X6

Palmyra X6 lists a post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use among its strengths; Hunyuan Hy3 does not.

Largest single-prompt input

Hunyuan Hy3

Its 256K window is about 2× larger than Palmyra X6's 128K, fitting roughly 384 pages in one prompt.

Which should you pick?

Someone analysing very long documents or codebases

Hunyuan Hy3

Larger 256K window fits more in one prompt.

A team with data-privacy or self-hosting needs

Hunyuan Hy3

Open weights let you run it on your own hardware; Palmyra X6 is API-only.

Anyone whose priority is frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost

Hunyuan Hy3

It is specifically built for that.

Anyone whose priority is enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents

Palmyra X6

That is its strongest area.

An enterprise with regional data-residency rules

Palmyra X6 or Hunyuan Hy3

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

Hunyuan Hy3: where it fits

A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Released July 6, 2026 by Tencent, it is built for frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost, runs a 295B model at the cost of a 21B — only 21B parameters active per token, clean, unrestricted Apache-2.0 license with no geographic carve-out, and broad day-one ecosystem support plus an FP8 checkpoint.

Its trade-offs are real: benchmarks are largely self-reported, and the ultra-low hosted pricing is a limited promotion, and the hosted API is China-jurisdiction, and self-hosting a 295B MoE still needs serious hardware. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

Palmyra X6: where it fits

Writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. Released August 13, 2026 by Writer, it is built for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures), and a post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use.

Its trade-offs: no public per-token API price - sold through Writer's enterprise platform, not a self-serve API, not independently benchmarked on general leaderboards like SWE-bench or Artificial Analysis, and built for a narrower enterprise-agent use case rather than general-purpose chat.

The bottom line for this matchup

The defining split here is open vs. closed. Hunyuan Hy3 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Palmyra X6 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 Hy3 and Palmyra X6 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 Hy3 or Palmyra X6 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 Hy3 leans toward frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost while Palmyra X6 leans toward enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Hunyuan Hy3 or Palmyra X6?

Hunyuan Hy3 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Palmyra X6 is API-metered at Not published. 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 Hy3 — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Hunyuan Hy3 and Palmyra X6 together?

Yes — a multi-model platform like LumiChats gives you Hunyuan Hy3, Palmyra X6 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 Hy3 or Palmyra X6?

Palmyra X6 — released August 13, 2026, about 38 days after Hunyuan Hy3.

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.