Model Comparison

DeepSeek-V4-Pro-Max vs Muse Spark 1.1Which is better in 2026?

Muse Spark 1.1 significantly outperforms across most benchmarks.

Verdict: DeepSeek-V4-Pro-Max vs Muse Spark 1.1 — which is better?

DeepSeek-V4-Pro-Max (by DeepSeek) 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.

DeepSeek-V4-Pro-Max outperforms in 0 benchmarks, while Muse Spark 1.1 is better at 4 benchmarks (Humanity's Last Exam, MCP Atlas, SWE-Bench Pro, Toolathlon). Muse Spark 1.1 significantly outperforms across most benchmarks.

Choose DeepSeek-V4-Pro-Max if…

  • 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 4 of 4 shared benchmarks
  • you want the most recent training data — it shipped Jul 2026

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-V4-Pro-Max outperforms in 0 benchmarks, while Muse Spark 1.1 is better at 4 benchmarks (Humanity's Last Exam, MCP Atlas, SWE-Bench Pro, Toolathlon).

Muse Spark 1.1 significantly outperforms across most benchmarks.

Fri Jul 17 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Pro-Max specifies input context (1,048,576 tokens). Only DeepSeek-V4-Pro-Max specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V4-Pro-Max
Input1,048,576 tokens
Output131,072 tokens
Meta
Muse Spark 1.1
Input- tokens
Output- tokens
Fri Jul 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Muse Spark 1.1 supports multimodal inputs, whereas DeepSeek-V4-Pro-Max does not.

Muse Spark 1.1 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4-Pro-Max

Text
Images
Audio
Video

Muse Spark 1.1

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4-Pro-Max 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.

DeepSeek-V4-Pro-Max

MIT

Open weights

Muse Spark 1.1

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V4-Pro-Max was released on 2026-04-23, while Muse Spark 1.1 was released on 2026-07-09.

Muse Spark 1.1 is 3 months newer than DeepSeek-V4-Pro-Max.

DeepSeek-V4-Pro-Max

Apr 23, 2026

2 months ago

Muse Spark 1.1

Jul 9, 2026

1 weeks ago

2mo 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Larger context window (1,048,576 tokens)
Has open weights
Meta
Supports multimodal inputs
Higher Humanity's Last Exam score (62.1% vs 48.2%)
Higher MCP Atlas score (88.1% vs 73.6%)
Higher SWE-Bench Pro score (61.5% vs 55.4%)
Higher Toolathlon score (75.6% vs 51.8%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V4-Pro-Max and Muse Spark 1.1 side-by-side, then vote on the output you prefer.

DeepSeek-V4-Pro-Max
✓ Preferred
Muse Spark 1.1
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V4-Pro-Max
Meta
Muse Spark 1.1

FAQ

Common questions about DeepSeek-V4-Pro-Max vs Muse Spark 1.1.

Which is better, DeepSeek-V4-Pro-Max or Muse Spark 1.1?

Muse Spark 1.1 significantly outperforms across most benchmarks. DeepSeek-V4-Pro-Max is made by DeepSeek 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 DeepSeek-V4-Pro-Max compare to Muse Spark 1.1 in benchmarks?

DeepSeek-V4-Pro-Max scores CodeForces: 100.0%, HMMT Feb 26: 95.2%, LiveCodeBench: 93.5%, MathArena Apex: 90.2%, GPQA: 90.1%. 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%.

What are the context window sizes for DeepSeek-V4-Pro-Max and Muse Spark 1.1?

DeepSeek-V4-Pro-Max supports 1.0M tokens and Muse Spark 1.1 supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4-Pro-Max and Muse Spark 1.1?

Key differences include multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Pro-Max and Muse Spark 1.1?

DeepSeek-V4-Pro-Max is developed by DeepSeek and Muse Spark 1.1 is developed by Meta.

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