Ling 3.1 Flash vs Muse Spark 1.1

InclusionAI (Ant Group) · China | Meta · US · 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 Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported) or subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck. On a tight budget at scale, Ling 3.1 Flash is the value pick.

Ling 3.1 Flash (InclusionAI (Ant Group), China) and Muse Spark 1.1 (Meta, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. Muse Spark 1.1 is meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. 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 4.2× cheaper on input ($0.3/$0.9 per 1M tokens vs $1.25/$4.25 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Muse Spark 1.1 holds 4× more — 1M (~1,573 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.
▸Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.

Side-by-side specs

Spec	Ling 3.1 Flash	Muse Spark 1.1
Provider	InclusionAI (Ant Group) (China)	Meta (US)
Released	September 30, 2026	July 9, 2026
Context window	262K tokens (~393 pages)	1M (~1,573 pages)
Price (in/out)	$0.3/$0.9 per 1M tokens	$1.25/$4.25 per 1M tokens
Open weight?	No — API only	No — API only
Modalities	text, code	text, image, video, code
SWE-Bench Verified	Not published	Not published
MRCR v2 @ 1M	Not published	54.1%

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

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 Muse Spark 1.1 ($1.25/$4.25 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

Muse Spark 1.1 is comparatively weak here — closed weights end the free, self-hostable Llama path — this is the first model Meta has charged for

Scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported)

Muse Spark 1.1

Ling 3.1 Flash is comparatively weak here — announced via WeChat rather than a formal English-language technical report, so some specs are vendor-reported only

Subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck

Muse Spark 1.1

Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding — and it carries the larger 1M context.

Professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported)

Muse Spark 1.1

Muse Spark 1.1 lists professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported) among its strengths; Ling 3.1 Flash does not.

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

Muse Spark 1.1

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 Muse Spark 1.1, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ Muse Spark 1.1

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 scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported)

→ Muse Spark 1.1

That is its strongest area.

An enterprise with regional data-residency rules

→ Muse Spark 1.1 or Ling 3.1 Flash

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

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.

Muse Spark 1.1: where it fits

Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. Released July 9, 2026 by Meta, it is built for scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported), subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck, professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported), and managing its own context: it compacts the 1M window mid-run instead of relying on external windowing.

Its trade-offs: not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark, the 1M window oversells its recall: 54.1 on MRCR v2 at 1M against GPT-5.5's 74.0, closed weights end the free, self-hostable Llama path — this is the first model Meta has charged for, and uS-only public preview behind a waitlist, and every benchmark is vendor-reported with no third-party replication. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.

The bottom line for this matchup

This is less "which is smarter" and more "which ecosystem fits." Ling 3.1 Flash (China) and Muse Spark 1.1 (US) 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 Ling 3.1 Flash and Muse Spark 1.1 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 3.1 Flash or Muse Spark 1.1 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 Muse Spark 1.1 leans toward scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported), and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Ling 3.1 Flash or Muse Spark 1.1?

Ling 3.1 Flash is cheaper — $0.3/$0.9 per 1M tokens vs $1.25/$4.25 per 1M tokens, roughly 4.2× apart on input.

Which has the bigger context window?

Muse Spark 1.1 — 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 Ling 3.1 Flash and Muse Spark 1.1 together?

Yes — a multi-model platform like LumiChats gives you Ling 3.1 Flash, Muse Spark 1.1 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 Muse Spark 1.1?

Ling 3.1 Flash — released September 30, 2026, about 3 months after Muse Spark 1.1.

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Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.