Ling 3.0 Flash vs Muse Spark 1.3
Muse Spark 1.3 leads the LLM Stats Score 55.1 to 36.5. Ling 3.0 Flash is 1.4x cheaper per token.
InclusionAI · Meta · Updated for 2026
Which is better?
Muse Spark 1.3 leads the overall LLM Stats Score 55.1 to 36.5, ranking #4 overall.
In the 2 individual benchmarks reported for both models, Muse Spark 1.3 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Ling 3.0 Flash is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Spark 1.3 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Ling 3.0 Flash
- cost matters — it's about 1.4x cheaper per token
Choose Muse Spark 1.3
- overall performance matters — it scores 55.1 and ranks #4 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
19 reported for Ling 3.0 Flash · 11 for Muse Spark 1.3
Ling 3.0 Flash outperforms in 0 benchmarks, while Muse Spark 1.3 is better at 2 benchmarks (GDPval-AA, Terminal-Bench 2.1).
Muse Spark 1.3 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Ling 3.0 Flash ($0.06/1M tokens) is 1.7x cheaper than Muse Spark 1.3 ($0.10/1M tokens).
For output processing, Ling 3.0 Flash ($0.18/1M tokens) is 1.1x cheaper than Muse Spark 1.3 ($0.20/1M tokens).
In conclusion, Muse Spark 1.3 is more expensive than Ling 3.0 Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Spark 1.3 accepts 1,048,576 input tokens compared to Ling 3.0 Flash's 131,072 tokens. Muse Spark 1.3 can generate longer responses up to 943,718 tokens, while Ling 3.0 Flash is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Muse Spark 1.3 supports multimodal inputs, whereas Ling 3.0 Flash does not.
Muse Spark 1.3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Ling 3.0 Flash
Muse Spark 1.3
Release Timeline
When each model was launched
Ling 3.0 Flash was released on 2026-08-04, while Muse Spark 1.3 was released on 2026-09-02.
Muse Spark 1.3 is 1 month newer than Ling 3.0 Flash.
Aug 4, 2026
1 months ago
Sep 2, 2026
6 days ago
4w newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Ling 3.0 Flash is available from DeepInfra. Muse Spark 1.3 is available from Meta Model API.
Ling 3.0 Flash
Muse Spark 1.3
Outputs Comparison
Judge for yourself.
Run your own prompts against Ling 3.0 Flash and Muse Spark 1.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ling 3.0 Flash vs Muse Spark 1.3.