DeepSeek-V4-Flash-Vision-Exp vs Muse Spark 1.3
Muse Spark 1.3 leads the LLM Stats Score 54.3 to 46.0. DeepSeek-V4-Flash-Vision-Exp is 6.1x cheaper per token.
DeepSeek · Meta · Updated for 2026
Which is better?
Muse Spark 1.3 leads the overall LLM Stats Score 54.3 to 46.0, ranking #6 overall.
In the 2 individual benchmarks reported for both models, Muse Spark 1.3 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4-Flash-Vision-Exp is roughly 6.1x 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-Vision-Exp
- cost matters — it's about 6.1x cheaper per token
Choose Muse Spark 1.3
- overall performance matters — it scores 54.3 and ranks #6 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
7 reported for DeepSeek-V4-Flash-Vision-Exp · 11 for Muse Spark 1.3
DeepSeek-V4-Flash-Vision-Exp outperforms in 0 benchmarks, while Muse Spark 1.3 is better at 2 benchmarks (AutomationBench, Terminal-Bench 2.1).
Muse Spark 1.3 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-Vision-Exp ($0.22/1M tokens) is 5.7x cheaper than Muse Spark 1.3 ($1.25/1M tokens).
For output processing, DeepSeek-V4-Flash-Vision-Exp ($0.66/1M tokens) is 6.4x cheaper than Muse Spark 1.3 ($4.25/1M tokens).
In conclusion, Muse Spark 1.3 is more expensive than DeepSeek-V4-Flash-Vision-Exp.*
* Using a 3:1 ratio of input to output tokens
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-Flash-Vision-Exp is limited to 393,216 tokens.
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4-Flash-Vision-Exp and Muse Spark 1.3 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4-Flash-Vision-Exp
Muse Spark 1.3
Release Timeline
When each model was launched
DeepSeek-V4-Flash-Vision-Exp was released on 2026-08-21, while Muse Spark 1.3 was released on 2026-09-02.
Muse Spark 1.3 is 0 month newer than DeepSeek-V4-Flash-Vision-Exp.
Aug 21, 2026
1 months ago
Sep 2, 2026
2 weeks ago
1w newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Flash-Vision-Exp is available from DeepSeek, DeepInfra. Muse Spark 1.3 is available from Meta Model API.
DeepSeek-V4-Flash-Vision-Exp
Muse Spark 1.3
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-Vision-Exp and Muse Spark 1.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-Vision-Exp vs Muse Spark 1.3.