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 Ling-2.6-1T for a trillion-parameter moe (1t total / ~50-63b active) from ant group - the fintech giant behind alipay - entering ai at frontier scale or fully open weights under the permissive mit license, unusual for a model this large. On a tight budget at scale, Hunyuan Hy3 is the value pick.
Hunyuan Hy3 (Tencent) and Ling-2.6-1T (Ant Group) are two of the models people most often weigh against each other in 2026. Hunyuan Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Ling-2.6-1T is ant Group's trillion-parameter, MIT-licensed open model - a fintech giant's frontier-scale entry into the Chinese open-weight AI race. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: 256K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: Hunyuan Hy3 is the newer model by about 3 months (released July 6, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Hunyuan Hy3
Ling-2.6-1T
Provider
Tencent (China)
Ant Group (China)
Released
July 6, 2026
April 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.3/$2.5 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not 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 is the newer of the two.
Runs a 295B model at the cost of a 21B — only 21B parameters active per token: Hunyuan Hy3 — Hunyuan Hy3 lists runs a 295B model at the cost of a 21B — only 21B parameters active per token among its strengths; Ling-2.6-1T does not.
Clean, unrestricted Apache-2.0 license with no geographic carve-out: Hunyuan Hy3 — Hunyuan Hy3 lists clean, unrestricted Apache-2.0 license with no geographic carve-out among its strengths; Ling-2.6-1T does not.
A trillion-parameter MoE (1T total / ~50-63B active) from Ant Group - the fintech giant behind Alipay - entering AI at frontier scale: Ling-2.6-1T — Ling-2.6-1T lists a trillion-parameter MoE (1T total / ~50-63B active) from Ant Group - the fintech giant behind Alipay - entering AI at frontier scale among its strengths; Hunyuan Hy3 does not.
Fully open weights under the permissive MIT license, unusual for a model this large: Ling-2.6-1T — Hunyuan Hy3 is comparatively weak here — benchmarks are largely self-reported, and the ultra-low hosted pricing is a limited promotion
A companion 'Ring' reasoning variant claims gold-medal-level IMO/CMO math scores using a hybrid linear-attention architecture: Ling-2.6-1T — Ling-2.6-1T lists a companion 'Ring' reasoning variant claims gold-medal-level IMO/CMO math scores using a hybrid linear-attention architecture among its strengths; Hunyuan Hy3 does not.
Lowest cost at scale: Hunyuan Hy3 — Its weights are open, so at volume you pay for your own hardware instead of Ling-2.6-1T's $0.3/$2.5 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Hunyuan Hy3 — At Open weight (self-host / free) it undercuts Ling-2.6-1T, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Ling-2.6-1T — Larger 256K window fits more in one prompt.
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 a trillion-parameter moe (1t total / ~50-63b active) from ant group - the fintech giant behind alipay - entering ai at frontier scale: Ling-2.6-1T — That is its strongest area.
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.
Ling-2.6-1T: where it fits
Ant Group's trillion-parameter, MIT-licensed open model - a fintech giant's frontier-scale entry into the Chinese open-weight AI race. Released April 2026 by Ant Group, it is built for a trillion-parameter MoE (1T total / ~50-63B active) from Ant Group - the fintech giant behind Alipay - entering AI at frontier scale, fully open weights under the permissive MIT license, unusual for a model this large, a companion 'Ring' reasoning variant claims gold-medal-level IMO/CMO math scores using a hybrid linear-attention architecture, and a major Chinese lab with real financial backing, distinct from DeepSeek, Alibaba, or Moonshot.
Its trade-offs: pricing shown is third-party hosting, not an official Ant Group rate card, newer entrant to LLMs specifically - less track record than dedicated AI labs, and exact release date is disputed across sources (reports range from mid to late April 2026). At $0.3 in / $2.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Hunyuan Hy3 and Ling-2.6-1T overlap enough that the right pick depends on your specific job. Hunyuan Hy3 costs less per token; Ling-2.6-1T holds the larger context; and each leads in its own area — Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost, Ling-2.6-1T for a trillion-parameter moe (1t total / ~50-63b active) from ant group - the fintech giant behind alipay - entering ai at frontier scale. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Hunyuan Hy3 or Ling-2.6-1T 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 Ling-2.6-1T leans toward a trillion-parameter moe (1t total / ~50-63b active) from ant group - the fintech giant behind alipay - entering ai at frontier scale, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy3 or Ling-2.6-1T?
Hunyuan Hy3 is cheaper — Open weight (self-host / free) vs $0.3/$2.5 per 1M tokens.
Which has the bigger context window?
Effectively neither — 256K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Hunyuan Hy3 and Ling-2.6-1T together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy3, Ling-2.6-1T 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 Ling-2.6-1T?
Hunyuan Hy3 — released July 6, 2026, about 3 months after Ling-2.6-1T.
Hunyuan Hy3 vs Ling-2.6-1T
Tencent · China | Ant Group · China · 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 Ling-2.6-1T for a trillion-parameter moe (1t total / ~50-63b active) from ant group - the fintech giant behind alipay - entering ai at frontier scale or fully open weights under the permissive mit license, unusual for a model this large. On a tight budget at scale, Hunyuan Hy3 is the value pick.
Hunyuan Hy3 (Tencent) and Ling-2.6-1T (Ant Group) are two of the models people most often weigh against each other in 2026. Hunyuan Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Ling-2.6-1T is ant Group's trillion-parameter, MIT-licensed open model - a fintech giant's frontier-scale entry into the Chinese open-weight AI race. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: 256K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: Hunyuan Hy3 is the newer model by about 3 months (released July 6, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Hunyuan Hy3
Ling-2.6-1T
Provider
Tencent (China)
Ant Group (China)
Released
July 6, 2026
April 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
Open weight (self-host / free)
$0.3/$2.5 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not 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 is the newer of the two.
Runs a 295B model at the cost of a 21B — only 21B parameters active per token
Hunyuan Hy3
Hunyuan Hy3 lists runs a 295B model at the cost of a 21B — only 21B parameters active per token among its strengths; Ling-2.6-1T does not.
Clean, unrestricted Apache-2.0 license with no geographic carve-out
Hunyuan Hy3
Hunyuan Hy3 lists clean, unrestricted Apache-2.0 license with no geographic carve-out among its strengths; Ling-2.6-1T does not.
A trillion-parameter MoE (1T total / ~50-63B active) from Ant Group - the fintech giant behind Alipay - entering AI at frontier scale
Ling-2.6-1T
Ling-2.6-1T lists a trillion-parameter MoE (1T total / ~50-63B active) from Ant Group - the fintech giant behind Alipay - entering AI at frontier scale among its strengths; Hunyuan Hy3 does not.
Fully open weights under the permissive MIT license, unusual for a model this large
Ling-2.6-1T
Hunyuan Hy3 is comparatively weak here — benchmarks are largely self-reported, and the ultra-low hosted pricing is a limited promotion
A companion 'Ring' reasoning variant claims gold-medal-level IMO/CMO math scores using a hybrid linear-attention architecture
Ling-2.6-1T
Ling-2.6-1T lists a companion 'Ring' reasoning variant claims gold-medal-level IMO/CMO math scores using a hybrid linear-attention architecture among its strengths; Hunyuan Hy3 does not.
Lowest cost at scale
Hunyuan Hy3
Its weights are open, so at volume you pay for your own hardware instead of Ling-2.6-1T's $0.3/$2.5 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Hunyuan Hy3
At Open weight (self-host / free) it undercuts Ling-2.6-1T, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Ling-2.6-1T
Larger 256K window fits more in one prompt.
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 a trillion-parameter moe (1t total / ~50-63b active) from ant group - the fintech giant behind alipay - entering ai at frontier scale
→ Ling-2.6-1T
That is its strongest area.
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.
Ling-2.6-1T: where it fits
Ant Group's trillion-parameter, MIT-licensed open model - a fintech giant's frontier-scale entry into the Chinese open-weight AI race. Released April 2026 by Ant Group, it is built for a trillion-parameter MoE (1T total / ~50-63B active) from Ant Group - the fintech giant behind Alipay - entering AI at frontier scale, fully open weights under the permissive MIT license, unusual for a model this large, a companion 'Ring' reasoning variant claims gold-medal-level IMO/CMO math scores using a hybrid linear-attention architecture, and a major Chinese lab with real financial backing, distinct from DeepSeek, Alibaba, or Moonshot.
Its trade-offs: pricing shown is third-party hosting, not an official Ant Group rate card, newer entrant to LLMs specifically - less track record than dedicated AI labs, and exact release date is disputed across sources (reports range from mid to late April 2026). At $0.3 in / $2.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Hunyuan Hy3 and Ling-2.6-1T overlap enough that the right pick depends on your specific job. Hunyuan Hy3 costs less per token; Ling-2.6-1T holds the larger context; and each leads in its own area — Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost, Ling-2.6-1T for a trillion-parameter moe (1t total / ~50-63b active) from ant group - the fintech giant behind alipay - entering ai at frontier scale. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Hunyuan Hy3 and Ling-2.6-1T 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.
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 Ling-2.6-1T leans toward a trillion-parameter moe (1t total / ~50-63b active) from ant group - the fintech giant behind alipay - entering ai at frontier scale, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Hunyuan Hy3 or Ling-2.6-1T?
Hunyuan Hy3 is cheaper — Open weight (self-host / free) vs $0.3/$2.5 per 1M tokens.
Which has the bigger context window?
Effectively neither — 256K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Hunyuan Hy3 and Ling-2.6-1T together?
Yes — a multi-model platform like LumiChats gives you Hunyuan Hy3, Ling-2.6-1T 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 Ling-2.6-1T?
Hunyuan Hy3 — released July 6, 2026, about 3 months after Ling-2.6-1T.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.