---
title: "Cheaper alternatives to Llama 3.2 3B Instruct · Undominated.ai"
canonical: https://undominated.ai/alternatives/meta-llama__llama-3.2-3b-instruct/
description: "17 models score at least as high as Llama 3.2 3B Instruct and cost no more on a balanced workload. 9 give up nothing measurable; the other 8 name what they drop. Measured prices and independent scores."
---

# Cheaper alternatives to Llama 3.2 3B Instruct · Undominated.ai

> 17 models score at least as high as Llama 3.2 3B Instruct and cost no more on a balanced workload. 9 give up nothing measurable; the other 8 name what they drop. Measured prices and independent scores.

# Cheaper alternatives to Llama 3.2 3B Instruct

Meta · LMArena 1109.7 · $0.120/M on a balanced workload · prices as of 2026-08-28

## 9 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, **17** score at least as high as Llama 3.2 3B Instruct and cost no more under at least one workload. **9** match or beat it on every capability we hold — context, maximum output, input modes, tool use and extended reasoning. **8** 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 Llama 3.2 3B Instruct, it is not generated.

## Where it holds

| Workload | Llama 3.2 3B Instruct $/M | Better and cheaper | With a trade |
| --- | --- | --- | --- |
| Balanced | $0.120 | 6 | 6 |
| Summarise | $0.064 | 6 | 5 |
| Chat | $0.162 | 7 | 7 |
| Code gen | $0.218 | 7 | 7 |
| Agentic | $0.092 | 9 | 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 | 1109.7 |
| --- | --- |
| Context window | 131K |
| Max output | 118K |
| Input modes | text |
| Tool use | no |
| Extended reasoning | no |

A replacement has to clear every line above, not just the score. [Full record for Llama 3.2 3B Instruct](/models/meta-llama__llama-3.2-3b-instruct/).

## Better and cheaper, nothing given up 9

Each of these matches or beats Llama 3.2 3B 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 +321.9 | $0.101 | Balanced −16% Chat −42% Code gen −43% Agentic −41% |
| 2 | Solar Pro 4 Upstage | 1376.2 +266.5 | $0.052 | Balanced −56% Summarise −57% Chat −64% Code gen −62% Agentic −68% |
| 3 | gpt-oss-120b OpenAI | 1365.6 +255.9 | $0.070 | Balanced −41% Summarise −32% Chat −44% Code gen −46% Agentic −38% |
| 4 | Granite 4.1 8B IBM | 1291.6 +181.9 | $0.063 | Balanced −48% Summarise −18% Chat −57% Code gen −63% Agentic −37% |
| 5 | gpt-oss-20b OpenAI | 1287.8 +178.1 | $0.055 | Balanced −54% Summarise −45% Chat −57% Code gen −59% Agentic −51% |
| 6 | Llama 3.1 8B Instruct Meta | 1186.7 +77 | $0.058 | Balanced −52% Summarise −31% Chat −66% Code gen −70% Agentic −57% |
| 7 | Hy3 Tencent | 1441.2 +331.5 | $0.083 agentic | Agentic −10% |
| 8 | MiMo-V2.5 Xiaomi | 1427.3 +317.6 | $0.155 chat | Chat −4% Code gen −2% Agentic −14% |
| 9 | GPT-5 Nano OpenAI | 1320.3 +210.6 | $0.055 summarise | Summarise −15% Agentic −18% |

## Cheaper and higher-scoring, but you give something up 8

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 |
| --- | --- | --- | --- | --- |
| Qwen3.5-Flash Qwen | 1397.6 +287.9 | $0.114 | Balanced −5% Chat −12% Code gen −17% | 118K → 66K max output |
| Qwen3 30B A3B Instruct 2507 Qwen | 1384.3 +274.6 | $0.084 | Balanced −30% Summarise −13% Chat −35% Code gen −38% Agentic −24% | 118K → 32K max output |
| Gemma 3 12B Google | 1334.2 +224.5 | $0.075 | Balanced −38% Summarise −14% Chat −44% Code gen −50% Agentic −29% | 118K → 16K max output |
| Gemma 3 4B Google | 1290.8 +181.1 | $0.063 | Balanced −48% Summarise −18% Chat −57% Code gen −63% Agentic −37% | 118K → 16K max output |
| Mistral Small 3 Mistral | 1233.6 +123.9 | $0.058 | Balanced −52% Summarise −20% Chat −62% Code gen −69% Agentic −41% | 131K → 33K context 118K → 16K max output |
| Phi 4 Microsoft | 1216.8 +107.1 | $0.087 | Balanced −27% Chat −40% Code gen −49% Agentic −12% | 131K → 16K context 118K → 15K max output |
| GLM 4.7 Flash Z.ai | 1352.9 +243.2 | $0.063 summarise | Summarise −2% Agentic −12% | 118K → 16K max output |
| Qwen3 32B Qwen | 1340.1 +230.4 | $0.160 chat | Chat −1% Code gen −8% | 118K → 16K 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/).