Muse Spark 1.3 vs Qwen2.5-Coder 32B Instruct
Muse Spark 1.3 leads the LLM Stats Score 55.4 to 2.3. Qwen2.5-Coder 32B Instruct is 1.4x cheaper per token.
Meta · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Muse Spark 1.3 leads the overall LLM Stats Score 55.4 to 2.3, ranking #5 overall.
On price, Qwen2.5-Coder 32B Instruct is roughly 1.4x 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 Muse Spark 1.3
- overall performance matters — it scores 55.4 and ranks #5 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Qwen2.5-Coder 32B Instruct
- cost matters — it's about 1.4x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
11 reported for Muse Spark 1.3 · 15 for Qwen2.5-Coder 32B Instruct
Muse Spark 1.3 and Qwen2.5-Coder 32B Instructdon'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
For input processing, Muse Spark 1.3 ($0.10/1M tokens) is 1.1x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
For output processing, Muse Spark 1.3 ($0.20/1M tokens) is 2.2x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
In conclusion, Muse Spark 1.3 is more expensive than Qwen2.5-Coder 32B Instruct.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Spark 1.3 accepts 1,048,576 input tokens compared to Qwen2.5-Coder 32B Instruct's 128,000 tokens. Muse Spark 1.3 can generate longer responses up to 943,718 tokens, while Qwen2.5-Coder 32B Instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Muse Spark 1.3 supports multimodal inputs, whereas Qwen2.5-Coder 32B Instruct does not.
Muse Spark 1.3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Muse Spark 1.3
Qwen2.5-Coder 32B Instruct
License
Usage and distribution terms
Muse Spark 1.3 is licensed under a proprietary license, while Qwen2.5-Coder 32B Instruct uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Muse Spark 1.3 was released on 2026-09-02, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
Muse Spark 1.3 is 24 months newer than Qwen2.5-Coder 32B Instruct.
Sep 2, 2026
0 days ago
2.0yr newerSep 19, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Muse Spark 1.3 is available from Meta Model API. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.
Muse Spark 1.3
Qwen2.5-Coder 32B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Muse Spark 1.3 and Qwen2.5-Coder 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Muse Spark 1.3 vs Qwen2.5-Coder 32B Instruct.