Ling-2.6-1T vs MiniMax M3

Ant Group · China  |  MiniMax · China · Updated June 2026

Quick verdict

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. Pick MiniMax M3 for open-weight 428b moe (~23b active per token) with a 1m-token context or native multimodal input — text, image and video. On a tight budget at scale, MiniMax M3 is the value pick.

Ling-2.6-1T (Ant Group) and MiniMax M3 (MiniMax) are two of the models people most often weigh against each other in 2026. 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. MiniMax M3 is miniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. They diverge most on price and context window — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecLing-2.6-1TMiniMax M3
ProviderAnt Group (China) MiniMax (China)
ReleasedApril 2026 May 31, 2026
Context window256K (~393 pages) 1M (~1,573 pages)
Price (in/out)$0.3/$2.5 per 1M tokens $0.23/$0.96 per 1M tokens
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, code text, image, video, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

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; MiniMax M3 does not.

Fully open weights under the permissive MIT license, unusual for a model this large

Ling-2.6-1T

Ling-2.6-1T lists fully open weights under the permissive MIT license, unusual for a model this large among its strengths; MiniMax M3 does not.

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; MiniMax M3 does not.

Open-weight 428B MoE (~23B active per token) with a 1M-token context

MiniMax M3

Its 1M window holds about 4× more than Ling-2.6-1T's 256K in a single prompt.

Native multimodal input — text, image and video

MiniMax M3

MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing — and it runs cheaper at $0.23/$0.96 per 1M tokens.

Reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5

MiniMax M3

Ling-2.6-1T is comparatively weak here — exact release date is disputed across sources (reports range from mid to late April 2026)

Lowest cost at scale

MiniMax M3

At $0.23/$0.96 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

MiniMax M3

Its 1M window is about 4× larger than Ling-2.6-1T's 256K, fitting roughly 1,573 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ MiniMax M3

At $0.23/$0.96 per 1M tokens it undercuts Ling-2.6-1T, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ MiniMax M3

Larger 1M window fits more in one prompt.

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

It is specifically built for that.

Anyone whose priority is open-weight 428b moe (~23b active per token) with a 1m-token context

→ MiniMax M3

That is its strongest area.

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 are real: 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.

MiniMax M3: where it fits

MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. Released May 31, 2026 by MiniMax, it is built for open-weight 428B MoE (~23B active per token) with a 1M-token context, native multimodal input — text, image and video, reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5, and low entry pricing at $0.30/$1.20 per million up to 512K tokens.

Its trade-offs: price doubles to $0.60/$2.40 above 512K tokens — not flat across 1M, miniMax's own reported 80.5 SWE-Bench Verified figure is vendor-stated, not independently verified, sWE-Bench Pro is a different, harder benchmark than SWE-Bench Verified, and newer than M2.7 but with less independent testing so far. At $0.23 in / $0.96 out per million tokens, it sits in the budget price band.

The bottom line for this matchup

Ling-2.6-1T and MiniMax M3 overlap enough that the right pick depends on your specific job. MiniMax M3 costs less per token; MiniMax M3 holds the larger context; and each leads in its own area — 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, MiniMax M3 for open-weight 428b moe (~23b active per token) with a 1m-token context. Rather than crowning one, run the same hard task through both once and let the results decide.

Want both Ling-2.6-1T and MiniMax M3 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 Ling-2.6-1T or MiniMax M3 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, 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 while MiniMax M3 leans toward open-weight 428b moe (~23b active per token) with a 1m-token context, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Ling-2.6-1T or MiniMax M3?

MiniMax M3 is cheaper — $0.3/$2.5 per 1M tokens vs $0.23/$0.96 per 1M tokens, roughly 1.3× apart on input.

Which has the bigger context window?

MiniMax M3 — 1M vs 256K, about 4× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Ling-2.6-1T and MiniMax M3 together?

Yes — a multi-model platform like LumiChats gives you Ling-2.6-1T, MiniMax M3 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, Ling-2.6-1T or MiniMax M3?

MiniMax M3 — released May 31, 2026, about 2 months after Ling-2.6-1T.

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.