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DeepSeek-V4-Flash-Max vs Muse Spark 1.3

Muse Spark 1.3 leads the LLM Stats Score 55.1 to 39.1. DeepSeek-V4-Flash-Max is 1.1x cheaper per token.

DeepSeek · Meta · Updated for 2026

Which is better?

Muse Spark 1.3 leads the overall LLM Stats Score 55.1 to 39.1, ranking #4 overall.

On price, DeepSeek-V4-Flash-Max is roughly 1.1x 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-Flash-Max

  • cost matters — it's about 1.1x cheaper per token
  • you need open weights you can self-host or fine-tune

Choose Muse Spark 1.3

  • overall performance matters — it scores 55.1 and ranks #4 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek-V4-Flash-Max
DeepSeek
Muse Spark 1.3
Meta
Core performance indexes
LLM Stats Score
39.1
#59
55.1
#4
Reasoning
39.8
#54
52.6
#7
Coding
28.9
#54
41.9
#9
Agents
18.5
#66
40.6
#4
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.09 / M
$0.10 / M
Output price
$0.18 / M
$0.20 / M
Context window
1,048,576
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek-V4-Flash-Max
Muse Spark 1.3
Tool use
17.3#72
35.8#2
Long context
11.5#65
31.9#1
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

19 reported for DeepSeek-V4-Flash-Max · 11 for Muse Spark 1.3

No common benchmarks found

DeepSeek-V4-Flash-Max and Muse Spark 1.3don'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

Pricing Analysis

Price comparison per million tokens

DeepSeek-V4-Flash-Max costs less

For input processing, DeepSeek-V4-Flash-Max ($0.09/1M tokens) is 1.1x cheaper than Muse Spark 1.3 ($0.10/1M tokens).

For output processing, DeepSeek-V4-Flash-Max ($0.18/1M tokens) is 1.1x cheaper than Muse Spark 1.3 ($0.20/1M tokens).

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

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

Lowest available price from all providers
Wed Sep 09 2026 • llm-stats.com
DeepSeek
DeepSeek-V4-Flash-Max
Input tokens$0.09
Output tokens$0.18
Best providerDeepinfra
Meta
Muse Spark 1.3
Input tokens$0.10
Output tokens$0.20
Best providerMeta
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

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

DeepSeek
DeepSeek-V4-Flash-Max
Input1,048,576 tokens
Output1,048,576 tokens
Meta
Muse Spark 1.3
Input1,048,576 tokens
Output943,718 tokens
Wed Sep 09 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Muse Spark 1.3 supports multimodal inputs, whereas DeepSeek-V4-Flash-Max does not.

Muse Spark 1.3 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4-Flash-Max

Text
Images
Audio
Video

Muse Spark 1.3

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4-Flash-Max 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-Flash-Max

MIT

Open weights

Muse Spark 1.3

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V4-Flash-Max was released on 2026-04-23, while Muse Spark 1.3 was released on 2026-09-02.

Muse Spark 1.3 is 4 months newer than DeepSeek-V4-Flash-Max.

DeepSeek-V4-Flash-Max

Apr 23, 2026

4 months ago

Muse Spark 1.3

Sep 2, 2026

1 weeks ago

4mo 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-V4-Flash-Max is available from DeepInfra, DeepSeek. Muse Spark 1.3 is available from Meta Model API.

DeepSeek-V4-Flash-Max

deepinfra logo
Deepinfra
Input Price:Input: $0.09/1MOutput Price:Output: $0.18/1M
deepseek logo
DeepSeek
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M

Muse Spark 1.3

meta logo
Meta
Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

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

DeepSeek-V4-Flash-Max
✓ Preferred
Muse Spark 1.3
Open in Playground

FAQ

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

Which is better, DeepSeek-V4-Flash-Max or Muse Spark 1.3?

Muse Spark 1.3 leads the LLM Stats Score 55.1 to 39.1. DeepSeek-V4-Flash-Max 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-Flash-Max compare to Muse Spark 1.3 in benchmarks?

DeepSeek-V4-Flash-Max scores CodeForces: 100.0%, HMMT Feb 26: 94.8%, LiveCodeBench: 91.6%, IMO-AnswerBench: 88.4%, GPQA: 88.1%. 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-Flash-Max cheaper than Muse Spark 1.3?

DeepSeek-V4-Flash-Max is 1.1x cheaper for input tokens. DeepSeek-V4-Flash-Max costs $0.09/M input and $0.18/M output via deepinfra. Muse Spark 1.3 costs $0.10/M input and $0.20/M output via meta.

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

DeepSeek-V4-Flash-Max 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-Flash-Max and Muse Spark 1.3?

Key differences include LLM Stats Score (39.1 vs 55.1), input pricing ($0.09 vs $0.10/M), multimodal support (no vs yes), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-Max and Muse Spark 1.3?

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

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