Model Comparison

GLM-4.7 vs Muse Spark 1.1Which is better in 2026?

Muse Spark 1.1 significantly outperforms across most benchmarks. GLM-4.7 is 2.0x cheaper per token.

Verdict: GLM-4.7 vs Muse Spark 1.1 — which is better?

GLM-4.7 (by Zhipu AI) and Muse Spark 1.1 (by Meta) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

GLM-4.7 outperforms in 0 benchmarks, while Muse Spark 1.1 is better at 1 benchmark (Humanity's Last Exam). Muse Spark 1.1 significantly outperforms across most benchmarks.

On price, GLM-4.7 is roughly 2.0x 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.

Choose GLM-4.7 if…

  • cost matters — it's about 2.0x cheaper per token
  • you need open weights you can self-host or fine-tune

Choose Muse Spark 1.1 if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Jul 2026

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GLM-4.7 outperforms in 0 benchmarks, while Muse Spark 1.1 is better at 1 benchmark (Humanity's Last Exam).

Muse Spark 1.1 significantly outperforms across most benchmarks.

Tue Jul 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GLM-4.7 costs less

For input processing, GLM-4.7 ($0.60/1M tokens) is 2.1x cheaper than Muse Spark 1.1 ($1.25/1M tokens).

For output processing, GLM-4.7 ($2.20/1M tokens) is 1.9x cheaper than Muse Spark 1.1 ($4.25/1M tokens).

In conclusion, Muse Spark 1.1 is more expensive than GLM-4.7.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Jul 21 2026 • llm-stats.com
Zhipu AI
GLM-4.7
Input tokens$0.60
Output tokens$2.20
Best providerFireworks
Meta
Muse Spark 1.1
Input tokens$1.25
Output tokens$4.25
Best providerMeta
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Muse Spark 1.1 accepts 1,048,576 input tokens compared to GLM-4.7's 202,800 tokens. Both models can generate responses up to 131,072 tokens.

Zhipu AI
GLM-4.7
Input202,800 tokens
Output131,072 tokens
Meta
Muse Spark 1.1
Input1,048,576 tokens
Output131,072 tokens
Tue Jul 21 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both GLM-4.7 and Muse Spark 1.1 support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

GLM-4.7

Text
Images
Audio
Video

Muse Spark 1.1

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.7 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.

GLM-4.7

MIT

Open weights

Muse Spark 1.1

Proprietary

Closed source

Release Timeline

When each model was launched

GLM-4.7 was released on 2025-12-22, while Muse Spark 1.1 was released on 2026-07-09.

Muse Spark 1.1 is 7 months newer than GLM-4.7.

GLM-4.7

Dec 22, 2025

7 months ago

Muse Spark 1.1

Jul 9, 2026

1 weeks ago

6mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

GLM-4.7 is available from Fireworks, Novita. Muse Spark 1.1 is available from Meta Model API.

GLM-4.7

fireworks logo
Fireworks
Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M
novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M

Muse Spark 1.1

meta logo
Meta
Input Price:Input: $1.25/1MOutput Price:Output: $4.25/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Zhipu AI
Less expensive input tokens
Less expensive output tokens
Has open weights
Meta
Larger context window (1,048,576 tokens)
Higher Humanity's Last Exam score (62.1% vs 42.8%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against GLM-4.7 and Muse Spark 1.1 side-by-side, then vote on the output you prefer.

GLM-4.7
✓ Preferred
Muse Spark 1.1
Open in Playground
AI Model Comparison Table
Feature
Zhipu AI
GLM-4.7
Meta
Muse Spark 1.1

FAQ

Common questions about GLM-4.7 vs Muse Spark 1.1.

Which is better, GLM-4.7 or Muse Spark 1.1?

Muse Spark 1.1 significantly outperforms across most benchmarks. GLM-4.7 is made by Zhipu AI and Muse Spark 1.1 is made by Meta. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GLM-4.7 compare to Muse Spark 1.1 in benchmarks?

GLM-4.7 scores AIME 2025: 95.7%, Tau-bench: 87.4%, GPQA: 85.7%, LiveCodeBench v6: 84.9%, MMLU-Pro: 84.3%. Muse Spark 1.1 scores CharXiv-R: 88.4%, MCP Atlas: 88.1%, OSWorld-Verified: 80.8%, Terminal-Bench 2.1: 80.0%, BabyVision: 76.3%.

Is GLM-4.7 cheaper than Muse Spark 1.1?

GLM-4.7 is 2.1x cheaper for input tokens. GLM-4.7 costs $0.60/M input and $2.20/M output via fireworks. Muse Spark 1.1 costs $1.25/M input and $4.25/M output via meta.

What are the context window sizes for GLM-4.7 and Muse Spark 1.1?

GLM-4.7 supports 203K tokens and Muse Spark 1.1 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-4.7 and Muse Spark 1.1?

Key differences include context window (203K vs 1.0M), input pricing ($0.60 vs $1.25/M), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.7 and Muse Spark 1.1?

GLM-4.7 is developed by Zhipu AI and Muse Spark 1.1 is developed by Meta.

Related comparisons