---
title: "Compare alternatives to Llama 3.3 70B Instruct · Undominated.ai"
canonical: https://undominated.ai/alternatives/meta-llama__llama-3.3-70b-instruct/
description: "26 alternatives score at least as high as Llama 3.3 70B Instruct and cost no more under at least one listed workload. 24 preserve recorded capabilities; 2 have named trade-offs."
---

# Compare alternatives to Llama 3.3 70B Instruct · Undominated.ai

> 26 alternatives score at least as high as Llama 3.3 70B Instruct and cost no more under at least one listed workload. 24 preserve recorded capabilities; 2 have named trade-offs.

# Alternatives to Llama 3.3 70B Instruct

Meta · LMArena 1274.1 · $0.201/M on a balanced workload · prices as of 2026-10-06

 [Compare models](https://undominated.ai/compare/) Comparison context

Choose up to three standard models in Compare.

Requirements and prompt length apply in Compare. This page keeps its stated price basis and workload controls.

## 24 models are higher-scoring or cheaper, with neither dimension worse.

Of the 144 models carrying both an independent score and a published price at the same delivery mode, **26** score at least as high as Llama 3.3 70B Instruct and cost no more under at least one listed workload, with at least one of those dimensions improved. **24** match or beat its recorded context, maximum output, input modes, tool use and extended reasoning. **2** have a recorded capability loss, named on every row.

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 only while a candidate improves score or price without worsening the other under a listed workload. When that comparison no longer holds, it is not generated.

## Where it holds

| Workload | Llama 3.3 70B Instruct $/M | Recorded capabilities preserved | Recorded capability losses |
| --- | --- | --- | --- |
| Balanced | $0.201 | 18 | 1 |
| Summarise | $0.148 | 24 | 1 |
| Chat | $0.241 | 17 | 1 |
| Code gen | $0.294 | 16 | 1 |
| Agentic | $0.175 | 21 | 2 |

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 | 1274.1 |
| --- | --- |
| Context window | 131K |
| Max output | 16K |
| Input modes | text |
| Tool use | yes |
| Extended reasoning | no |

Preserving recorded capabilities requires matching or beating these fields. [Full record for Llama 3.3 70B Instruct](/models/meta-llama__llama-3.3-70b-instruct/), or [check Llama 3.3 70B Instruct against the whole catalogue](/check/meta-llama__llama-3.3-70b-instruct/).

## Recorded capabilities preserved 24

Each option has a higher score or a lower price, with neither dimension worse under the listed workloads. It matches or beats Llama 3.3 70B Instruct on recorded context, maximum output, input modes, tool use and extended reasoning.

| # | Model | Intelligence | $/M | Holds under |
| --- | --- | --- | --- | --- |
| 1 | [DeepSeek V4.1 Flash](/models/deepseek__deepseek-v4.1-flash/) DeepSeek | 1462.5 +188.4 | $0.182 | Balanced −9% Summarise −55% Agentic −40% |
| 2 | [MiMo-V2.6-Flash](/models/xiaomi__mimo-v2.6-flash/) Xiaomi | 1456.4 +182.3 | $0.175 | Balanced −13% Summarise −27% Chat −36% Code gen −28% Agentic −55% |
| 3 | [Gemma 4 26B A4B](/models/google__gemma-4-26b-a4b-it/) Google | 1433.9 +159.8 | $0.127 | Balanced −37% Summarise −53% Chat −38% Code gen −30% Agentic −54% |
| 4 | [DeepSeek V4 Flash 0423](/models/deepseek__deepseek-v4-flash/) DeepSeek | 1432.1 +158 | $0.113 | Balanced −44% Summarise −50% Chat −57% Code gen −53% Agentic −65% |
| 5 | [MiMo-V2.5](/models/xiaomi__mimo-v2.5/) Xiaomi | 1427.5 +153.4 | $0.175 | Balanced −13% Summarise −27% Chat −36% Code gen −28% Agentic −55% |
| 6 | [Step 3.5 Flash](/models/stepfun__step-3.5-flash/) StepFun | 1403 +128.9 | $0.150 | Balanced −25% Summarise −26% Chat −25% Code gen −25% Agentic −26% |
| 7 | [Qwen3.5-Flash](/models/qwen__qwen3.5-flash-02-23/) Qwen | 1397 +122.9 | $0.114 | Balanced −43% Summarise −50% Chat −41% Code gen −38% Agentic −46% |
| 8 | [GPT-6 Luna](/models/openai__gpt-6-luna/) OpenAI | 1391.5 +117.4 | $0.200 | Balanced −1% Summarise −36% Chat −3% Agentic −39% |
| 9 | [Qwen3 30B A3B Instruct 2507](/models/qwen__qwen3-30b-a3b-instruct-2507/) Qwen | 1384.1 +110 | $0.143 | Balanced −29% Summarise −32% Chat −28% Code gen −27% Agentic −30% |
| 10 | [gpt-oss-120b](/models/openai__gpt-oss-120b/) OpenAI | 1365.4 +91.3 | $0.065 | Balanced −68% Summarise −75% Chat −64% Code gen −61% Agentic −71% |
| 11 | [Gemma 3 27B](/models/google__gemma-3-27b-it/) Google | 1357.8 +83.7 | $0.100 | Balanced −50% Summarise −43% Chat −54% Code gen −56% Agentic −47% |
| 12 | [GLM 4.7 Flash](/models/z-ai__glm-4.7-flash/) Z.ai | 1350.9 +76.8 | $0.145 | Balanced −28% Summarise −58% Chat −25% Code gen −12% Agentic −54% |
| 13 | [Qwen3 32B](/models/qwen__qwen3-32b/) Qwen | 1340.1 +66 | $0.130 | Balanced −35% Summarise −39% Chat −34% Code gen −32% Agentic −37% |
| 14 | [Gemma 3 12B](/models/google__gemma-3-12b-it/) Google | 1334.2 +60.1 | $0.075 | Balanced −63% Summarise −63% Chat −63% Code gen −63% Agentic −63% |
| 15 | [GPT-5 Nano](/models/openai__gpt-5-nano/) OpenAI | 1320 +45.9 | $0.138 | Balanced −32% Summarise −63% Chat −27% Code gen −13% Agentic −57% |
| 16 | [Granite 4.2 8B](/models/ibm-granite__granite-4.2-8b/) IBM | 1317.8 +43.7 | $0.108 | Balanced −47% Summarise −62% Chat −49% Code gen −42% Agentic −65% |
| 17 | [gpt-oss-20b](/models/openai__gpt-oss-20b/) OpenAI | 1287.7 +13.6 | $0.036 | Balanced −82% Summarise −87% Chat −82% Code gen −79% Agentic −87% |
| 18 | [GPT-4.1 Nano](/models/openai__gpt-4.1-nano/) OpenAI | 1284.8 +10.7 | $0.175 | Balanced −13% Summarise −37% Chat −18% Code gen −7% Agentic −43% |
| 19 | [GLM 5.3 Flash](/models/z-ai__glm-5.3-flash/) Z.ai | 1469.6 +195.5 | $0.133 summarise | Summarise −10% Agentic −25% |
| 20 | [Hy3](/models/tencent__hy3/) Tencent | 1440.7 +166.6 | $0.124 summarise | Summarise −17% Agentic −24% |
| 21 | [Qwen3 235B A22B Instruct 2507](/models/qwen__qwen3-235b-a22b-2507/) Qwen | 1419.3 +145.2 | $0.113 summarise | Summarise −24% Agentic −9% |
| 22 | [Qwen3 Next 80B A3B Instruct](/models/qwen__qwen3-next-80b-a3b-instruct/) Qwen | 1417.3 +143.2 | $0.132 summarise | Summarise −11% |
| 23 | [GLM 4.5 Air](/models/z-ai__glm-4.5-air/) Z.ai | 1383.9 +109.8 | $0.136 summarise | Summarise −8% |
| 24 | [Qwen3 30B A3B](/models/qwen__qwen3-30b-a3b/) Qwen | 1316.6 +42.5 | $0.139 summarise | Summarise −6% |

## Alternatives with recorded capability losses 2

These improve score or price without worsening the other under the listed workloads, but reduce at least one recorded capability. Read the last column before switching.

| Model | Intelligence | $/M | Holds under | Recorded capability loss |
| --- | --- | --- | --- | --- |
| [Gemma 3 4B](/models/google__gemma-3-4b-it/) Google | 1290.8 +16.7 | $0.063 | Balanced −69% Summarise −65% Chat −71% Code gen −73% Agentic −67% | no tool use |
| [GPT-4o-mini (2024-07-18)](/models/openai__gpt-4o-mini-2024-07-18/) OpenAI | 1286.4 +12.3 | $0.173 agentic | Agentic −1% | 131K → 128K context |

## 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 ±10.47 points, so a gap smaller than that is marked *tie* rather than an improvement — see [significance bands](/significance/).
 - 204 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.
 - Models with no higher-scoring or cheaper alternative that is no worse on the other axis are on the [value frontier](/frontier/). Models with such an alternative are [listed here](/alternatives/).

## Continue your investigation

 - [Check requirements](/check/)
- [Compare exact differences](/compare/)
- [Set a quality floor](/cheapest-at/)
- [Inspect tier boundaries](/cliffs/)