Ling 3.1 Flash vs Qwen 3.7 Max
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 Qwen 3.7 Max for long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7) or 1m-token long-document and full-codebase analysis. On a tight budget at scale, Ling 3.1 Flash is the value pick.
Ling 3.1 Flash (InclusionAI (Ant Group)) and Qwen 3.7 Max (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. Qwen 3.7 Max is alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: Ling 3.1 Flash is about 8.3× cheaper on input ($0.3/$0.9 per 1M tokens vs $2.5/$7.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: Qwen 3.7 Max 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 4 months (released September 30, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Ling 3.1 Flash | Qwen 3.7 Max |
|---|---|---|
| Provider | InclusionAI (Ant Group) (China) | Alibaba (China) |
| Released | September 30, 2026 | May 20, 2026 |
| Context window | 262K tokens (~393 pages) | 1M (~1,500 pages) |
| Price (in/out) | $0.3/$0.9 per 1M tokens | $2.5/$7.5 per 1M tokens |
| Open weight? | No — API only | No — API only |
| 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
Qwen 3.7 Max is comparatively weak here — trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning
Artificial Analysis Intelligence Index score of 41 — above average for its price tier
Ling 3.1 Flash
At $0.3/$0.9 per 1M tokens it undercuts Qwen 3.7 Max ($2.5/$7.5 per 1M tokens), and that gap compounds at volume.
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 runs cheaper at $0.3/$0.9 per 1M tokens.
Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7)
Qwen 3.7 Max
Its 1M window holds about 3.8× more than Ling 3.1 Flash's 262K tokens in a single prompt.
1M-token long-document and full-codebase analysis
Qwen 3.7 Max
Ling 3.1 Flash is comparatively weak here — context window currently served at 262K tokens even though InclusionAI's stated target is 1M — the larger window isn't live yet
MCP tool orchestration and multi-hour autonomous runs
Qwen 3.7 Max
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships — and it carries the larger 1M context.
Lowest cost at scale
Ling 3.1 Flash
At $0.3/$0.9 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Qwen 3.7 Max
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
→ Ling 3.1 Flash
At $0.3/$0.9 per 1M tokens it undercuts Qwen 3.7 Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Qwen 3.7 Max
Larger 1M window fits more in one prompt.
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 long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7)
→ Qwen 3.7 Max
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.
Qwen 3.7 Max: where it fits
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. Released May 20, 2026 by Alibaba, it is built for long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7), 1M-token long-document and full-codebase analysis, mCP tool orchestration and multi-hour autonomous runs, and frontier intelligence at roughly half the price of US flagships.
Its trade-offs: text-only — no vision input (the Plus variant adds images), closed-weight, API-only — no self-hosting, trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning, and chinese-jurisdiction data-residency considerations. At $2.5 in / $7.5 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Ling 3.1 Flash and Qwen 3.7 Max overlap enough that the right pick depends on your specific job. Ling 3.1 Flash costs less per token; Qwen 3.7 Max holds the larger context; and each leads in its own area — Ling 3.1 Flash for hybrid-reasoning moe — 560b total parameters, ~25b active per token, aimed at agents, tool use, and long-document work, Qwen 3.7 Max for long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Ling 3.1 Flash and Qwen 3.7 Max 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 Qwen 3.7 Max 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 Qwen 3.7 Max leans toward long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Ling 3.1 Flash or Qwen 3.7 Max?
Ling 3.1 Flash is cheaper — $0.3/$0.9 per 1M tokens vs $2.5/$7.5 per 1M tokens, roughly 8.3× apart on input.
Which has the bigger context window?
Qwen 3.7 Max — 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 Qwen 3.7 Max together?
Yes — a multi-model platform like LumiChats gives you Ling 3.1 Flash, Qwen 3.7 Max 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 Qwen 3.7 Max?
Ling 3.1 Flash — released September 30, 2026, about 4 months after Qwen 3.7 Max.
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.