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DeepSeek VL2 vs Muse Spark Open

Muse Spark Open leads the LLM Stats Score 44.9 to 2.6.

DeepSeek · Meta · Updated for 2026

Which is better?

Muse Spark Open leads the overall LLM Stats Score 44.9 to 2.6, ranking #43 overall.

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 DeepSeek VL2

  • you are already invested in the DeepSeek ecosystem

Choose Muse Spark Open

  • overall performance matters — it scores 44.9 and ranks #43 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • 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.

DeepSeek VL2
DeepSeek
Muse Spark Open
Meta
Core performance indexes
LLM Stats Score
2.6
#335
44.9
#43
Reasoning
-2.1
#353
45.2
#39
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$1.25 / M
Output price
— / M
$4.25 / M
Context window
129,280
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek VL2
Muse Spark Open
Vision
2.0#186
31.2#34
Multimodal
5.0#156
33.1#20
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for DeepSeek VL2 · 17 for Muse Spark Open

No common benchmarks found

DeepSeek VL2 and Muse Spark Opendon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

789.0B diff

Muse Spark Open has 789.0B more parameters than DeepSeek VL2, making it 2922.2% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
Meta
Muse Spark Open
816.0Bparameters
27.0B
DeepSeek VL2
816.0B
Muse Spark Open

Context Window

Maximum input and output token capacity

Muse Spark Open accepts 1,048,576 input tokens compared to DeepSeek VL2's 129,280 tokens. Muse Spark Open can generate longer responses up to 1,048,576 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Meta
Muse Spark Open
Input1,048,576 tokens
Output1,048,576 tokens
Tue Oct 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek VL2 and Muse Spark Open support multimodal inputs.

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

DeepSeek VL2

Text
Images
Audio
Video

Muse Spark Open

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while Muse Spark Open uses Muse Model License.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek VL2

deepseek

Open weights

Muse Spark Open

Muse Model License

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while Muse Spark Open was released on 2026-10-15.

Muse Spark Open is 22 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.8 years ago

Muse Spark Open

Oct 15, 2026

4 days ago

1.8yr 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

DeepSeek VL2 is available from Replicate. Muse Spark Open is available from Together.

DeepSeek VL2

replicate logo
Replicate

Muse Spark Open

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

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek VL2 and Muse Spark Open side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
Muse Spark Open
Open in Playground

FAQ

Common questions about DeepSeek VL2 vs Muse Spark Open.

Which is better, DeepSeek VL2 or Muse Spark Open?

Muse Spark Open leads the LLM Stats Score 44.9 to 2.6. DeepSeek VL2 is made by DeepSeek and Muse Spark Open is made by Meta. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek VL2 compare to Muse Spark Open in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. Muse Spark Open scores MCP Atlas: 89.2%, GPQA: 89.0%, OSWorld-Verified: 80.4%, BabyVision: 80.2%, Terminal-Bench 2.1: 76.4%.

What are the context window sizes for DeepSeek VL2 and Muse Spark Open?

DeepSeek VL2 supports 129K tokens and Muse Spark Open 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 DeepSeek VL2 and Muse Spark Open?

Key differences include LLM Stats Score (2.6 vs 44.9), context window (129K vs 1.0M), licensing (deepseek vs Muse Model License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and Muse Spark Open?

DeepSeek VL2 is developed by DeepSeek and Muse Spark Open is developed by Meta.

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