Cheaper alternatives to Qwen2.5 72B Instruct

Qwen LMArena 1269.1 $0.370/M on a balanced workload prices as of 2026-08-28

50 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, 53 score at least as high as Qwen2.5 72B Instruct and cost no more under at least one workload. 50 match or beat it on every capability we hold — context, maximum output, input modes, tool use and extended reasoning. 3 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 Qwen2.5 72B Instruct, it is not generated.

Where it holds

WorkloadQwen2.5 72B Instruct $/MBetter and cheaperWith a trade
Balanced$0.370252
Summarise$0.362493
Chat$0.376232
Code gen$0.384222
Agentic$0.366402

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

Intelligence1269.1
Context window33K
Max output16K
Input modestext
Tool useyes
Extended reasoningno

A replacement has to clear every line above, not just the score. Full record for Qwen2.5 72B Instruct.

Better and cheaper, nothing given up 50

Each of these matches or beats Qwen2.5 72B Instruct on context, maximum output, input modes, tool use and reasoning, scores at least as high, and costs no more.

#ModelIntelligence$/MHolds under
1Gemma 4 31B Google1441.7 +172.6$0.152
  • Balanced −59%
  • Summarise −75%
  • Chat −53%
  • Code gen −38%
  • Agentic −72%
2Hy3 Tencent1441.2 +172.1$0.144
  • Balanced −61%
  • Summarise −79%
  • Chat −57%
  • Code gen −41%
  • Agentic −77%
3Gemma 4 26B A4B Google1434.6 +165.5$0.138
  • Balanced −63%
  • Summarise −77%
  • Chat −53%
  • Code gen −40%
  • Agentic −70%
4DeepSeek V4 Flash 0423 DeepSeek1431.6 +162.5$0.101
  • Balanced −73%
  • Summarise −82%
  • Chat −75%
  • Code gen −68%
  • Agentic −85%
5MiMo-V2.5 Xiaomi1427.3 +158.2$0.175
  • Balanced −53%
  • Summarise −70%
  • Chat −59%
  • Code gen −45%
  • Agentic −78%
6DeepSeek V3.2 DeepSeek1424.6 +155.5$0.290
  • Balanced −22%
  • Summarise −37%
  • Chat −28%
  • Code gen −16%
  • Agentic −45%
7DeepSeek V3.2 Exp DeepSeek1424.4 +155.3$0.305
  • Balanced −18%
  • Summarise −23%
  • Chat −13%
  • Code gen −8%
  • Agentic −20%
8Qwen3 235B A22B Instruct 2507 Qwen1419.3 +150.2$0.205
  • Balanced −45%
  • Summarise −69%
  • Chat −27%
  • Code gen −5%
  • Agentic −57%
9Qwen3 Next 80B A3B Instruct Qwen1418.6 +149.5$0.350
  • Balanced −5%
  • Summarise −61%
  • Agentic −37%
10Step 3.5 Flash StepFun1403.8 +134.7$0.150
  • Balanced −59%
  • Summarise −70%
  • Chat −52%
  • Code gen −43%
  • Agentic −64%
11Qwen3.5-Flash Qwen1397.6 +128.5$0.114
  • Balanced −69%
  • Summarise −79%
  • Chat −62%
  • Code gen −53%
  • Agentic −74%
12Qwen3 30B A3B Instruct 2507 Qwen1384.3 +115.2$0.084
  • Balanced −77%
  • Summarise −85%
  • Chat −72%
  • Code gen −65%
  • Agentic −81%
13Solar Pro 4 Upstage1376.2 +107.1$0.052
  • Balanced −86%
  • Summarise −92%
  • Chat −84%
  • Code gen −79%
  • Agentic −92%
14GLM 4.5 Air Z.ai1382.8 +113.7$0.310
  • Balanced −16%
  • Summarise −62%
  • Agentic −52%
15gpt-oss-120b OpenAI1365.6 +96.5$0.070
  • Balanced −81%
  • Summarise −88%
  • Chat −76%
  • Code gen −70%
  • Agentic −84%
16Gemma 3 27B Google1358.3 +89.2$0.172
  • Balanced −53%
  • Summarise −76%
  • Chat −43%
  • Code gen −22%
  • Agentic −69%
17GLM 4.7 Flash Z.ai1352.9 +83.8$0.145
  • Balanced −61%
  • Summarise −83%
  • Chat −52%
  • Code gen −32%
  • Agentic −78%
18Qwen3 32B Qwen1340.1 +71$0.130
  • Balanced −65%
  • Summarise −75%
  • Chat −57%
  • Code gen −48%
  • Agentic −70%
19Gemma 3 12B Google1334.2 +65.1$0.075
  • Balanced −80%
  • Summarise −85%
  • Chat −76%
  • Code gen −71%
  • Agentic −82%
20GPT-5 Nano OpenAI1320.3 +51.2$0.138
  • Balanced −63%
  • Summarise −85%
  • Chat −53%
  • Code gen −33%
  • Agentic −79%
21Qwen3 30B A3B Qwen1316.9 +47.8$0.215
  • Balanced −42%
  • Summarise −62%
  • Chat −28%
  • Code gen −9%
  • Agentic −52%
22Granite 4.1 8B IBM1291.6 +22.5$0.063
  • Balanced −83%
  • Summarise −85%
  • Chat −81%
  • Code gen −79%
  • Agentic −84%
23gpt-oss-20b OpenAI1287.8 +18.7$0.055
  • Balanced −85%
  • Summarise −90%
  • Chat −81%
  • Code gen −77%
  • Agentic −88%
24GPT-4.1 Nano OpenAI1284.8 +15.7$0.175
  • Balanced −53%
  • Summarise −74%
  • Chat −47%
  • Code gen −29%
  • Agentic −73%
25GPT-4o-mini (2024-07-18) OpenAI1286.6 +17.5$0.263
  • Balanced −29%
  • Summarise −58%
  • Chat −18%
  • Agentic −53%
26Gemini 3.7 Flash Google1490.2 +221.1$0.354 summarise
  • Summarise −2%
27MiMo-V2.5-Pro Xiaomi1465 +195.9$0.334 summarise
  • Summarise −8%
  • Agentic −33%
28Qwen3.7 Plus Qwen1456.2 +187.1$0.295 summarise
  • Summarise −19%
  • Agentic −15%
29Gemini 3.5 Flash Lite Google1436.5 +167.4$0.333 summarise
  • Summarise −8%
30MiniMax M3 MiniMax1434.8 +165.7$0.277 summarise
  • Summarise −24%
  • Agentic −20%
31GPT-5.6 Luna OpenAI1428.5 +159.4$0.199 summarise
  • Summarise −45%
  • Agentic −34%
32Qwen3 VL 235B A22B Instruct Qwen1420.9 +151.8$0.263 summarise
  • Summarise −27%
33DeepSeek V3.1 Terminus DeepSeek1419.6 +150.5$0.268 summarise
  • Summarise −26%
  • Agentic −18%
34Qwen3.5-122B-A10B Qwen1417.9 +148.8$0.351 summarise
  • Summarise −3%
35Gemini 2.5 Flash Google1417.3 +148.2$0.333 summarise
  • Summarise −8%
36Gemini 3.1 Flash Lite Preview Google1414.8 +145.7$0.248 summarise
  • Summarise −31%
  • Agentic −17%
37Qwen3 235B A22B Thinking 2507 Qwen1413.8 +144.7$0.334 summarise
  • Summarise −8%
38Inkling Small Thinking Machines1411.7 +142.6$0.354 agentic
  • Agentic −3%
39Qwen3.5-27B Qwen1407.9 +138.8$0.263 summarise
  • Summarise −27%
40MiniMax M2.7 MiniMax1405.3 +136.2$0.277 summarise
  • Summarise −24%
  • Agentic −20%
41Qwen3.5-35B-A3B Qwen1395.6 +126.5$0.300 summarise
  • Summarise −17%
42GLM 4.6V Z.ai1374.7 +105.6$0.260 summarise
  • Summarise −28%
  • Agentic −33%
43GPT-5.4 Nano OpenAI1372.8 +103.7$0.201 summarise
  • Summarise −44%
  • Agentic −32%
44DeepSeek V3 0324 DeepSeek1375 +105.9$0.287 summarise
  • Summarise −21%
  • Agentic −1%
45GPT-5 Mini OpenAI1373.4 +104.3$0.273 summarise
  • Summarise −24%
46Qwen3 Next 80B A3B Thinking Qwen1367.5 +98.4$0.203 summarise
  • Summarise −44%
  • Agentic −16%
47Mercury 2 Inception1357.8 +88.7$0.211 summarise
  • Summarise −42%
  • Agentic −48%
48MiniMax M2.5 MiniMax1359 +89.9$0.241 summarise
  • Summarise −33%
  • Agentic −33%
49Trinity Large Thinking Arcee1341.9 +72.8$0.206 summarise
  • Summarise −43%
  • Agentic −40%
50MiniMax M2 MiniMax1342.1 +73$0.293 summarise
  • Summarise −19%

Cheaper and higher-scoring, but you give something up 3

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.

ModelIntelligence$/MHolds underWhat you give up
Olmo 3 32B Think Allen AI1298.5 +29.4$0.237
  • Balanced −36%
  • Summarise −54%
  • Chat −23%
  • Code gen −6%
  • Agentic −45%
  • no tool use
Gemma 3 4B Google1290.8 +21.7$0.063
  • Balanced −83%
  • Summarise −85%
  • Chat −81%
  • Code gen −79%
  • Agentic −84%
  • no tool use
DeepSeek V3 DeepSeek1332.6 +63.5$0.296 summarise
  • Summarise −18%
  • 16K → 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.
  • 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, and every other model something cheaper beats is listed here.