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DeepSeek-V3.2-Speciale vs Muse Spark 1.3

Muse Spark 1.3 leads the LLM Stats Score 55.3 to 34.3. Muse Spark 1.3 is 2.5x cheaper per token.

DeepSeek · Meta · Updated for 2026

Which is better?

Muse Spark 1.3 leads the overall LLM Stats Score 55.3 to 34.3, ranking #5 overall.

On price, Muse Spark 1.3 is roughly 2.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Muse Spark 1.3 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

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

Choose DeepSeek-V3.2-Speciale

  • you need open weights you can self-host or fine-tune

Choose Muse Spark 1.3

  • overall performance matters — it scores 55.3 and ranks #5 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • cost matters — it's about 2.5x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

DeepSeek-V3.2-Speciale
DeepSeek
Muse Spark 1.3
Meta
Core performance indexes
LLM Stats Score
34.3
#87
55.3
#5
Reasoning
32.9
#95
52.8
#7
Coding
18.4
#105
41.7
#10
Agents
10.4
#105
40.4
#4
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.28 / M
$0.10 / M
Output price
$0.42 / M
$0.20 / M
Context window
131,072
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3.2-Speciale
Muse Spark 1.3
Tool use
9.8#124
35.5#2
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

8 reported for DeepSeek-V3.2-Speciale · 11 for Muse Spark 1.3

No common benchmarks found

DeepSeek-V3.2-Speciale 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

Muse Spark 1.3 costs less

For input processing, DeepSeek-V3.2-Speciale ($0.28/1M tokens) is 2.8x more expensive than Muse Spark 1.3 ($0.10/1M tokens).

For output processing, DeepSeek-V3.2-Speciale ($0.42/1M tokens) is 2.1x more expensive than Muse Spark 1.3 ($0.20/1M tokens).

In conclusion, DeepSeek-V3.2-Speciale is more expensive than Muse Spark 1.3.*

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

Lowest available price from all providers
Mon Sep 07 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Speciale
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
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

Muse Spark 1.3 accepts 1,048,576 input tokens compared to DeepSeek-V3.2-Speciale's 131,072 tokens. Muse Spark 1.3 can generate longer responses up to 943,718 tokens, while DeepSeek-V3.2-Speciale is limited to 131,072 tokens.

DeepSeek
DeepSeek-V3.2-Speciale
Input131,072 tokens
Output131,072 tokens
Meta
Muse Spark 1.3
Input1,048,576 tokens
Output943,718 tokens
Mon Sep 07 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Muse Spark 1.3 supports multimodal inputs, whereas DeepSeek-V3.2-Speciale does not.

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

DeepSeek-V3.2-Speciale

Text
Images
Audio
Video

Muse Spark 1.3

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2-Speciale 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-V3.2-Speciale

MIT

Open weights

Muse Spark 1.3

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3.2-Speciale was released on 2025-12-01, while Muse Spark 1.3 was released on 2026-09-02.

Muse Spark 1.3 is 9 months newer than DeepSeek-V3.2-Speciale.

DeepSeek-V3.2-Speciale

Dec 1, 2025

9 months ago

Muse Spark 1.3

Sep 2, 2026

4 days ago

9mo 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-V3.2-Speciale is available from DeepSeek. Muse Spark 1.3 is available from Meta Model API.

DeepSeek-V3.2-Speciale

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

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-V3.2-Speciale and Muse Spark 1.3 side-by-side, then vote on the output you prefer.

DeepSeek-V3.2-Speciale
✓ Preferred
Muse Spark 1.3
Open in Playground

FAQ

Common questions about DeepSeek-V3.2-Speciale vs Muse Spark 1.3.

Which is better, DeepSeek-V3.2-Speciale or Muse Spark 1.3?

Muse Spark 1.3 leads the LLM Stats Score 55.3 to 34.3. DeepSeek-V3.2-Speciale 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-V3.2-Speciale compare to Muse Spark 1.3 in benchmarks?

DeepSeek-V3.2-Speciale scores HMMT 2025: 99.2%, AIME 2025: 96.0%, CodeForces: 90.0%, t2-bench: 80.3%, SWE-Bench Verified: 73.1%. 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-V3.2-Speciale cheaper than Muse Spark 1.3?

Muse Spark 1.3 is 2.8x cheaper for input tokens. DeepSeek-V3.2-Speciale costs $0.28/M input and $0.42/M output via deepseek. Muse Spark 1.3 costs $0.10/M input and $0.20/M output via meta.

What are the context window sizes for DeepSeek-V3.2-Speciale and Muse Spark 1.3?

DeepSeek-V3.2-Speciale supports 131K 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-V3.2-Speciale and Muse Spark 1.3?

Key differences include LLM Stats Score (34.3 vs 55.3), context window (131K vs 1.0M), input pricing ($0.28 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-V3.2-Speciale and Muse Spark 1.3?

DeepSeek-V3.2-Speciale is developed by DeepSeek and Muse Spark 1.3 is developed by Meta.

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