GPT-5.3 Codex vs Muse Spark Open
Muse Spark Open leads the LLM Stats Score 45.3 to 36.3. Muse Spark Open is 2.4x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
Muse Spark Open leads the overall LLM Stats Score 45.3 to 36.3, ranking #42 overall.
In the 1 individual benchmarks reported for both models, Muse Spark Open wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Muse Spark Open is roughly 2.4x 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 GPT-5.3 Codex
- you want predictable pricing at $1.75/M input and $14.00/M output
Choose Muse Spark Open
- overall performance matters — it scores 45.3 and ranks #42 on LLM Stats
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 2.4x 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 Oct 2026
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
6 reported for GPT-5.3 Codex · 17 for Muse Spark Open
GPT-5.3 Codex outperforms in 0 benchmarks, while Muse Spark Open is better at 1 benchmark (OSWorld-Verified).
Muse Spark Open 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, GPT-5.3 Codex ($1.75/1M tokens) is 1.4x more expensive than Muse Spark Open ($1.25/1M tokens).
For output processing, GPT-5.3 Codex ($14.00/1M tokens) is 3.3x more expensive than Muse Spark Open ($4.25/1M tokens).
In conclusion, GPT-5.3 Codex is more expensive than Muse Spark Open.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Spark Open accepts 1,048,576 input tokens compared to GPT-5.3 Codex's 400,000 tokens. Muse Spark Open can generate longer responses up to 1,048,576 tokens, while GPT-5.3 Codex is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-5.3 Codex and Muse Spark Open support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.3 Codex
Muse Spark Open
License
Usage and distribution terms
GPT-5.3 Codex is licensed under a proprietary license, while Muse Spark Open uses Muse Model License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Muse Model License
Open weights
Release Timeline
When each model was launched
GPT-5.3 Codex was released on 2026-02-05, while Muse Spark Open was released on 2026-10-15.
Muse Spark Open is 8 months newer than GPT-5.3 Codex.
Feb 5, 2026
8 months ago
Oct 15, 2026
1 weeks ago
8mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT-5.3 Codex is available from OpenAI. Muse Spark Open is available from Together.
GPT-5.3 Codex
Muse Spark Open
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.3 Codex and Muse Spark Open side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.3 Codex vs Muse Spark Open.