Cheaper alternatives to GPT-5.6 Luna

OpenAI LMArena 1428.5 $0.450/M on a balanced workload prices as of 2026-08-28

Everything cheaper and higher-scoring gives something up.

Of the 133 models carrying both an independent score and a published price at the same delivery mode, 5 score at least as high as GPT-5.6 Luna and cost no more under at least one workload. 5 do not, and every row names what it drops.

Dominance is not a property of a model. It is a property of a model, a capability lens and a workload, and all three are named on every row. Scores are LMArena Elo, used under CC BY 4.0 from the official dataset; prices are blended per million tokens. A higher score is not a drop-in replacement.

This page is built from that comparison and nothing else. When no model is both better and cheaper than GPT-5.6 Luna, it is not generated.

Where it holds

Workload	GPT-5.6 Luna $/M	With a trade
Balanced	$0.450	4
Summarise	$0.199	4
Chat	$0.546	5
Code gen	$0.786	5
Agentic	$0.243	4

Workload mixes are defined on the methodology page. Cached input is priced at the cached rate, and reasoning tokens at the worse of the reasoning and output rates.

What you would be replacing

Intelligence	1428.5
Context window	1.1M
Max output	128K
Input modes	file, image, text
Tool use	yes
Extended reasoning	yes

A replacement has to clear every line above, not just the score. Full record for GPT-5.6 Luna.

Cheaper and higher-scoring, but you give something up 5

These score at least as high and cost no more on the two plotted axes, and lose something that is not on them. Read the last column before switching.

Model	Intelligence	$/M	Holds under	What you give up
Gemma 4 31B Google	1441.7 +13.2	$0.152	Balanced −66% Summarise −54% Chat −67% Code gen −70% Agentic −57%	1.1M → 262K context 128K → 16K max output no file input
Hy3 Tencent	1441.2 +12.7	$0.144	Balanced −68% Summarise −61% Chat −70% Code gen −71% Agentic −66%	1.1M → 262K context no file, image input
Gemma 4 26B A4B Google	1434.6 tie	$0.138	Balanced −69% Summarise −58% Chat −67% Code gen −70% Agentic −55%	1.1M → 262K context 128K → 16K max output no file input
DeepSeek V4 Flash 0423 DeepSeek	1431.6 tie	$0.101	Balanced −77% Summarise −66% Chat −83% Code gen −84% Agentic −78%	1.1M → 1.0M context no file, image input
MiMo-V2.5-Pro Xiaomi	1465 +36.5	$0.480 chat	Chat −12% Code gen −16%	no file, image input

What this compares, and what it leaves out

Quality is LMArena Elo, used under CC BY 4.0 from the official dataset. The 95% confidence interval on a difference between two scores is about ±10.68 points, so a gap smaller than that is marked tie rather than an improvement — see significance bands.
188 further models at this delivery mode carry a price but no independent score. They are absent from the comparison in both directions — unrated is not a zero, and an unmeasured model is neither an alternative nor a worse buy.
Retired models are never offered as an alternative, and a model only competes against its own delivery mode: batch trades latency for price, so it is not a like-for-like swap.
Nothing here measures latency, throughput, rate limits or how a model behaves on your prompts. Two models with the same index score are not interchangeable.
The models that nothing beats on both axes are on the value frontier, and every other model something cheaper beats is listed here.