Is MiniMax M3 a good deal?
Whether anything in this catalogue beats MiniMax M3 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 M3 is dominated for Balanced on LMArena. GLM 5.3 Flash scores 37.5 higher and costs 51% 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 M3: 37.5 points higher on LMArena and 51% less per million tokens, $0.248 cheaper at this mix.
LMArena Elo · higher is better
Scale starts at 1040 Elo
1432.1
Effective $/M · Balanced · lower is better
$0.485/M
LMArena Elo · higher is better
Scale starts at 1040 Elo
1469.6
Effective $/M · Balanced · lower is better
$0.238/M
MiniMax M3 takes text, image, video, returns up to 512,000 tokens from a 1,048,576-token context, and is listed by 13 sellers. Open weights, so it can also be self-hosted.
Compared against 145 rated, priced models on this lens: 1 model dominates it and gives up nothing, 5 more dominate it but give something up. MiniMax M3 scores 1432.1 at $0.485 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 +37.5 | $0.238/M | 51% |
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 |
|---|---|---|---|
| DeepSeek V4.1 Flash | 1462.5 | $0.182/M | video |
| MiMo-V2.6-Flash | 1456.4 | $0.175/M | max output |
| Gemma 4 31B | 1443.4 | $0.205/M | context, max output |
| Hy3 | 1440.7 | $0.231/M | context, max output, image, video |
| Gemma 4 26B A4B | 1433.9 | $0.127/M | context, max output |
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Constraint: replacements must preserve the model’s capabilities; any losses remain named trade-offs.
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