GLM-5.3-Flash vs Muse Spark Open
GLM-5.3-Flash and Muse Spark Open are closely matched at 48.6 and 44.9 on the LLM Stats Score. GLM-5.3-Flash is 8.4x cheaper per token.
Zhipu AI · Meta · Updated for 2026
Which is better?
GLM-5.3-Flash and Muse Spark Open are closely matched on the overall LLM Stats Score at 48.6 and 44.9.
In the 5 individual benchmarks reported for both models, GLM-5.3-Flash wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5.3-Flash is roughly 8.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GLM-5.3-Flash
- you value its reported benchmark strengths — it wins 4 of 5 exact shared results
- cost matters — it's about 8.4x cheaper per token
Choose Muse Spark Open
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for GLM-5.3-Flash · 17 for Muse Spark Open
GLM-5.3-Flash outperforms in 4 benchmarks (Artificial Analysis, DeepSWE 1.1, GDPval-AA, Terminal-Bench 2.1), while Muse Spark Open is better at 1 benchmark (BabyVision).
GLM-5.3-Flash 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, GLM-5.3-Flash ($0.15/1M tokens) is 8.3x cheaper than Muse Spark Open ($1.25/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 8.5x cheaper than Muse Spark Open ($4.25/1M tokens).
In conclusion, Muse Spark Open is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Muse Spark Open has 496.0B more parameters than GLM-5.3-Flash, making it 155.0% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. Both models can generate responses up to 1,048,576 tokens.
Input capabilities
Documented input modalities across available providers
Both GLM-5.3-Flash and Muse Spark Open support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-5.3-Flash
Muse Spark Open
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while Muse Spark Open uses Muse Model License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Muse Model License
Open weights
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Muse Spark Open was released on 2026-10-15.
Muse Spark Open is 2 months newer than GLM-5.3-Flash.
Aug 26, 2026
1 months ago
Oct 15, 2026
4 days ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5.3-Flash is available from DeepInfra, FriendliAI, Novita, ZAI. Muse Spark Open is available from Together.
GLM-5.3-Flash
Muse Spark Open
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Muse Spark Open side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Muse Spark Open.