Gemini 3.7 Flash vs Ling 3.1 Flash

Google · US  |  InclusionAI (Ant Group) · China · Updated June 2026

Quick verdict

Pick Gemini 3.7 Flash for strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing or 1m-token context with full multimodal input (text, image, audio, video). 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. On a tight budget at scale, Ling 3.1 Flash is the value pick.

Gemini 3.7 Flash (Google, US) and Ling 3.1 Flash (InclusionAI (Ant Group), China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Gemini 3.7 Flash is google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed. 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. 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

SpecGemini 3.7 FlashLing 3.1 Flash
ProviderGoogle (US) InclusionAI (Ant Group) (China)
ReleasedAugust 13, 2026 September 30, 2026
Context window1M (~1,573 pages) 262K tokens (~393 pages)
Price (in/out)$0.75/$3.75 per 1M tokens $0.3/$0.9 per 1M tokens
Open weight?No — API only No — API only
Modalitiestext, image, audio, video, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Strong intelligence-per-dollar - Artificial Analysis Intelligence Index 56 at introductory $0.75/$3.75 pricing

Gemini 3.7 Flash

Google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed — and it carries the larger 1M context.

1M-token context with full multimodal input (text, image, audio, video)

Gemini 3.7 Flash

Its 1M window holds about 4× more than Ling 3.1 Flash's 262K tokens in a single prompt.

Built for coding and agents, with roughly 3x faster output than GPT-5.6 Terra

Gemini 3.7 Flash

Gemini 3.7 Flash lists built for coding and agents, with roughly 3x faster output than GPT-5.6 Terra among its strengths; Ling 3.1 Flash does not.

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 runs cheaper at $0.3/$0.9 per 1M tokens.

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 Gemini 3.7 Flash ($0.75/$3.75 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

Gemini 3.7 Flash is comparatively weak here — introductory pricing ($0.75/$3.75) reverts to $1.50/$7.50 on Jan 1, 2027

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

Gemini 3.7 Flash

Its 1M window is about 4× larger than Ling 3.1 Flash's 262K tokens, fitting roughly 1,573 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 Gemini 3.7 Flash, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ Gemini 3.7 Flash

Larger 1M window fits more in one prompt.

Anyone whose priority is strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing

→ Gemini 3.7 Flash

It is specifically built for that.

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

That is its strongest area.

An enterprise with regional data-residency rules

→ Gemini 3.7 Flash or Ling 3.1 Flash

Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

Gemini 3.7 Flash: where it fits

Google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed. Released August 13, 2026 by Google, it is built for strong intelligence-per-dollar - Artificial Analysis Intelligence Index 56 at introductory $0.75/$3.75 pricing, 1M-token context with full multimodal input (text, image, audio, video), built for coding and agents, with roughly 3x faster output than GPT-5.6 Terra, and wins broad-coding and web-development benchmarks against GPT-5.6 Terra.

Its trade-offs are real: introductory pricing ($0.75/$3.75) reverts to $1.50/$7.50 on Jan 1, 2027, trails GPT-5.6 Terra on the hardest repo-scale and terminal-agent coding, a fast 'workhorse,' not Google's top-intelligence model (Gemini 3.1 Pro is still the flagship), and some benchmark gains are Google's own figures. At $0.75 in / $3.75 out per million tokens, it sits in the budget price band.

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: 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.

The bottom line for this matchup

This is less "which is smarter" and more "which ecosystem fits." Gemini 3.7 Flash (US) and Ling 3.1 Flash (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Ling 3.1 Flash is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.

Want both Gemini 3.7 Flash and Ling 3.1 Flash 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 Gemini 3.7 Flash or Ling 3.1 Flash 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, Gemini 3.7 Flash leans toward strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing while 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, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Gemini 3.7 Flash or Ling 3.1 Flash?

Ling 3.1 Flash is cheaper — $0.75/$3.75 per 1M tokens vs $0.3/$0.9 per 1M tokens, roughly 2.5× apart on input.

Which has the bigger context window?

Gemini 3.7 Flash — 1M vs 262K tokens, about 4× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Gemini 3.7 Flash and Ling 3.1 Flash together?

Yes — a multi-model platform like LumiChats gives you Gemini 3.7 Flash, Ling 3.1 Flash 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, Gemini 3.7 Flash or Ling 3.1 Flash?

Ling 3.1 Flash — released September 30, 2026, about 48 days after Gemini 3.7 Flash.

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.