Standard Compute
Model comparison 2026

GPT-5.3-Codex vs Muse Spark Open

GPT-5.3-Codex
OpenAI · Balanced · Proprietary
$5.42/1M · 400K ctx
Muse Spark Open
Meta · Balanced · Open weights
$2.15/1M · 1.0M ctx

Community vote

Pick a winner in each dimension. You can change your vote any time.

Output Quality

Correctness and depth of what it produces

Agentic Ability

Tool calls, instruction-following, and multi-step tasks

Speed

Tokens per second and time-to-first-token

Value for Money

How much capability you get per dollar

Reliability

Consistent results: fewer refusals, loops and format breaks

Specs and pricing side by side

Spec
GPT-5.3-Codex
Muse Spark Open
Maker
OpenAI
Meta
Blended price / 1M
$5.42
$2.15
Input / output
$1.75 in · $14 out / 1M tokens
$1.25 in · $4.25 out / 1M tokens
Context window
400K
1.0M
Open weights
No
Yes
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
6.8
7.0
Agentic Ability
5.1
5.0
Speed
8.0
7.0
Value for Money
5.0
5.3
Reliability
8.4
8.0

Pricing and capabilities synced from the OpenRouter catalogue. Scores are editorial (0–10).

Verdict: GPT-5.3-Codex or Muse Spark Open?

Updated 2026-10-16

Choose GPT-5.3-Codex if you want existing Codex setups on an API key that still pin GPT-5.3-Codex. Choose Muse Spark Open if you want trying Meta's open-weight coding model through OpenRouter, or self-hosting it where code must stay on your own hardware.

In our editorial scoring, GPT-5.3-Codex leads in 3 of five dimensions (agentic ability, speed and reliability), while Muse Spark Open leads in 2. On price, GPT-5.3-Codex runs about $5.42 per 1M tokens (blended) and is proprietary; Muse Spark Open is about $2.15 and open-weight.

Where GPT-5.3-Codex falls short
  • Deprecated in Codex with ChatGPT sign-in
  • GPT-6.1 Sol scores far higher for about 20% more per request ($0.067 vs $0.055)
Full GPT-5.3-Codex breakdown →
Where Muse Spark Open falls short
  • No independent agent benchmark results yet; the published figures are Meta's own
  • Self-hosting needs at least 700 GB of GPU memory in NVFP4 (2 TB in BF16), per Meta's model card
Full Muse Spark Open breakdown →

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