Model Comparison 2026

GPT-5.3-Codex vs GPT-5.6 Luna

GPT-5.3-Codex
OpenAI · Balanced · Proprietary
$5.42/1M · 400K ctx
GPT-5.6 Luna
OpenAI · Budget · Proprietary
$2.50/1M · 1.1M ctx

Community Vote

Pick a winner in each dimension — change your vote anytime.

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 $
How much capability you get per dollar
Reliability
Consistent results — fewer refusals, loops, and format breaks

Specs & Pricing, Side by Side

Spec
GPT-5.3-Codex
Luna
Maker
OpenAI
OpenAI
Blended price / 1M
$5.42
$2.50
Input / output
$1.75 in · $14 out / 1M tokens
$1.00 in · $6.00 out / 1M tokens
Context window
400K
1.1M
Open weights
No
No
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
8.8
8.4
Agentic Ability
9.3
8.3
Speed
7.8
9.3
Value for $
7.8
9.0
Reliability
8.7
9.1

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

Verdict: GPT-5.3-Codex or Luna?

Updated 2026-07-17

Choose GPT-5.3-Codex if you want codex CLI users and dedicated coding agents. Choose GPT-5.6 Luna if you want cheap, fast subtasks, routing, and subagents in OpenAI-based stacks.

In our editorial scoring, GPT-5.6 Luna leads in 3 of five dimensions (speed, value for $ and reliability), while GPT-5.3-Codex leads in 2. On price, GPT-5.3-Codex runs about $5.42 per 1M tokens (blended) and is proprietary; GPT-5.6 Luna is about $2.50 and proprietary.

Where GPT-5.3-Codex falls short
  • Narrower than a general flagship outside coding
  • Mid-tier pricing
Full GPT-5.3-Codex breakdown →
Where Luna falls short
  • Clear quality step below Terra and Sol
  • Very new — behavior under long agent chains still settling
Full Luna breakdown →

The model is half the story — the agent is the other half

The model picks the moves; the agent runs the loop, the tools, and the guardrails. Once you've chosen a model, see which agent gets the most out of it.

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