Alternatives to Llama 3.3 70B Instruct

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

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

WorkloadLlama 3.3 70B Instruct $/MRecorded capabilities preservedRecorded capability losses
Balanced$0.201181
Summarise$0.148241
Chat$0.241171
Code gen$0.294161
Agentic$0.175212

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

Intelligence1274.1
Context window131K
Max output16K
Input modestext
Tool useyes
Extended reasoningno

Preserving recorded capabilities requires matching or beating these fields. Full record for Llama 3.3 70B Instruct, or check Llama 3.3 70B Instruct against the whole catalogue.

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.

#ModelIntelligence$/MHolds under
1DeepSeek V4.1 Flash DeepSeek1462.5 +188.4$0.182
  • Balanced −9%
  • Summarise −55%
  • Agentic −40%
2MiMo-V2.6-Flash Xiaomi1456.4 +182.3$0.175
  • Balanced −13%
  • Summarise −27%
  • Chat −36%
  • Code gen −28%
  • Agentic −55%
3Gemma 4 26B A4B Google1433.9 +159.8$0.127
  • Balanced −37%
  • Summarise −53%
  • Chat −38%
  • Code gen −30%
  • Agentic −54%
4DeepSeek V4 Flash 0423 DeepSeek1432.1 +158$0.113
  • Balanced −44%
  • Summarise −50%
  • Chat −57%
  • Code gen −53%
  • Agentic −65%
5MiMo-V2.5 Xiaomi1427.5 +153.4$0.175
  • Balanced −13%
  • Summarise −27%
  • Chat −36%
  • Code gen −28%
  • Agentic −55%
6Step 3.5 Flash StepFun1403 +128.9$0.150
  • Balanced −25%
  • Summarise −26%
  • Chat −25%
  • Code gen −25%
  • Agentic −26%
7Qwen3.5-Flash Qwen1397 +122.9$0.114
  • Balanced −43%
  • Summarise −50%
  • Chat −41%
  • Code gen −38%
  • Agentic −46%
8GPT-6 Luna OpenAI1391.5 +117.4$0.200
  • Balanced −1%
  • Summarise −36%
  • Chat −3%
  • Agentic −39%
9Qwen3 30B A3B Instruct 2507 Qwen1384.1 +110$0.143
  • Balanced −29%
  • Summarise −32%
  • Chat −28%
  • Code gen −27%
  • Agentic −30%
10gpt-oss-120b OpenAI1365.4 +91.3$0.065
  • Balanced −68%
  • Summarise −75%
  • Chat −64%
  • Code gen −61%
  • Agentic −71%
11Gemma 3 27B Google1357.8 +83.7$0.100
  • Balanced −50%
  • Summarise −43%
  • Chat −54%
  • Code gen −56%
  • Agentic −47%
12GLM 4.7 Flash Z.ai1350.9 +76.8$0.145
  • Balanced −28%
  • Summarise −58%
  • Chat −25%
  • Code gen −12%
  • Agentic −54%
13Qwen3 32B Qwen1340.1 +66$0.130
  • Balanced −35%
  • Summarise −39%
  • Chat −34%
  • Code gen −32%
  • Agentic −37%
14Gemma 3 12B Google1334.2 +60.1$0.075
  • Balanced −63%
  • Summarise −63%
  • Chat −63%
  • Code gen −63%
  • Agentic −63%
15GPT-5 Nano OpenAI1320 +45.9$0.138
  • Balanced −32%
  • Summarise −63%
  • Chat −27%
  • Code gen −13%
  • Agentic −57%
16Granite 4.2 8B IBM1317.8 +43.7$0.108
  • Balanced −47%
  • Summarise −62%
  • Chat −49%
  • Code gen −42%
  • Agentic −65%
17gpt-oss-20b OpenAI1287.7 +13.6$0.036
  • Balanced −82%
  • Summarise −87%
  • Chat −82%
  • Code gen −79%
  • Agentic −87%
18GPT-4.1 Nano OpenAI1284.8 +10.7$0.175
  • Balanced −13%
  • Summarise −37%
  • Chat −18%
  • Code gen −7%
  • Agentic −43%
19GLM 5.3 Flash Z.ai1469.6 +195.5$0.133 summarise
  • Summarise −10%
  • Agentic −25%
20Hy3 Tencent1440.7 +166.6$0.124 summarise
  • Summarise −17%
  • Agentic −24%
21Qwen3 235B A22B Instruct 2507 Qwen1419.3 +145.2$0.113 summarise
  • Summarise −24%
  • Agentic −9%
22Qwen3 Next 80B A3B Instruct Qwen1417.3 +143.2$0.132 summarise
  • Summarise −11%
23GLM 4.5 Air Z.ai1383.9 +109.8$0.136 summarise
  • Summarise −8%
24Qwen3 30B A3B Qwen1316.6 +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.

ModelIntelligence$/MHolds underRecorded capability loss
Gemma 3 4B Google1290.8 +16.7$0.063
  • Balanced −69%
  • Summarise −65%
  • Chat −71%
  • Code gen −73%
  • Agentic −67%
  • no tool use
GPT-4o-mini (2024-07-18) OpenAI1286.4 +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.
  • 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. Models with such an alternative are listed here.
Evidence & Ask