---
title: "Cheaper alternatives to GLM 4.6V · Undominated.ai"
canonical: https://undominated.ai/alternatives/z-ai__glm-4.6v/
description: "18 models score at least as high as GLM 4.6V and cost no more on a balanced workload. 3 give up nothing measurable; the other 15 name what they drop. Measured prices and independent scores."
---

# Cheaper alternatives to GLM 4.6V · Undominated.ai

> 18 models score at least as high as GLM 4.6V and cost no more on a balanced workload. 3 give up nothing measurable; the other 15 name what they drop. Measured prices and independent scores.

# Cheaper alternatives to GLM 4.6V

Z.ai · LMArena 1374.7 · $0.450/M on a balanced workload · prices as of 2026-08-28

## 3 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, **18** score at least as high as GLM 4.6V and cost no more under at least one workload. **3** match or beat it on every capability we hold — context, maximum output, input modes, tool use and extended reasoning. **15** 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 4.6V, it is not generated.

## Where it holds

| Workload | GLM 4.6V $/M | Better and cheaper | With a trade |
| --- | --- | --- | --- |
| Balanced | $0.450 | 2 | 14 |
| Summarise | $0.260 | 3 | 12 |
| Chat | $0.467 | 2 | 11 |
| Code gen | $0.640 | 2 | 11 |
| Agentic | $0.244 | 2 | 13 |

Workload mixes are defined on the [methodology page](/methodology/). 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 | 1374.7 |
| --- | --- |
| Context window | 131K |
| Max output | 33K |
| Input modes | image, text, video |
| Tool use | yes |
| Extended reasoning | yes |

A replacement has to clear every line above, not just the score. [Full record for GLM 4.6V](/models/z-ai__glm-4.6v/).

## Better and cheaper, nothing given up 3

Each of these matches or beats GLM 4.6V 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 Xiaomi | 1427.3 +52.6 | $0.175 | Balanced −61% Summarise −59% Chat −67% Code gen −67% Agentic −67% |
| 2 | Qwen3.5-Flash Qwen | 1397.6 +22.9 | $0.114 | Balanced −75% Summarise −71% Chat −69% Code gen −72% Agentic −61% |
| 3 | Gemini 3.1 Flash Lite Preview Google | 1414.8 +40.1 | $0.248 summarise | Summarise −5% |

## Cheaper and higher-scoring, but you give something up 15

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 +67 | $0.152 | Balanced −66% Summarise −65% Chat −62% Code gen −63% Agentic −58% | 33K → 16K max output |
| Hy3 Tencent | 1441.2 +66.5 | $0.144 | Balanced −68% Summarise −70% Chat −65% Code gen −65% Agentic −66% | no image, video input |
| Gemma 4 26B A4B Google | 1434.6 +59.9 | $0.138 | Balanced −69% Summarise −68% Chat −62% Code gen −64% Agentic −55% | 33K → 16K max output |
| DeepSeek V4 Flash 0423 DeepSeek | 1431.6 +56.9 | $0.101 | Balanced −77% Summarise −74% Chat −80% Code gen −81% Agentic −78% | no image, video input |
| GPT-5.6 Luna OpenAI | 1428.5 +53.8 | $0.450 | Balanced same price Summarise −24% Agentic −1% | no video input |
| DeepSeek V3.2 DeepSeek | 1424.6 +49.9 | $0.290 | Balanced −36% Summarise −12% Chat −42% Code gen −50% Agentic −18% | no image, video input |
| DeepSeek V3.2 Exp DeepSeek | 1424.4 +49.7 | $0.305 | Balanced −32% Chat −30% Code gen −45% | no image, video input |
| Qwen3 235B A22B Instruct 2507 Qwen | 1419.3 +44.6 | $0.205 | Balanced −54% Summarise −57% Chat −41% Code gen −43% Agentic −35% | 33K → 16K max output no image, video input no extended reasoning |
| Qwen3 Next 80B A3B Instruct Qwen | 1418.6 +43.9 | $0.350 | Balanced −22% Summarise −46% Agentic −5% | no image, video input no extended reasoning |
| Step 3.5 Flash StepFun | 1403.8 +29.1 | $0.150 | Balanced −67% Summarise −58% Chat −61% Code gen −66% Agentic −47% | no image, video input |
| Qwen3 30B A3B Instruct 2507 Qwen | 1384.3 tie | $0.084 | Balanced −81% Summarise −79% Chat −77% Code gen −79% Agentic −71% | 33K → 32K max output no image, video input no extended reasoning |
| GLM 4.5 Air Z.ai | 1382.8 tie | $0.310 | Balanced −31% Summarise −48% Chat −17% Code gen −14% Agentic −28% | no image, video input |
| Solar Pro 4 Upstage | 1376.2 tie | $0.052 | Balanced −88% Summarise −89% Chat −87% Code gen −87% Agentic −88% | no image, video input |
| DeepSeek V3 0324 DeepSeek | 1375 tie | $0.438 | Balanced −3% | no image, video input no extended reasoning |
| MiMo-V2.5-Pro Xiaomi | 1465 +90.3 | $0.244 agentic | Agentic under 1% less | no image, video 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](/significance/).
 - 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](/frontier/), and every other model something cheaper beats is [listed here](/alternatives/).