Ling 3.1 Flash vs Muse Spark 1.3
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 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 or deepswe v1.1 long-horizon software engineering (75.4). 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 1.3 (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 1.3 is meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. 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 1.3 holds 3.8× more — 1M tokens (~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 28 days (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 1.3 |
|---|---|---|
| Provider | InclusionAI (Ant Group) (China) | Meta (US) |
| Released | September 30, 2026 | September 2, 2026 |
| Context window | 262K tokens (~393 pages) | 1M tokens (~1,500 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 |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | 98.1% |
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
Muse Spark 1.3 is comparatively weak here — strongest 'max' reasoning configuration still gated pending additional safety testing
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 1.3 ($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
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.
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2
Muse Spark 1.3
Its 1M tokens window holds about 3.8× more than Ling 3.1 Flash's 262K tokens in a single prompt.
DeepSWE v1.1 long-horizon software engineering (75.4)
Muse Spark 1.3
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it carries the larger 1M tokens context.
Near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1)
Muse Spark 1.3
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
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 1.3
Its 1M tokens 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 Muse Spark 1.3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Spark 1.3
Larger 1M tokens 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 agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2
→ Muse Spark 1.3
That is its strongest area.
An enterprise with regional data-residency rules
→ Muse Spark 1.3 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 1.3: where it fits
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Released September 2, 2026 by Meta, it is built for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2, deepSWE v1.1 long-horizon software engineering (75.4), near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1), and ranks third overall on the Artificial Analysis Intelligence Index (score 61, xhigh variant; the limited-preview max variant scores 62) - behind only Claude Fable 5.1 and Claude Opus 5.
Its trade-offs: strongest 'max' reasoning configuration still gated pending additional safety testing, not yet open-weight, despite Meta roadmapping a future Muse Spark weights release, and no official SWE-bench Verified score published. 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 1.3 (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 1.3 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 Muse Spark 1.3 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 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Ling 3.1 Flash or Muse Spark 1.3?
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 1.3 — 1M tokens 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 Muse Spark 1.3 together?
Yes — a multi-model platform like LumiChats gives you Ling 3.1 Flash, Muse Spark 1.3 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 1.3?
Ling 3.1 Flash — released September 30, 2026, about 28 days after Muse Spark 1.3.
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.