--- title: "Is MiniMax M1 still undominated? · Undominated.ai" canonical: https://undominated.ai/check/minimax__minimax-m1/ description: "MiniMax M1: whether it is still undominated. If anything in this catalogue is both better and cheaper, it is named, as of Oct 6, 2026. Unrated stays unrated." --- # Is MiniMax M1 still undominated? · Undominated.ai > MiniMax M1: whether it is still undominated. If anything in this catalogue is both better and cheaper, it is named, as of Oct 6, 2026. Unrated stays unrated. # Is MiniMax M1 a good deal? Whether anything in this catalogue beats MiniMax M1 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 [1 · Choose & set workload](#check-input)[2 · Read verdict](#check-verdict)[3 · Inspect alternatives](#check-options) As of Oct 6, 2026, MiniMax M1 is dominated for Balanced on LMArena. MiMo-V2.6-Pro scores 148.2 higher and costs 36% less, with a covering envelope. 12 of 145 rated, priced standard models are undominated. [Inspect model evidence](/models/minimax__minimax-m1/) [Compare differences & requirements](/compare/?models=minimax%2Fminimax-m1%2Cxiaomi%2Fmimo-v2.6-pro) Current model MiniMax M1 Balanced 3 tokens in per 1 out Balanced Summarise Chat Code gen Agentic Monthly spend (USD) Used only to say how many months a named switching cost would take to earn back. Leave blank to skip. Switching cost (USD) MiMo-V2.6-Pro is both better and cheaper than MiniMax M1: 148.2 points higher on LMArena and 36% less per million tokens, $0.310 cheaper at this mix. [MiniMax M1](https://undominated.ai/models/minimax__minimax-m1/) LMArena Elo · higher is better Scale starts at 1040 Elo ** 1342.8 Effective $/M · Balanced · lower is better ** $0.850/M [MiMo-V2.6-Pro](https://undominated.ai/models/xiaomi__mimo-v2.6-pro/) LMArena Elo · higher is better Scale starts at 1040 Elo ** 1491.0 Effective $/M · Balanced · lower is better ** $0.540/M MiniMax M1 takes text, returns up to 40,000 tokens from a 1,000,000-token context, and is listed by 2 sellers. Compared against 145 rated, priced models on this lens: 18 models dominate it and give up nothing, 5 more dominate it but give something up. MiniMax M1 scores 1342.8 at $0.850 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 | | --- | --- | --- | --- | | [MiMo-V2.6-Pro](/models/xiaomi__mimo-v2.6-pro/) | 1491.0 +148.2 | $0.540/M | 36% | | [GLM 5.3 Flash](/models/z-ai__glm-5.3-flash/) | 1469.6 +126.8 | $0.238/M | 72% | | [MiMo-V2.5-Pro](/models/xiaomi__mimo-v2.5-pro/) | 1465.0 +122.2 | $0.544/M | 36% | | [DeepSeek V4.1 Flash](/models/deepseek__deepseek-v4.1-flash/) | 1462.5 +119.7 | $0.182/M | 79% | | [MiMo-V2.6-Flash](/models/xiaomi__mimo-v2.6-flash/) | 1456.4 +113.6 | $0.175/M | 79% | | [Qwen3.7 Plus](/models/qwen__qwen3.7-plus/) | 1454.6 +111.8 | $0.560/M | 34% | | [Qwen3.8 27B](/models/qwen__qwen3.8-27b/) | 1440.7 +97.9 | $0.562/M | 34% | | [Qwen3.6 Plus](/models/qwen__qwen3.6-plus/) | 1436.7 +93.9 | $0.731/M | 14% | | [Gemini 3.5 Flash Lite](/models/google__gemini-3.5-flash-lite/) | 1434.7 +91.9 | $0.850/M | 0% | | [DeepSeek V4 Flash 0423](/models/deepseek__deepseek-v4-flash/) | 1432.1 +89.3 | $0.113/M | 87% | | [MiniMax M3](/models/minimax__minimax-m3/) | 1432.1 +89.3 | $0.485/M | 43% | | [GPT-5.6 Luna](/models/openai__gpt-5.6-luna/) | 1431.0 +88.2 | $0.450/M | 47% | | [MiMo-V2.5](/models/xiaomi__mimo-v2.5/) | 1427.5 +84.7 | $0.175/M | 79% | | [Gemini 2.5 Flash](/models/google__gemini-2.5-flash/) | 1417.0 +74.2 | $0.850/M | 0% | | [Gemini 3.1 Flash Lite Preview](/models/google__gemini-3.1-flash-lite-preview/) | 1415.7 +72.9 | $0.563/M | 34% | | [Qwen3.5-Flash](/models/qwen__qwen3.5-flash-02-23/) | 1397.0 +54.2 | $0.114/M | 87% | | [GPT-6 Luna](/models/openai__gpt-6-luna/) | 1391.5 +48.7 | $0.200/M | 76% | | [Nova 2 Lite](/models/amazon__nova-2-lite-v1/) | 1361.8 +19.0 | $0.850/M | 0% | ## 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](/models/google__gemma-4-31b-it/) | 1443.4 | $0.205/M | context, max output | | [Hy3](/models/tencent__hy3/) | 1440.7 | $0.231/M | context | | [GLM 4.6](/models/z-ai__glm-4.6/) | 1439.9 | $0.760/M | context, max output | | [GLM 4.7](/models/z-ai__glm-4.7/) | 1435.5 | $0.738/M | context | | [Gemma 4 26B A4B](/models/google__gemma-4-26b-a4b-it/) | 1433.9 | $0.127/M | context | 145 rated, priced standard models. Chartreuse is the frontier. Cobalt is the model you named, when it is not on the staircase. Copy watch URL [Open the frontier](/frontier/) The link keeps the model and mix, using the current catalogue. Monthly spend and switching cost stay in this browser tab and are left out of the link. ## Saved decision references Save the model, workload, catalogue date and capability-preservation rule in this browser. Spend, switching cost and bill contents are not saved. No account or notifications. Constraint: replacements must preserve the model’s capabilities; any losses remain named trade-offs. Historical decisions cannot be fully replayed from saved references: past prices, scores and capability evidence are not stored. Save this reference ## Continue your investigation - [Build a shortlist](/compare/) - [Inspect alternatives](/alternatives/) - [Check billing conditions](/traps/) - [Read model evidence](/models/)