GLM-4.7-Flash vs Muse Spark Open
Muse Spark Open leads the LLM Stats Score 44.9 to 23.2. GLM-4.7-Flash is 13.1x cheaper per token.
Zhipu AI · Meta · Updated for 2026
Which is better?
Muse Spark Open leads the overall LLM Stats Score 44.9 to 23.2, ranking #43 overall.
In the 1 individual benchmarks reported for both models, Muse Spark Open wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-4.7-Flash is roughly 13.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Spark Open 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 GLM-4.7-Flash
- cost matters — it's about 13.1x cheaper per token
Choose Muse Spark Open
- overall performance matters — it scores 44.9 and ranks #43 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 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 Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
6 reported for GLM-4.7-Flash · 17 for Muse Spark Open
GLM-4.7-Flash outperforms in 0 benchmarks, while Muse Spark Open is better at 1 benchmark (GPQA).
Muse Spark Open 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-4.7-Flash ($0.07/1M tokens) is 17.9x cheaper than Muse Spark Open ($1.25/1M tokens).
For output processing, GLM-4.7-Flash ($0.40/1M tokens) is 10.6x cheaper than Muse Spark Open ($4.25/1M tokens).
In conclusion, Muse Spark Open is more expensive than GLM-4.7-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Muse Spark Open has 786.0B more parameters than GLM-4.7-Flash, making it 2620.0% larger.
Context Window
Maximum input and output token capacity
Muse Spark Open accepts 1,048,576 input tokens compared to GLM-4.7-Flash's 128,000 tokens. Muse Spark Open can generate longer responses up to 1,048,576 tokens, while GLM-4.7-Flash is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
Muse Spark Open supports multimodal inputs, whereas GLM-4.7-Flash does not.
Muse Spark Open can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-4.7-Flash
Muse Spark Open
License
Usage and distribution terms
GLM-4.7-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-4.7-Flash was released on 2026-01-19, while Muse Spark Open was released on 2026-10-15.
Muse Spark Open is 9 months newer than GLM-4.7-Flash.
Jan 19, 2026
9 months ago
Oct 15, 2026
4 days ago
8mo 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-4.7-Flash is available from ZAI. Muse Spark Open is available from Together.
GLM-4.7-Flash
Muse Spark Open
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-4.7-Flash and Muse Spark Open side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-4.7-Flash vs Muse Spark Open.