---
title: "Cheaper alternatives to Qwen3 Next 80B A3B Instruct · Undominated.ai"
canonical: https://undominated.ai/alternatives/qwen__qwen3-next-80b-a3b-instruct/
description: "10 models score at least as high as Qwen3 Next 80B A3B Instruct and cost no more on a balanced workload. 1 give up nothing measurable; the other 9 name what they drop. Measured prices and independent scores."
---

# Cheaper alternatives to Qwen3 Next 80B A3B Instruct · Undominated.ai

> 10 models score at least as high as Qwen3 Next 80B A3B Instruct and cost no more on a balanced workload. 1 give up nothing measurable; the other 9 name what they drop. Measured prices and independent scores.

# Cheaper alternatives to Qwen3 Next 80B A3B Instruct

Qwen · LMArena 1418.6 · $0.350/M on a balanced workload · prices as of 2026-08-28

## 1 model is 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, **10** score at least as high as Qwen3 Next 80B A3B Instruct and cost no more under at least one workload. **1** matches or beats it on every capability we hold — context, maximum output, input modes, tool use and extended reasoning. **9** 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 Qwen3 Next 80B A3B Instruct, it is not generated.

## Where it holds

| Workload | Qwen3 Next 80B A3B Instruct $/M | Better and cheaper | With a trade |
| --- | --- | --- | --- |
| Balanced | $0.350 | 1 | 7 |
| Summarise | $0.141 | 1 | 5 |
| Chat | $0.491 | 1 | 8 |
| Code gen | $0.698 | 1 | 9 |
| Agentic | $0.232 | 1 | 6 |

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 | 1418.6 |
| --- | --- |
| Context window | 262K |
| Max output | 236K |
| Input modes | text |
| Tool use | yes |
| Extended reasoning | no |

A replacement has to clear every line above, not just the score. [Full record for Qwen3 Next 80B A3B Instruct](/models/qwen__qwen3-next-80b-a3b-instruct/).

## Better and cheaper, nothing given up 1

Each of these matches or beats Qwen3 Next 80B A3B Instruct 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 | DeepSeek V4 Flash 0423 DeepSeek | 1431.6 +13 | $0.101 | Balanced −71% Summarise −53% Chat −81% Code gen −82% Agentic −76% |

## Cheaper and higher-scoring, but you give something up 9

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 +23.1 | $0.152 | Balanced −56% Summarise −36% Chat −64% Code gen −66% Agentic −55% | 236K → 16K max output |
| Hy3 Tencent | 1441.2 +22.6 | $0.144 | Balanced −59% Summarise −45% Chat −67% Code gen −68% Agentic −64% | 236K → 128K max output |
| Gemma 4 26B A4B Google | 1434.6 +16 | $0.138 | Balanced −61% Summarise −41% Chat −64% Code gen −67% Agentic −52% | 236K → 16K max output |
| MiMo-V2.5 Xiaomi | 1427.3 tie | $0.175 | Balanced −50% Summarise −24% Chat −68% Code gen −69% Agentic −66% | 236K → 131K max output |
| DeepSeek V3.2 DeepSeek | 1424.6 tie | $0.290 | Balanced −17% Chat −45% Code gen −54% Agentic −14% | 262K → 164K context 236K → 147K max output |
| DeepSeek V3.2 Exp DeepSeek | 1424.4 tie | $0.305 | Balanced −13% Chat −34% Code gen −49% | 262K → 164K context 236K → 66K max output |
| Qwen3 235B A22B Instruct 2507 Qwen | 1419.3 tie | $0.205 | Balanced −41% Summarise −20% Chat −44% Code gen −48% Agentic −32% | 236K → 16K max output |
| MiMo-V2.5-Pro Xiaomi | 1465 +46.4 | $0.480 chat | Chat −2% Code gen −5% | 236K → 131K max output |
| DeepSeek V3.1 Terminus DeepSeek | 1419.6 tie | $0.697 code gen | Code gen under 1% less | 262K → 164K context 236K → 33K 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](/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/).