Muse Spark Open vs Qwen2.5-Coder 32B Instruct
Muse Spark Open leads the LLM Stats Score 44.9 to 1.7. Qwen2.5-Coder 32B Instruct is 22.2x cheaper per token.
Meta · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Muse Spark Open leads the overall LLM Stats Score 44.9 to 1.7, ranking #43 overall.
On price, Qwen2.5-Coder 32B Instruct is roughly 22.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Spark Open 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 Open
- overall performance matters — it scores 44.9 and ranks #43 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 Oct 2026
Choose Qwen2.5-Coder 32B Instruct
- cost matters — it's about 22.2x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
17 reported for Muse Spark Open · 15 for Qwen2.5-Coder 32B Instruct
Muse Spark Open 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 Open ($1.25/1M tokens) is 13.9x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
For output processing, Muse Spark Open ($4.25/1M tokens) is 47.2x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).
In conclusion, Muse Spark Open is more expensive than Qwen2.5-Coder 32B Instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Muse Spark Open has 784.0B more parameters than Qwen2.5-Coder 32B Instruct, making it 2450.0% larger.
Context Window
Maximum input and output token capacity
Muse Spark Open accepts 1,048,576 input tokens compared to Qwen2.5-Coder 32B Instruct's 128,000 tokens. Muse Spark Open can generate longer responses up to 1,048,576 tokens, while Qwen2.5-Coder 32B Instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Muse Spark Open supports multimodal inputs, whereas Qwen2.5-Coder 32B Instruct does not.
Muse Spark Open can handle both text and other forms of data like images, making it suitable for multimodal applications.
Muse Spark Open
Qwen2.5-Coder 32B Instruct
License
Usage and distribution terms
Muse Spark Open is licensed under Muse Model 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.
Muse Model License
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Muse Spark Open was released on 2026-10-15, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.
Muse Spark Open is 25 months newer than Qwen2.5-Coder 32B Instruct.
Oct 15, 2026
4 days ago
2.1yr newerSep 19, 2024
2.1 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 Open is available from Together. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.
Muse Spark Open
Qwen2.5-Coder 32B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against Muse Spark Open and Qwen2.5-Coder 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Muse Spark Open vs Qwen2.5-Coder 32B Instruct.
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