Cheaper alternatives to DeepSeek V3

DeepSeek LMArena 1332.6 $0.450/M on a balanced workload prices as of 2026-08-28

32 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, 38 score at least as high as DeepSeek V3 and cost no more under at least one workload. 32 match or beat it on every capability we hold — context, maximum output, input modes, tool use and extended reasoning. 6 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 DeepSeek V3, it is not generated.

Where it holds

WorkloadDeepSeek V3 $/MBetter and cheaperWith a trade
Balanced$0.450206
Summarise$0.296306
Chat$0.566226
Code gen$0.720206
Agentic$0.373296

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

Intelligence1332.6
Context window164K
Max output16K
Input modestext
Tool useyes
Extended reasoningno

A replacement has to clear every line above, not just the score. Full record for DeepSeek V3.

Better and cheaper, nothing given up 32

Each of these matches or beats DeepSeek V3 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 +109.1$0.152
  • Balanced −66%
  • Summarise −69%
  • Chat −69%
  • Code gen −67%
  • Agentic −72%
2Hy3 Tencent1441.2 +108.6$0.144
  • Balanced −68%
  • Summarise −74%
  • Chat −71%
  • Code gen −69%
  • Agentic −78%
3Gemma 4 26B A4B Google1434.6 +102$0.138
  • Balanced −69%
  • Summarise −72%
  • Chat −69%
  • Code gen −68%
  • Agentic −70%
4DeepSeek V4 Flash 0423 DeepSeek1431.6 +99$0.101
  • Balanced −77%
  • Summarise −78%
  • Chat −83%
  • Code gen −83%
  • Agentic −85%
5MiMo-V2.5 Xiaomi1427.3 +94.7$0.175
  • Balanced −61%
  • Summarise −64%
  • Chat −73%
  • Code gen −70%
  • Agentic −79%
6GPT-5.6 Luna OpenAI1428.5 +95.9$0.450
  • Balanced under 1% less
  • Summarise −33%
  • Chat −4%
  • Agentic −35%
7DeepSeek V3.2 DeepSeek1424.6 +92$0.290
  • Balanced −36%
  • Summarise −23%
  • Chat −52%
  • Code gen −55%
  • Agentic −46%
8DeepSeek V3.2 Exp DeepSeek1424.4 +91.8$0.305
  • Balanced −32%
  • Summarise −6%
  • Chat −42%
  • Code gen −51%
  • Agentic −22%
9Qwen3 235B A22B Instruct 2507 Qwen1419.3 +86.7$0.205
  • Balanced −54%
  • Summarise −62%
  • Chat −52%
  • Code gen −49%
  • Agentic −57%
10Qwen3 Next 80B A3B Instruct Qwen1418.6 +86$0.350
  • Balanced −22%
  • Summarise −52%
  • Chat −13%
  • Code gen −3%
  • Agentic −38%
11Step 3.5 Flash StepFun1403.8 +71.2$0.150
  • Balanced −67%
  • Summarise −63%
  • Chat −68%
  • Code gen −69%
  • Agentic −65%
12Qwen3.5-Flash Qwen1397.6 +65$0.114
  • Balanced −75%
  • Summarise −75%
  • Chat −75%
  • Code gen −75%
  • Agentic −75%
13Qwen3 30B A3B Instruct 2507 Qwen1384.3 +51.7$0.084
  • Balanced −81%
  • Summarise −81%
  • Chat −81%
  • Code gen −81%
  • Agentic −81%
14Solar Pro 4 Upstage1376.2 +43.6$0.052
  • Balanced −88%
  • Summarise −91%
  • Chat −90%
  • Code gen −89%
  • Agentic −92%
15DeepSeek V3 0324 DeepSeek1375 +42.4$0.438
  • Balanced −3%
  • Summarise −3%
  • Chat −3%
  • Code gen −3%
  • Agentic −3%
16Qwen3 Next 80B A3B Thinking Qwen1367.5 +34.9$0.412
  • Balanced −8%
  • Summarise −32%
  • Agentic −18%
17Gemma 3 27B Google1358.3 +25.7$0.172
  • Balanced −62%
  • Summarise −71%
  • Chat −62%
  • Code gen −59%
  • Agentic −70%
18GLM 4.7 Flash Z.ai1352.9 +20.3$0.145
  • Balanced −68%
  • Summarise −79%
  • Chat −68%
  • Code gen −64%
  • Agentic −78%
19Trinity Large Thinking Arcee1341.9 tie$0.378
  • Balanced −16%
  • Summarise −30%
  • Chat −25%
  • Code gen −19%
  • Agentic −41%
20MiniMax M2 MiniMax1342.1 tie$0.446
  • Balanced −1%
  • Summarise −1%
  • Chat −1%
  • Code gen −1%
  • Agentic −1%
21MiMo-V2.5-Pro Xiaomi1465 +132.4$0.480 chat
  • Chat −15%
  • Code gen −8%
  • Agentic −35%
22Qwen3.7 Plus Qwen1456.2 +123.6$0.295 summarise
  • Summarise under 1% less
  • Agentic −16%
23MiniMax M3 MiniMax1434.8 +102.2$0.277 summarise
  • Summarise −7%
  • Agentic −22%
24Qwen3 VL 235B A22B Instruct Qwen1420.9 +88.3$0.263 summarise
  • Summarise −11%
25DeepSeek V3.1 Terminus DeepSeek1419.6 +87$0.268 summarise
  • Summarise −9%
  • Chat −8%
  • Code gen −3%
  • Agentic −20%
26Gemini 3.1 Flash Lite Preview Google1414.8 +82.2$0.248 summarise
  • Summarise −16%
  • Agentic −19%
27Inkling Small Thinking Machines1411.7 +79.1$0.354 agentic
  • Agentic −5%
28Qwen3.5-27B Qwen1407.9 +75.3$0.263 summarise
  • Summarise −11%
29MiniMax M2.7 MiniMax1405.3 +72.7$0.277 summarise
  • Summarise −7%
  • Agentic −22%
30GPT-5.4 Nano OpenAI1372.8 +40.2$0.201 summarise
  • Summarise −32%
  • Agentic −33%
31GPT-5 Mini OpenAI1373.4 +40.8$0.273 summarise
  • Summarise −8%
32MiniMax M2.5 MiniMax1359 +26.4$0.241 summarise
  • Summarise −19%
  • Chat −8%
  • Agentic −34%

Cheaper and higher-scoring, but you give something up 6

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
GLM 4.5 Air Z.ai1382.8 +50.2$0.310
  • Balanced −31%
  • Summarise −54%
  • Chat −32%
  • Code gen −23%
  • Agentic −53%
  • 164K → 131K context
GLM 4.6V Z.ai1374.7 +42.1$0.450
  • Balanced under 1% less
  • Summarise −12%
  • Chat −18%
  • Code gen −11%
  • Agentic −35%
  • 164K → 131K context
gpt-oss-120b OpenAI1365.6 +33$0.070
  • Balanced −84%
  • Summarise −85%
  • Chat −84%
  • Code gen −84%
  • Agentic −85%
  • 164K → 131K context
Mercury 2 Inception1357.8 +25.2$0.375
  • Balanced −17%
  • Summarise −29%
  • Chat −32%
  • Code gen −26%
  • Agentic −49%
  • 164K → 128K context
Qwen3 32B Qwen1340.1 tie$0.130
  • Balanced −71%
  • Summarise −70%
  • Chat −72%
  • Code gen −72%
  • Agentic −71%
  • 164K → 131K context
Gemma 3 12B Google1334.2 tie$0.075
  • Balanced −83%
  • Summarise −81%
  • Chat −84%
  • Code gen −85%
  • Agentic −83%
  • 164K → 131K 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 ±10.68 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.