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DeepSeek-V4.1-Flash-1017 vs Muse Spark 1.3

DeepSeek-V4.1-Flash-1017 and Muse Spark 1.3 are closely matched at 51.0 and 51.9 on the LLM Stats Score. DeepSeek-V4.1-Flash-1017 is 3.8x cheaper per token.

DeepSeek · Meta · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 and Muse Spark 1.3 are closely matched on the overall LLM Stats Score at 51.0 and 51.9.

In the 2 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 wins 2; this is a narrower head-to-head signal than the composite indexes.

On price, DeepSeek-V4.1-Flash-1017 is roughly 3.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

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

Choose DeepSeek-V4.1-Flash-1017

  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • cost matters — it's about 3.8x cheaper per token
  • you want the most recent training data — it shipped Oct 2026
  • you need open weights you can self-host or fine-tune

Choose Muse Spark 1.3

  • you want predictable pricing at $1.25/M input and $4.25/M output

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash-1017
DeepSeek
Muse Spark 1.3
Meta
Core performance indexes
LLM Stats Score
51.0
#15
51.9
#13
Reasoning
48.6
#18
50.8
#11
Coding
39.1
#15
37.4
#24
Agents
38.6
#9
37.3
#15
Cost, coverage & limits
Benchmark wins
2 of 2
0 of 2
Input price
$0.30 / M
$1.25 / M
Output price
$1.20 / M
$4.25 / M
Context window
1,048,576
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash-1017
Muse Spark 1.3
Tool use
30.9#7
30.6#9
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 11 for Muse Spark 1.3

2 shared

DeepSeek-V4.1-Flash-1017 outperforms in 2 benchmarks (AutomationBench, DeepSWE 1.1), while Muse Spark 1.3 is better at 0 benchmarks.

DeepSeek-V4.1-Flash-1017 significantly outperforms across most benchmarks.

Mon Oct 19 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

DeepSeek-V4.1-Flash-1017 costs less

For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 4.2x cheaper than Muse Spark 1.3 ($1.25/1M tokens).

For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 3.5x cheaper than Muse Spark 1.3 ($4.25/1M tokens).

In conclusion, Muse Spark 1.3 is more expensive than DeepSeek-V4.1-Flash-1017.*

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

Lowest available price from all providers
Mon Oct 19 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash-1017
Input tokens$0.30
Output tokens$1.20
Best providerDeepSeek
Meta
Muse Spark 1.3
Input tokens$1.25
Output tokens$4.25
Best providerMeta
Notice missing or incorrect data?

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,048,576 tokens. Muse Spark 1.3 can generate longer responses up to 943,718 tokens, while DeepSeek-V4.1-Flash-1017 is limited to 393,216 tokens.

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
Meta
Muse Spark 1.3
Input1,048,576 tokens
Output943,718 tokens
Mon Oct 19 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash-1017 and Muse Spark 1.3 support multimodal inputs.

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

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

Muse Spark 1.3

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, while Muse Spark 1.3 uses a proprietary license.

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

DeepSeek-V4.1-Flash-1017

MIT

Open weights

Muse Spark 1.3

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Muse Spark 1.3 was released on 2026-09-02.

DeepSeek-V4.1-Flash-1017 is 2 months newer than Muse Spark 1.3.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

0 days ago

1mo newer
Muse Spark 1.3

Sep 2, 2026

1 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

Provider Availability

DeepSeek-V4.1-Flash-1017 is available from DeepSeek. Muse Spark 1.3 is available from Meta Model API.

DeepSeek-V4.1-Flash-1017

deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Muse Spark 1.3

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?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and Muse Spark 1.3 side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
Muse Spark 1.3
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs Muse Spark 1.3.

Which is better, DeepSeek-V4.1-Flash-1017 or Muse Spark 1.3?

DeepSeek-V4.1-Flash-1017 and Muse Spark 1.3 are closely matched on the LLM Stats Score at 51.0 and 51.9. DeepSeek-V4.1-Flash-1017 is made by DeepSeek and Muse Spark 1.3 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-1017 compare to Muse Spark 1.3 in benchmarks?

DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%. Muse Spark 1.3 scores MRCR v2 (8-needle): 98.5%, MRCR v2 (8-needle, 512K-1M): 98.1%, DeepSearchQA: 89.4%, Terminal-Bench 2.1: 88.8%, DeepSWE 1.1: 75.4%.

Is DeepSeek-V4.1-Flash-1017 cheaper than Muse Spark 1.3?

DeepSeek-V4.1-Flash-1017 is 4.2x cheaper for input tokens. DeepSeek-V4.1-Flash-1017 costs $0.30/M input and $1.20/M output via deepseek. Muse Spark 1.3 costs $1.25/M input and $4.25/M output via meta.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and Muse Spark 1.3?

DeepSeek-V4.1-Flash-1017 supports 1.0M tokens and Muse Spark 1.3 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-V4.1-Flash-1017 and Muse Spark 1.3?

Key differences include LLM Stats Score (51.0 vs 51.9), input pricing ($0.30 vs $1.25/M), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash-1017 and Muse Spark 1.3?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and Muse Spark 1.3 is developed by Meta.

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