GPT-5.3-Codex vs Muse Spark Open
OpenAI · US | Meta · US · Updated June 2026
Quick verdict
Pick GPT-5.3-Codex for dedicated coding agent or cli and ide integration. Pick Muse Spark Open for meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input or artificial analysis intelligence index of 39, first among us open-weight models. Choose Muse Spark Open if you need self-hosting or data privacy; GPT-5.3-Codex if you want a managed API.
GPT-5.3-Codex (OpenAI) and Muse Spark Open (Meta) are two of the models people most often weigh against each other in 2026. GPT-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. Muse Spark Open is meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Cost model: Muse Spark Open ships open weights you can self-host (hardware cost only, no per-token fee), while GPT-5.3-Codex is API-metered at $1.75/$14 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
- ▸Context window: Muse Spark Open holds 2.5× more — 1M tokens (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Muse Spark Open is the newer model by about 8 months (released October 15, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | GPT-5.3-Codex | Muse Spark Open |
|---|---|---|
| Provider | OpenAI (US) | Meta (US) |
| Released | February 5, 2026 | October 15, 2026 |
| Context window | 400K (~600 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | $1.75/$14 per 1M tokens | Open weight (self-host / free) |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, code | text, image, video, audio, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Dedicated coding agent
GPT-5.3-Codex
GPT-5.3-Codex lists dedicated coding agent among its strengths; Muse Spark Open does not.
CLI and IDE integration
GPT-5.3-Codex
GPT-5.3-Codex lists cLI and IDE integration among its strengths; Muse Spark Open does not.
Autonomous software tasks
GPT-5.3-Codex
GPT-5.3-Codex lists autonomous software tasks among its strengths; Muse Spark Open does not.
Meta's first open-weight Muse model - 816B-parameter MoE with 42B active, accepting text, image, video and audio input
Muse Spark Open
Open weights make this possible at all — GPT-5.3-Codex is API-only, so it cannot leave the vendor's servers.
Artificial Analysis Intelligence Index of 39, first among US open-weight models
Muse Spark Open
Meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License — and it carries the larger 1M tokens context.
About 143 output tokens/sec; up to 128K output tokens
Muse Spark Open
Its 1M tokens window holds about 2.5× more than GPT-5.3-Codex's 400K in a single prompt.
Lowest cost at scale
Muse Spark Open
Its weights are open, so at volume you pay for your own hardware instead of GPT-5.3-Codex's $1.75/$14 per 1M tokens.
Largest single-prompt input
Muse Spark Open
Its 1M tokens window is about 2.5× larger than GPT-5.3-Codex's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Muse Spark Open
At Open weight (self-host / free) it undercuts GPT-5.3-Codex, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Spark Open
Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Muse Spark Open
Open weights let you run it on your own hardware; GPT-5.3-Codex is API-only.
Anyone whose priority is dedicated coding agent
→ GPT-5.3-Codex
It is specifically built for that.
Anyone whose priority is meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input
→ Muse Spark Open
That is its strongest area.
GPT-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released February 5, 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs are real: coding-specialized, narrower general use, and retired in favor of GPT-5.5 Codex. At $1.75 in / $14 out per million tokens, it sits in the mid price band.
Muse Spark Open: where it fits
Meta's October 15, 2026 open-weight Muse Spark - an 816B/42B-active multimodal MoE with a 1M context under a gated Muse Model License. Released October 15, 2026 by Meta, it is built for meta's first open-weight Muse model - 816B-parameter MoE with 42B active, accepting text, image, video and audio input, artificial Analysis Intelligence Index of 39, first among US open-weight models, and about 143 output tokens/sec; up to 128K output tokens.
Its trade-offs: weakest of the three Muse models (Wonder Full scores 56, Wonder 52), muse Model License: attribution required and a revenue threshold (reported as about $20M; check the license text) before a separate license is needed, and needs about 1 TB of memory at 4-bit; no first-party per-token price confirmed. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
The defining split here is open vs. closed. Muse Spark Open gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.3-Codex gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both GPT-5.3-Codex and Muse Spark Open without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is GPT-5.3-Codex or Muse Spark Open better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, GPT-5.3-Codex leans toward dedicated coding agent while Muse Spark Open leans toward meta's first open-weight muse model - 816b-parameter moe with 42b active, accepting text, image, video and audio input, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.3-Codex or Muse Spark Open?
Muse Spark Open is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.3-Codex is API-metered at $1.75/$14 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Muse Spark Open — 1M tokens vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.3-Codex and Muse Spark Open together?
Yes — a multi-model platform like LumiChats gives you GPT-5.3-Codex, Muse Spark Open and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, GPT-5.3-Codex or Muse Spark Open?
Muse Spark Open — released October 15, 2026, about 8 months after GPT-5.3-Codex.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.