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

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 44.9. DeepSeek-V4.1-Flash-1017 is 3.8x cheaper per token.

DeepSeek · Meta · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 44.9, ranking #15 overall.

In the 3 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 wins 3; 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

  • overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
  • your work emphasizes agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results
  • cost matters — it's about 3.8x cheaper per token
  • you want the most recent training data — it shipped Oct 2026

Choose Muse Spark Open

  • 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 Open
Meta
Core performance indexes
LLM Stats Score
51.0
#15
44.9
#43
Reasoning
48.6
#18
45.2
#39
Coding
39.1
#15
33.0
#42
Agents
38.6
#9
30.6
#43
Cost, coverage & limits
Benchmark wins
3 of 3
0 of 3
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

4 shared
Index
DeepSeek-V4.1-Flash-1017
Muse Spark Open
Math
31.8#67
31.6#69
Vision
32.2#26
31.2#34
Tool use
30.9#7
23.3#44
Multimodal
35.0#14
33.1#20
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 17 for Muse Spark Open

3 shared

DeepSeek-V4.1-Flash-1017 outperforms in 3 benchmarks (BabyVision, DeepSWE 1.1, ZEROBench), while Muse Spark Open 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 Open ($1.25/1M tokens).

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

In conclusion, Muse Spark Open 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 Open
Input tokens$1.25
Output tokens$4.25
Best providerTogether
Notice missing or incorrect data?

Model Size

Parameter count comparison

52.8B diff

Muse Spark Open has 52.8B more parameters than DeepSeek-V4.1-Flash-1017, making it 6.9% larger.

DeepSeek
DeepSeek-V4.1-Flash-1017
763.2Bparameters
Meta
Muse Spark Open
816.0Bparameters
763.2B
DeepSeek-V4.1-Flash-1017
816.0B
Muse Spark Open

Context Window

Maximum input and output token capacity

Both models have the same input context window of 1,048,576 tokens. Muse Spark Open can generate longer responses up to 1,048,576 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 Open
Input1,048,576 tokens
Output1,048,576 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 Open 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 Open

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 is licensed under MIT, 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-V4.1-Flash-1017

MIT

Open weights

Muse Spark Open

Muse Model License

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while Muse Spark Open was released on 2026-10-15.

DeepSeek-V4.1-Flash-1017 is 0 month newer than Muse Spark Open.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

0 days ago

2d newer
Muse Spark Open

Oct 15, 2026

2 days 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 Open is available from Together.

DeepSeek-V4.1-Flash-1017

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

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-V4.1-Flash-1017 and Muse Spark Open side-by-side, then vote on the output you prefer.

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

FAQ

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

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

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 44.9. DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017 compare to Muse Spark Open 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 Open scores MCP Atlas: 89.2%, GPQA: 89.0%, OSWorld-Verified: 80.4%, BabyVision: 80.2%, Terminal-Bench 2.1: 76.4%.

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

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 Open costs $1.25/M input and $4.25/M output via together.

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

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

Key differences include LLM Stats Score (51.0 vs 44.9), input pricing ($0.30 vs $1.25/M), licensing (MIT vs Muse Model License). See the full comparison above for benchmark-by-benchmark results.

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

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

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