Inkling vs Muse Spark 1.3
Muse Spark 1.3 leads the LLM Stats Score 55.1 to 37.5. Muse Spark 1.3 is 13.8x cheaper per token.
Thinking Machines Lab · Meta · Updated for 2026
Which is better?
Muse Spark 1.3 leads the overall LLM Stats Score 55.1 to 37.5, ranking #4 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, Muse Spark 1.3 is roughly 13.8x 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 Inkling
- 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 value its reported benchmark strengths — it wins 2 of 2 exact shared results
- cost matters — it's about 13.8x 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.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for Inkling · 11 for Muse Spark 1.3
Inkling outperforms in 0 benchmarks, while Muse Spark 1.3 is better at 2 benchmarks (GDPval-AA, 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, Inkling ($0.95/1M tokens) is 9.5x more expensive than Muse Spark 1.3 ($0.10/1M tokens).
For output processing, Inkling ($4.05/1M tokens) is 20.2x more expensive than Muse Spark 1.3 ($0.20/1M tokens).
In conclusion, Inkling is more expensive than Muse Spark 1.3.*
* 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 Inkling's 524,288 tokens. Muse Spark 1.3 can generate longer responses up to 943,718 tokens, while Inkling is limited to 524,288 tokens.
Input capabilities
Documented input modalities across available providers
Both Inkling and Muse Spark 1.3 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Inkling
Muse Spark 1.3
License
Usage and distribution terms
Inkling is licensed under Apache 2.0, 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.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Inkling was released on 2026-07-21, while Muse Spark 1.3 was released on 2026-09-02.
Muse Spark 1.3 is 1 month newer than Inkling.
Jul 21, 2026
1 months ago
Sep 2, 2026
1 weeks ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Inkling is available from DeepInfra. Muse Spark 1.3 is available from Meta Model API.
Inkling
Muse Spark 1.3
Outputs Comparison
Judge for yourself.
Run your own prompts against Inkling and Muse Spark 1.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Inkling vs Muse Spark 1.3.