Ling 3.1 Flash vs Qwen3 235B A22B (2507)
InclusionAI (Ant Group) · China | Alibaba · 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 Qwen3 235B A22B (2507) for deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux) or exceptional multilingual and alignment results (79.2 arena-hard v2, 85.2 writingbench). Choose Qwen3 235B A22B (2507) 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 Qwen3 235B A22B (2507) (Alibaba) 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. Qwen3 235B A22B (2507) is an older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Cost model: Qwen3 235B A22B (2507) 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: both advertise 262K tokens (~393 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: Ling 3.1 Flash is the newer model by about 15 months (released September 30, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Ling 3.1 Flash | Qwen3 235B A22B (2507) |
|---|---|---|
| Provider | InclusionAI (Ant Group) (China) | Alibaba (China) |
| Released | September 30, 2026 | July 21, 2025 |
| Context window | 262K tokens (~393 pages) | 256K (~393 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
Qwen3 235B A22B (2507) is comparatively weak here — text-only with no vision, and the absence of a thinking mode caps its hardest reasoning
Artificial Analysis Intelligence Index score of 41 — above average for its price tier
Ling 3.1 Flash
Qwen3 235B A22B (2507) is comparatively weak here — nearly a year old and superseded — Artificial Analysis now steers users to Qwen3.5-397B instead
First-party pricing of $0.30/$0.90 per million tokens, with an 80% cache-read discount ($0.06/MTok)
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.
Deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux)
Qwen3 235B A22B (2507)
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding — and its weights are open while Ling 3.1 Flash is API-only.
Exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench)
Qwen3 235B A22B (2507)
Qwen3 235B A22B (2507) lists exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench) among its strengths; Ling 3.1 Flash does not.
Outstanding structured logic — 95.0 on ZebraLogic
Qwen3 235B A22B (2507)
Qwen3 235B A22B (2507) lists outstanding structured logic — 95.0 on ZebraLogic among its strengths; Ling 3.1 Flash does not.
Lowest cost at scale
Qwen3 235B A22B (2507)
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.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen3 235B A22B (2507)
At Open weight (self-host / free) it undercuts Ling 3.1 Flash, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ Qwen3 235B A22B (2507)
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 deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux)
→ Qwen3 235B A22B (2507)
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.
Qwen3 235B A22B (2507): where it fits
An older 235B text-only open mixture-of-experts with broad knowledge and strong writing — but no vision, no thinking mode, and weak coding. Released July 21, 2025 by Alibaba, it is built for deep world knowledge from 235B total parameters (83.0 MMLU-Pro, 93.1 MMLU-Redux), exceptional multilingual and alignment results (79.2 Arena-Hard v2, 85.2 WritingBench), outstanding structured logic — 95.0 on ZebraLogic, and no thinking mode, which makes latency and token spend entirely predictable.
Its trade-offs: nearly a year old and superseded — Artificial Analysis now steers users to Qwen3.5-397B instead, text-only with no vision, and the absence of a thinking mode caps its hardest reasoning, coding is weak by 2026 standards, and it publishes no SWE-Bench score to compare on, and its 235B weights need roughly 438GB in BF16, far beyond consumer hardware. 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. Qwen3 235B A22B (2507) 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 Qwen3 235B A22B (2507) 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 Qwen3 235B A22B (2507) 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 Qwen3 235B A22B (2507) leans toward deep world knowledge from 235b total parameters (83.0 mmlu-pro, 93.1 mmlu-redux), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Ling 3.1 Flash or Qwen3 235B A22B (2507)?
Qwen3 235B A22B (2507) 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?
Both advertise 262K tokens (~393 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Ling 3.1 Flash and Qwen3 235B A22B (2507) together?
Yes — a multi-model platform like LumiChats gives you Ling 3.1 Flash, Qwen3 235B A22B (2507) 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 Qwen3 235B A22B (2507)?
Ling 3.1 Flash — released September 30, 2026, about 15 months after Qwen3 235B A22B (2507).
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.