Cheaper alternatives to GLM 4.7

Z.ai LMArena 1435.3 $0.738/M on a balanced workload prices as of 2026-08-28

2 models are both better and cheaper, giving up nothing.

Of the 133 models carrying both an independent score and a published price at the same delivery mode, 7 score at least as high as GLM 4.7 and cost no more under at least one workload. 2 match or beat it on every capability we hold — context, maximum output, input modes, tool use and extended reasoning. 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 GLM 4.7, it is not generated.

Where it holds

Workload	GLM 4.7 $/M	Better and cheaper	With a trade
Balanced	$0.738	2	3
Summarise	$0.376	2	4
Chat	$0.844	2	2
Code gen	$1.18	2	2
Agentic	$0.412	2	3

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	1435.3
Context window	205K
Max output	131K
Input modes	text
Tool use	yes
Extended reasoning	yes

A replacement has to clear every line above, not just the score. Full record for GLM 4.7.

Better and cheaper, nothing given up 2

Each of these matches or beats GLM 4.7 on context, maximum output, input modes, tool use and reasoning, scores at least as high, and costs no more.

#	Model	Intelligence	$/M	Holds under
1	MiMo-V2.5-Pro Xiaomi	1465 +29.7	$0.544	Balanced −26% Summarise −11% Chat −43% Code gen −44% Agentic −41%
2	Qwen3.7 Plus Qwen	1456.2 +20.9	$0.560	Balanced −24% Summarise −22% Chat −26% Code gen −26% Agentic −24%

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 tie	$0.152	Balanced −79% Summarise −76% Chat −79% Code gen −80% Agentic −75%	131K → 16K max output
Hy3 Tencent	1441.2 tie	$0.144	Balanced −80% Summarise −79% Chat −81% Code gen −81% Agentic −80%	131K → 128K max output
Qwen3.6 Plus Qwen	1436.8 tie	$0.731	Balanced −1%	131K → 66K max output
Gemini 3.7 Flash Google	1490.2 +54.9	$0.354 summarise	Summarise −6% Agentic −3%	131K → 66K max output
Gemini 3.5 Flash Lite Google	1436.5 tie	$0.333 summarise	Summarise −12%	131K → 66K max output

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.