GPT-6.1 Sol vs Muse Wonder
GPT-6.1 Sol and Muse Wonder are closely matched at 54.0 and 47.9 on the LLM Stats Score. GPT-6.1 Sol is 2.0x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
GPT-6.1 Sol and Muse Wonder are closely matched on the overall LLM Stats Score at 54.0 and 47.9.
In the 3 individual benchmarks reported for both models, GPT-6.1 Sol wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-6.1 Sol is roughly 2.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6.1 Sol also accepts a larger context window (1,050,000 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 GPT-6.1 Sol
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- cost matters — it's about 2.0x cheaper per token
- you process long inputs — it offers a 1,050,000 token context window
Choose Muse Wonder
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
17 reported for GPT-6.1 Sol · 16 for Muse Wonder
GPT-6.1 Sol outperforms in 2 benchmarks (GDP.pdf, HealthBench Professional), while Muse Wonder is better at 1 benchmark (DeepSWE 1.1).
GPT-6.1 Sol shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6.1 Sol ($2.00/1M tokens) is 2.0x cheaper than Muse Wonder ($4.00/1M tokens).
For output processing, GPT-6.1 Sol ($10.00/1M tokens) is 2.0x cheaper than Muse Wonder ($20.00/1M tokens).
In conclusion, Muse Wonder is more expensive than GPT-6.1 Sol.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6.1 Sol accepts 1,050,000 input tokens compared to Muse Wonder's 1,048,576 tokens. Only GPT-6.1 Sol specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Both GPT-6.1 Sol and Muse Wonder support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-6.1 Sol
Muse Wonder
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
GPT-6.1 Sol was released on 2026-09-29, while Muse Wonder was released on 2026-10-12.
Muse Wonder is 0 month newer than GPT-6.1 Sol.
Sep 29, 2026
1 weeks ago
Oct 12, 2026
-1 days ago
1w newerKnowledge Cutoff
When training data ends
GPT-6.1 Sol has a documented knowledge cutoff of 2026-04-30, while Muse Wonder's cutoff date is not specified.
We can confirm GPT-6.1 Sol's training data extends to 2026-04-30, but cannot make a direct comparison without Muse Wonder's cutoff date.
Apr 2026
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Provider Availability
GPT-6.1 Sol is available from OpenAI. Muse Wonder is available from Meta Model API.
GPT-6.1 Sol
Muse Wonder
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6.1 Sol and Muse Wonder side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6.1 Sol vs Muse Wonder.