Model Comparison 2026

GPT-5.6 Luna vs Qwen3 235B A22B

GPT-5.6 Luna
OpenAI · Budget · Proprietary
$2.50/1M · 1.1M ctx
Qwen3 235B A22B
Alibaba (Qwen) · Budget · Open weights
$0.23/1M · 262K 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
Luna
Qwen3 235B
Maker
OpenAI
Alibaba (Qwen)
Blended price / 1M
$2.50
$0.23
Input / output
$1.00 in · $6.00 out / 1M tokens
$0.09 in · $0.55 out / 1M tokens
Context window
1.1M
262K
Open weights
No
Yes
Tool use
Yes
Yes
Reasoning
Yes
No
Output Quality
8.4
8.0
Agentic Ability
8.3
8.0
Speed
9.3
8.2
Value for $
9.0
10.0
Reliability
9.1
8.8

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

Verdict: Luna or Qwen3 235B?

Updated 2026-07-17

Choose GPT-5.6 Luna if you want cheap, fast subtasks, routing, and subagents in OpenAI-based stacks. Choose Qwen3 235B A22B if you want self-hosted or ultra-cheap open-weight agents.

In our editorial scoring, GPT-5.6 Luna leads in 4 of five dimensions (output quality, agentic ability, speed and reliability), while Qwen3 235B A22B leads in 1. On price, GPT-5.6 Luna runs about $2.50 per 1M tokens (blended) and is proprietary; Qwen3 235B A22B is about $0.23 and open-weight.

Where Luna falls short
  • Clear quality step below Terra and Sol
  • Very new — behavior under long agent chains still settling
Full Luna breakdown →
Where Qwen3 235B falls short
  • Behind frontier models on quality
  • Needs real GPUs to self-host well
Full Qwen3 235B breakdown →

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