Cheaper alternatives to MiniMax M2

MiniMax LMArena 1342.1 $0.446/M on a balanced workload prices as of 2026-08-28

8 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, 34 score at least as high as MiniMax M2 and cost no more under at least one workload. 8 match or beat it on every capability we hold — context, maximum output, input modes, tool use and extended reasoning. 26 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 MiniMax M2, it is not generated.

Where it holds

WorkloadMiniMax M2 $/MBetter and cheaperWith a trade
Balanced$0.446317
Summarise$0.293526
Chat$0.561420
Code gen$0.714418
Agentic$0.370823

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

Intelligence1342.1
Context window205K
Max output131K
Input modestext
Tool useyes
Extended reasoningyes

A replacement has to clear every line above, not just the score. Full record for MiniMax M2.

Better and cheaper, nothing given up 8

Each of these matches or beats MiniMax M2 on context, maximum output, input modes, tool use and reasoning, scores at least as high, and costs no more.

#ModelIntelligence$/MHolds under
1DeepSeek V4 Flash 0423 DeepSeek1431.6 +89.5$0.101
  • Balanced −77%
  • Summarise −77%
  • Chat −83%
  • Code gen −83%
  • Agentic −85%
2MiMo-V2.5 Xiaomi1427.3 +85.2$0.175
  • Balanced −61%
  • Summarise −63%
  • Chat −72%
  • Code gen −70%
  • Agentic −79%
3Solar Pro 4 Upstage1376.2 +34.1$0.052
  • Balanced −88%
  • Summarise −91%
  • Chat −90%
  • Code gen −89%
  • Agentic −92%
4MiMo-V2.5-Pro Xiaomi1465 +122.9$0.480 chat
  • Chat −15%
  • Code gen −7%
  • Agentic −34%
5Qwen3.7 Plus Qwen1456.2 +114.1$0.312 agentic
  • Agentic −16%
6MiniMax M3 MiniMax1434.8 +92.7$0.277 summarise
  • Summarise −6%
  • Agentic −21%
7Inkling Small Thinking Machines1411.7 +69.6$0.354 agentic
  • Agentic −4%
8MiniMax M2.7 MiniMax1405.3 +63.2$0.277 summarise
  • Summarise −6%
  • Agentic −21%

Cheaper and higher-scoring, but you give something up 26

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
Gemma 4 31B Google1441.7 +99.6$0.152
  • Balanced −66%
  • Summarise −69%
  • Chat −68%
  • Code gen −67%
  • Agentic −72%
  • 131K → 16K max output
Hy3 Tencent1441.2 +99.1$0.144
  • Balanced −68%
  • Summarise −74%
  • Chat −71%
  • Code gen −68%
  • Agentic −78%
  • 131K → 128K max output
Gemma 4 26B A4B Google1434.6 +92.5$0.138
  • Balanced −69%
  • Summarise −72%
  • Chat −68%
  • Code gen −68%
  • Agentic −70%
  • 131K → 16K max output
DeepSeek V3.2 DeepSeek1424.6 +82.5$0.290
  • Balanced −35%
  • Summarise −22%
  • Chat −52%
  • Code gen −55%
  • Agentic −46%
  • 205K → 164K context
DeepSeek V3.2 Exp DeepSeek1424.4 +82.3$0.305
  • Balanced −32%
  • Summarise −6%
  • Chat −42%
  • Code gen −50%
  • Agentic −21%
  • 205K → 164K context
  • 131K → 66K max output
Qwen3 235B A22B Instruct 2507 Qwen1419.3 +77.2$0.205
  • Balanced −54%
  • Summarise −61%
  • Chat −51%
  • Code gen −49%
  • Agentic −57%
  • 131K → 16K max output
  • no extended reasoning
Qwen3 Next 80B A3B Instruct Qwen1418.6 +76.5$0.350
  • Balanced −22%
  • Summarise −52%
  • Chat −12%
  • Code gen −2%
  • Agentic −37%
  • no extended reasoning
Step 3.5 Flash StepFun1403.8 +61.7$0.150
  • Balanced −66%
  • Summarise −62%
  • Chat −68%
  • Code gen −69%
  • Agentic −65%
  • 131K → 66K max output
Qwen3.5-Flash Qwen1397.6 +55.5$0.114
  • Balanced −75%
  • Summarise −75%
  • Chat −75%
  • Code gen −75%
  • Agentic −74%
  • 131K → 66K max output
Qwen3 30B A3B Instruct 2507 Qwen1384.3 +42.2$0.084
  • Balanced −81%
  • Summarise −81%
  • Chat −81%
  • Code gen −81%
  • Agentic −81%
  • 131K → 32K max output
  • no extended reasoning
GLM 4.5 Air Z.ai1382.8 +40.7$0.310
  • Balanced −31%
  • Summarise −54%
  • Chat −31%
  • Code gen −22%
  • Agentic −53%
  • 205K → 131K context
  • 131K → 98K max output
DeepSeek V3 0324 DeepSeek1375 +32.9$0.438
  • Balanced −2%
  • Summarise −2%
  • Chat −2%
  • Code gen −2%
  • Agentic −2%
  • 205K → 164K context
  • no extended reasoning
gpt-oss-120b OpenAI1365.6 +23.5$0.070
  • Balanced −84%
  • Summarise −85%
  • Chat −84%
  • Code gen −84%
  • Agentic −85%
  • 205K → 131K context
  • 131K → 118K max output
Qwen3 Next 80B A3B Thinking Qwen1367.5 +25.4$0.412
  • Balanced −8%
  • Summarise −31%
  • Agentic −17%
  • 131K → 33K max output
Gemma 3 27B Google1358.3 +16.2$0.172
  • Balanced −61%
  • Summarise −70%
  • Chat −61%
  • Code gen −58%
  • Agentic −70%
  • 131K → 118K max output
  • no extended reasoning
GLM 4.7 Flash Z.ai1352.9 +10.8$0.145
  • Balanced −68%
  • Summarise −79%
  • Chat −68%
  • Code gen −64%
  • Agentic −78%
  • 205K → 203K context
  • 131K → 16K max output
Mercury 2 Inception1357.8 +15.7$0.375
  • Balanced −16%
  • Summarise −28%
  • Chat −32%
  • Code gen −25%
  • Agentic −48%
  • 205K → 128K context
  • 131K → 50K max output
GPT-5.6 Luna OpenAI1428.5 +86.4$0.199 summarise
  • Summarise −32%
  • Chat −3%
  • Agentic −34%
  • 131K → 128K max output
Qwen3 VL 235B A22B Instruct Qwen1420.9 +78.8$0.263 summarise
  • Summarise −10%
  • 131K → 33K max output
  • no extended reasoning
DeepSeek V3.1 Terminus DeepSeek1419.6 +77.5$0.268 summarise
  • Summarise −9%
  • Chat −7%
  • Code gen −2%
  • Agentic −19%
  • 205K → 164K context
  • 131K → 33K max output
Gemini 3.1 Flash Lite Preview Google1414.8 +72.7$0.248 summarise
  • Summarise −15%
  • Agentic −18%
  • 131K → 66K max output
Qwen3.5-27B Qwen1407.9 +65.8$0.263 summarise
  • Summarise −10%
  • 131K → 66K max output
GLM 4.6V Z.ai1374.7 +32.6$0.260 summarise
  • Summarise −11%
  • Chat −17%
  • Code gen −10%
  • Agentic −34%
  • 205K → 131K context
  • 131K → 33K max output
GPT-5.4 Nano OpenAI1372.8 +30.7$0.201 summarise
  • Summarise −31%
  • Agentic −32%
  • 131K → 128K max output
GPT-5 Mini OpenAI1373.4 +31.3$0.273 summarise
  • Summarise −7%
  • 131K → 128K max output
MiniMax M2.5 MiniMax1359 +16.9$0.241 summarise
  • Summarise −18%
  • Chat −7%
  • Agentic −33%
  • 131K → 128K 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.