Ling 3.1 Flash vs LongCat-2.0
InclusionAI (Ant Group) · China | Meituan · China · Updated June 2026
Quick verdict
Pick Ling 3.1 Flash for hybrid-reasoning moe — 560b total parameters, ~25b active per token, aimed at agents, tool use, and long-document work or artificial analysis intelligence index score of 41 — above average for its price tier. Pick LongCat-2.0 for near-frontier agentic coding — topped openrouter anonymously as 'owl alpha' for two months or massive native 1m context at near-linear cost via sparse attention. Choose LongCat-2.0 if you need self-hosting or data privacy; Ling 3.1 Flash if you want a managed API.
Ling 3.1 Flash (InclusionAI (Ant Group)) and LongCat-2.0 (Meituan) are two of the models people most often weigh against each other in 2026. Ling 3.1 Flash is inclusionAI's (Ant Group) September 30, 2026 hybrid-reasoning MoE model — 560B parameters aimed at agents and long documents, launched as a free trial with weights still unreleased. LongCat-2.0 is a trillion-parameter, MIT-licensed open MoE delivering near-frontier agentic coding at 1M context — trained entirely on Chinese chips. 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
- ▸Cost model: LongCat-2.0 ships open weights you can self-host (hardware cost only, no per-token fee), while Ling 3.1 Flash is API-metered at $0.3/$0.9 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
- ▸Context window: LongCat-2.0 holds 3.8× more — 1M (~1,500 pages) vs 262K tokens (~393 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Ling 3.1 Flash is the newer model by about 3 months (released September 30, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Ling 3.1 Flash | LongCat-2.0 |
|---|---|---|
| Provider | InclusionAI (Ant Group) (China) | Meituan (China) |
| Released | September 30, 2026 | July 5, 2026 |
| Context window | 262K tokens (~393 pages) | 1M (~1,500 pages) |
| Price (in/out) | $0.3/$0.9 per 1M tokens | Open weight (self-host / free) |
| Open weight? | No — API only | 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
Hybrid-reasoning MoE — 560B total parameters, ~25B active per token, aimed at agents, tool use, and long-document work
Ling 3.1 Flash
InclusionAI's (Ant Group) September 30, 2026 hybrid-reasoning MoE model — 560B parameters aimed at agents and long documents, launched as a free trial with weights still unreleased — and it is the newer of the two.
Artificial Analysis Intelligence Index score of 41 — above average for its price tier
Ling 3.1 Flash
LongCat-2.0 is comparatively weak here — headline scores are vendor-reported on SWE-Bench Pro, not the Verified set
First-party pricing of $0.30/$0.90 per million tokens, with an 80% cache-read discount ($0.06/MTok)
Ling 3.1 Flash
Ling 3.1 Flash lists first-party pricing of $0.30/$0.90 per million tokens, with an 80% cache-read discount ($0.06/MTok) among its strengths; LongCat-2.0 does not.
Near-frontier agentic coding — topped OpenRouter anonymously as 'Owl Alpha' for two months
LongCat-2.0
Open weights make this possible at all — Ling 3.1 Flash is API-only, so it cannot leave the vendor's servers.
Massive native 1M context at near-linear cost via sparse attention
LongCat-2.0
Its 1M window holds about 3.8× more than Ling 3.1 Flash's 262K tokens in a single prompt.
Fully MIT-licensed 1.6T-parameter mixture-of-experts (about 48B active)
LongCat-2.0
A trillion-parameter, MIT-licensed open MoE delivering near-frontier agentic coding at 1M context — trained entirely on Chinese chips — and it carries the larger 1M context.
Lowest cost at scale
LongCat-2.0
Its weights are open, so at volume you pay for your own hardware instead of Ling 3.1 Flash's $0.3/$0.9 per 1M tokens.
Largest single-prompt input
LongCat-2.0
Its 1M window is about 3.8× larger than Ling 3.1 Flash's 262K tokens, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ LongCat-2.0
At Open weight (self-host / free) it undercuts Ling 3.1 Flash, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ LongCat-2.0
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ LongCat-2.0
Open weights let you run it on your own hardware; Ling 3.1 Flash is API-only.
Anyone whose priority is hybrid-reasoning moe — 560b total parameters, ~25b active per token, aimed at agents, tool use, and long-document work
→ Ling 3.1 Flash
It is specifically built for that.
Anyone whose priority is near-frontier agentic coding — topped openrouter anonymously as 'owl alpha' for two months
→ LongCat-2.0
That is its strongest area.
Ling 3.1 Flash: where it fits
InclusionAI's (Ant Group) September 30, 2026 hybrid-reasoning MoE model — 560B parameters aimed at agents and long documents, launched as a free trial with weights still unreleased. Released September 30, 2026 by InclusionAI (Ant Group), it is built for hybrid-reasoning MoE — 560B total parameters, ~25B active per token, aimed at agents, tool use, and long-document work, artificial Analysis Intelligence Index score of 41 — above average for its price tier, first-party pricing of $0.30/$0.90 per million tokens, with an 80% cache-read discount ($0.06/MTok), and predecessor Ling 3.0 Flash shipped MIT-licensed open weights, suggesting a similar path once 3.1 clears review.
Its trade-offs are real: shipped as an announcement plus a two-week free trial rather than a full release — no weights, no model card, and limited independent verification at launch, context window currently served at 262K tokens even though InclusionAI's stated target is 1M — the larger window isn't live yet, not yet open-weight despite InclusionAI saying it plans to open-source the model 'soon', and announced via WeChat rather than a formal English-language technical report, so some specs are vendor-reported only. At $0.3 in / $0.9 out per million tokens, it sits in the budget price band.
LongCat-2.0: where it fits
A trillion-parameter, MIT-licensed open MoE delivering near-frontier agentic coding at 1M context — trained entirely on Chinese chips. Released July 5, 2026 by Meituan, it is built for near-frontier agentic coding — topped OpenRouter anonymously as 'Owl Alpha' for two months, massive native 1M context at near-linear cost via sparse attention, fully MIT-licensed 1.6T-parameter mixture-of-experts (about 48B active), and trained end to end on domestic Chinese chips, independent of Nvidia hardware.
Its trade-offs: a 1.6T model is extremely expensive to self-host, so most use leans on the China-hosted API, and headline scores are vendor-reported on SWE-Bench Pro, not the Verified set. 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. LongCat-2.0 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Ling 3.1 Flash 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 Ling 3.1 Flash and LongCat-2.0 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 pricingFrequently asked questions
Is Ling 3.1 Flash or LongCat-2.0 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 3.1 Flash leans toward hybrid-reasoning moe — 560b total parameters, ~25b active per token, aimed at agents, tool use, and long-document work while LongCat-2.0 leans toward near-frontier agentic coding — topped openrouter anonymously as 'owl alpha' for two months, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Ling 3.1 Flash or LongCat-2.0?
LongCat-2.0 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Ling 3.1 Flash is API-metered at $0.3/$0.9 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?
LongCat-2.0 — 1M vs 262K tokens, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Ling 3.1 Flash and LongCat-2.0 together?
Yes — a multi-model platform like LumiChats gives you Ling 3.1 Flash, LongCat-2.0 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 3.1 Flash or LongCat-2.0?
Ling 3.1 Flash — released September 30, 2026, about 3 months after LongCat-2.0.
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.