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DeepSeek-V4-Pro-0813 vs Muse Glimmer-30B

DeepSeek-V4-Pro-0813 leads the LLM Stats Score 52.5 to 35.1.

DeepSeek · Meta · Updated for 2026

Which is better?

DeepSeek-V4-Pro-0813 leads the overall LLM Stats Score 52.5 to 35.1, ranking #10 overall.

In the 2 individual benchmarks reported for both models, DeepSeek-V4-Pro-0813 wins 2; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Pro-0813

  • overall performance matters — it scores 52.5 and ranks #10 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped Aug 2026

Choose Muse Glimmer-30B

  • you are already invested in the Meta ecosystem

At a glance

The differences that matter most.

Core performance indexes
52.5
#10
35.1
#83
50.1
#14
34.5
#85
41.2
#11
22.6
#75
37.8
#9
16.9
#70
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$0.43 / M
— / M
Output price
$0.87 / M
— / M
Context window
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4-Pro-0813
Muse Glimmer-30B
39.4#16
28.4#88
31.5#9
17.5#70
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

12 reported for DeepSeek-V4-Pro-0813 · 25 for Muse Glimmer-30B

2 shared

DeepSeek-V4-Pro-0813 outperforms in 2 benchmarks (Humanity's Last Exam, Terminal-Bench 2.1), while Muse Glimmer-30B is better at 0 benchmarks.

DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks.

Sat Sep 05 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

1570.4B diff

DeepSeek-V4-Pro-0813 has 1570.4B more parameters than Muse Glimmer-30B, making it 5305.4% larger.

DeepSeek
DeepSeek-V4-Pro-0813
1.6Tparameters
Meta
Muse Glimmer-30B
29.6Bparameters
1600.0B
DeepSeek-V4-Pro-0813
29.6B
Muse Glimmer-30B

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Pro-0813 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Pro-0813 specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4-Pro-0813
Input1,048,576 tokens
Output393,216 tokens
Meta
Muse Glimmer-30B
Input- tokens
Output- tokens
Sat Sep 05 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Muse Glimmer-30B supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.

Muse Glimmer-30B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4-Pro-0813

Text
Images
Audio
Video

Muse Glimmer-30B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4-Pro-0813 is licensed under MIT, while Muse Glimmer-30B uses Apache 2.0.

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

DeepSeek-V4-Pro-0813

MIT

Open weights

Muse Glimmer-30B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Muse Glimmer-30B was released on 2026-08-10.

DeepSeek-V4-Pro-0813 is 0 month newer than Muse Glimmer-30B.

DeepSeek-V4-Pro-0813

Aug 13, 2026

3 weeks ago

3d newer
Muse Glimmer-30B

Aug 10, 2026

3 weeks ago

Knowledge Cutoff

When training data ends

Muse Glimmer-30B has a documented knowledge cutoff of 2026-01-04, while DeepSeek-V4-Pro-0813's cutoff date is not specified.

We can confirm Muse Glimmer-30B's training data extends to 2026-01-04, but cannot make a direct comparison without DeepSeek-V4-Pro-0813's cutoff date.

DeepSeek-V4-Pro-0813

Muse Glimmer-30B

Jan 2026

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-V4-Pro-0813 and Muse Glimmer-30B side-by-side, then vote on the output you prefer.

DeepSeek-V4-Pro-0813
✓ Preferred
Muse Glimmer-30B
Open in Playground

FAQ

Common questions about DeepSeek-V4-Pro-0813 vs Muse Glimmer-30B.

Which is better, DeepSeek-V4-Pro-0813 or Muse Glimmer-30B?

DeepSeek-V4-Pro-0813 leads the LLM Stats Score 52.5 to 35.1. DeepSeek-V4-Pro-0813 is made by DeepSeek and Muse Glimmer-30B 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-V4-Pro-0813 compare to Muse Glimmer-30B in benchmarks?

DeepSeek-V4-Pro-0813 scores Terminal-Bench 2.1: 87.9%, CyberGym: 83.3%, Toolathlon: 74.1%, DSBench-FullStack: 71.1%, DSBench-Hard: 67.2%. Muse Glimmer-30B scores AIME 2026: 94.7%, Siren AgentDojo Utility: 94.2%, GPQA: 83.5%, AA-LCR: 80.0%, CharXiv-R: 78.8%.

What are the context window sizes for DeepSeek-V4-Pro-0813 and Muse Glimmer-30B?

DeepSeek-V4-Pro-0813 supports 1.0M tokens and Muse Glimmer-30B 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-0813 and Muse Glimmer-30B?

Key differences include LLM Stats Score (52.5 vs 35.1), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Pro-0813 and Muse Glimmer-30B?

DeepSeek-V4-Pro-0813 is developed by DeepSeek and Muse Glimmer-30B is developed by Meta.