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DeepSeek-V4.1-Flash vs Muse Spark

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.5 to 41.7.

DeepSeek · Meta · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.5 to 41.7, ranking #13 overall.

In the 3 individual benchmarks reported for both models, DeepSeek-V4.1-Flash 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-V4.1-Flash

  • overall performance matters — it scores 51.5 and ranks #13 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 3 exact shared results
  • you want the most recent training data — it shipped Sep 2026
  • you need open weights you can self-host or fine-tune

Choose Muse Spark

  • you are already invested in the Meta ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
Muse Spark
Meta
Core performance indexes
LLM Stats Score
51.5
#13
41.7
#53
Reasoning
48.6
#19
40.6
#53
Coding
43.8
#5
23.1
#79
Agents
40.6
#4
14.3
#93
Cost, coverage & limits
Benchmark wins
2 of 3
1 of 3
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,040,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

3 shared
Index
DeepSeek-V4.1-Flash
Muse Spark
Vision
29.5#31
31.2#26
Tool use
32.1#2
16.2#82
Multimodal
34.2#13
32.4#21
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 19 for Muse Spark

3 shared

DeepSeek-V4.1-Flash outperforms in 2 benchmarks (GPQA, ZEROBench), while Muse Spark is better at 1 benchmark (Humanity's Last Exam).

DeepSeek-V4.1-Flash shows notably better performance in the majority of benchmarks.

Tue Sep 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Meta
Muse Spark
Input- tokens
Output- tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash and Muse Spark support multimodal inputs.

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

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

Muse Spark

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while Muse Spark uses a proprietary license.

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

DeepSeek-V4.1-Flash

MIT

Open weights

Muse Spark

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Muse Spark was released on 2026-04-08.

DeepSeek-V4.1-Flash is 5 months newer than Muse Spark.

DeepSeek-V4.1-Flash

Sep 10, 2026

1 weeks ago

5mo newer
Muse Spark

Apr 8, 2026

5 months ago

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→

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash and Muse Spark side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
Muse Spark
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs Muse Spark.

Which is better, DeepSeek-V4.1-Flash or Muse Spark?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.5 to 41.7. DeepSeek-V4.1-Flash is made by DeepSeek and Muse Spark 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-V4.1-Flash compare to Muse Spark in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. Muse Spark scores Tau2 Telecom: 91.5%, GPQA: 89.5%, CharXiv-R: 86.4%, ScreenSpot Pro: 84.1%, IPhO 2025: 82.6%.

What are the context window sizes for DeepSeek-V4.1-Flash and Muse Spark?

DeepSeek-V4.1-Flash supports 1.0M tokens and Muse Spark 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-V4.1-Flash and Muse Spark?

Key differences include LLM Stats Score (51.5 vs 41.7), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and Muse Spark?

DeepSeek-V4.1-Flash is developed by DeepSeek and Muse Spark is developed by Meta.

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