GLM-5.3-Flash vs Muse Spark 1.1
GLM-5.3-Flash shows notably better performance in the majority of benchmarks. GLM-5.3-Flash is 8.4x cheaper per token.
Zhipu AI · Meta · Updated for 2026
Which is better?
GLM-5.3-Flash outperforms in 4 benchmarks (CharXiv-R, DeepSWE 1.1, Terminal-Bench 2.1, Toolathlon), while Muse Spark 1.1 is better at 2 benchmarks (BabyVision, Humanity's Last Exam). GLM-5.3-Flash shows notably better performance in the majority of benchmarks.
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.
Muse Spark 1.1 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 benchmark, pricing, and model metadata for 2026.
Choose GLM-5.3-Flash
- you want the strongest raw capability — it leads on 4 of 6 shared benchmarks
- cost matters — it's about 8.4x cheaper per token
- you want the most recent training data — it shipped Aug 2026
- you need open weights you can self-host or fine-tune
Choose Muse Spark 1.1
- you process long inputs — it offers a 1,048,576 token context window
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3-Flash outperforms in 4 benchmarks (CharXiv-R, DeepSWE 1.1, Terminal-Bench 2.1, Toolathlon), while Muse Spark 1.1 is better at 2 benchmarks (BabyVision, Humanity's Last Exam).
GLM-5.3-Flash shows notably better performance in the majority of benchmarks.
Arena Performance
Playground indexes and blind 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 1.1 ($1.25/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 8.5x cheaper than Muse Spark 1.1 ($4.25/1M tokens).
In conclusion, Muse Spark 1.1 is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Spark 1.1 accepts 1,048,576 input tokens compared to GLM-5.3-Flash's 1,000,000 tokens. Both models can generate responses up to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Both GLM-5.3-Flash and Muse Spark 1.1 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-5.3-Flash
Muse Spark 1.1
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while Muse Spark 1.1 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while Muse Spark 1.1 was released on 2026-07-09.
GLM-5.3-Flash is 2 months newer than Muse Spark 1.1.
Aug 26, 2026
0 days ago
1mo newerJul 9, 2026
1 months ago
Knowledge 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 ZAI. Muse Spark 1.1 is available from Meta Model API.
GLM-5.3-Flash
Muse Spark 1.1
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and Muse Spark 1.1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs Muse Spark 1.1.