Is MiniMax M2.5 a good deal?
Whether anything in this catalogue beats MiniMax M2.5 on both quality and price, and what you give up if it does. A computation on the current catalogue, not an opinion.
12 undominated of 145 · Oct 6, 2026
As of Oct 6, 2026, MiniMax M2.5 is dominated for Balanced on LMArena. GLM 5.3 Flash scores 110.3 higher and costs 54% less, with a covering envelope. 12 of 145 rated, priced standard models are undominated.
Inspect model evidence Compare differences & requirements
GLM 5.3 Flash is both better and cheaper than MiniMax M2.5: 110.3 points higher on LMArena and 54% less per million tokens, $0.284 cheaper at this mix.
LMArena Elo · higher is better
Scale starts at 1040 Elo
1359.3
Effective $/M · Balanced · lower is better
$0.521/M
LMArena Elo · higher is better
Scale starts at 1040 Elo
1469.6
Effective $/M · Balanced · lower is better
$0.238/M
MiniMax M2.5 takes text, returns up to 128,000 tokens from a 204,800-token context, and is listed by 9 sellers.
Compared against 145 rated, priced models on this lens: 11 models dominate it and give up nothing, 5 more dominate it but give something up. MiniMax M2.5 scores 1359.3 at $0.521 per million tokens for this mix.
Envelope-safe replacements
Each row scores at least as high, costs no more, and covers this model’s context, output, modalities, tools, and reasoning. A cheaper narrower model is not listed here.
| Model | LMArena | Effective $/M | You save |
|---|---|---|---|
| GLM 5.3 Flash | 1469.6 +110.3 | $0.238/M | 54% |
| DeepSeek V4.1 Flash | 1462.5 +103.2 | $0.182/M | 65% |
| MiMo-V2.6-Flash | 1456.4 +97.1 | $0.175/M | 66% |
| Hy3 | 1440.7 +81.4 | $0.231/M | 56% |
| Gemma 4 26B A4B | 1433.9 +74.6 | $0.127/M | 76% |
| DeepSeek V4 Flash 0423 | 1432.1 +72.8 | $0.113/M | 78% |
| MiniMax M3 | 1432.1 +72.8 | $0.485/M | 7% |
| GPT-5.6 Luna | 1431.0 +71.7 | $0.450/M | 14% |
| MiMo-V2.5 | 1427.5 +68.2 | $0.175/M | 66% |
| GPT-6 Luna | 1391.5 +32.2 | $0.200/M | 62% |
| GPT-5.4 Nano | 1372.1 +12.8 | $0.463/M | 11% |
Higher score, lower price, named losses
Not a drop-in. The loss is why these are not a recommendation.
| Model | LMArena | Effective $/M | You give up |
|---|---|---|---|
| Gemma 4 31B | 1443.4 | $0.205/M | max output |
| DeepSeek V3.2 | 1424.5 | $0.290/M | context, max output |
| DeepSeek V3.2 Exp | 1422.4 | $0.305/M | context |
| Qwen3 VL 235B A22B Instruct | 1420.1 | $0.370/M | max output, reasoning |
| DeepSeek V3.1 | 1419.7 | $0.453/M | context, max output |
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Saved decision references
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Constraint: replacements must preserve the model’s capabilities; any losses remain named trade-offs.
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