--- title: "Is DeepSeek V3.1 Terminus still undominated? · Undominated.ai" canonical: https://undominated.ai/check/deepseek__deepseek-v3.1-terminus/ description: "DeepSeek V3.1 Terminus: whether it is still undominated. If anything in this catalogue is both better and cheaper, it is named, as of Sep 23, 2026. Unrated stays unrated." --- # Is DeepSeek V3.1 Terminus still undominated? · Undominated.ai > DeepSeek V3.1 Terminus: whether it is still undominated. If anything in this catalogue is both better and cheaper, it is named, as of Sep 23, 2026. Unrated stays unrated. # Is DeepSeek V3.1 Terminus a good deal? Whether anything in this catalogue beats DeepSeek V3.1 Terminus on both quality and price, and what you give up if it does. A computation on the current catalogue, not an opinion. 13 undominated of 136 · Sep 23, 2026 [1 · Choose & set workload](#check-input)[2 · Read verdict](#check-verdict)[3 · Inspect alternatives](#check-options) As of Sep 23, 2026, DeepSeek V3.1 Terminus is dominated for Balanced on LMArena. GLM 5.3 Flash scores 55.0 higher and costs 48% less, with a covering envelope. 13 of 136 rated, priced standard models are undominated. [Inspect model evidence](/models/deepseek__deepseek-v3.1-terminus/) [Compare differences & requirements](/compare/?models=deepseek%2Fdeepseek-v3.1-terminus%2Cz-ai%2Fglm-5.3-flash) Current model DeepSeek V3.1 Terminus 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) GLM 5.3 Flash is both better and cheaper than DeepSeek V3.1 Terminus: 55.0 points higher on LMArena and 48% less per million tokens, $0.22 cheaper at this mix. [DeepSeek V3.1 Terminus](https://undominated.ai/models/deepseek__deepseek-v3.1-terminus/) LMArena Elo · higher is better Scale starts at 1040 Elo ** 1416.9 Effective $/M · Balanced · lower is better ** $0.453/M [GLM 5.3 Flash](https://undominated.ai/models/z-ai__glm-5.3-flash/) LMArena Elo · higher is better Scale starts at 1040 Elo ** 1471.9 Effective $/M · Balanced · lower is better ** $0.237/M DeepSeek V3.1 Terminus takes text, returns up to 32,768 tokens from a 163,840-token context, and is listed by 4 sellers. Compared against 136 rated, priced models on this lens: 9 models dominate it and give up nothing, 3 more dominate it but give something up. DeepSeek V3.1 Terminus scores 1416.9 at $0.45 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](/models/z-ai__glm-5.3-flash/) | 1471.9 +55.0 | $0.237/M | 48% | | [Hy3](/models/tencent__hy3/) | 1440.6 +23.7 | $0.144/M | 68% | | [Gemma 4 26B A4B](/models/google__gemma-4-26b-a4b-it/) | 1434.5 +17.6 | $0.143/M | 69% | | [DeepSeek V4 Flash 0423](/models/deepseek__deepseek-v4-flash/) | 1431.8 +14.9 | $0.103/M | 77% | | [GPT-5.6 Luna](/models/openai__gpt-5.6-luna/) | 1429.9 +13.0 | $0.450/M | 1% | | [MiMo-V2.5](/models/xiaomi__mimo-v2.5/) | 1427.4 +10.5 | $0.175/M | 61% | | [DeepSeek V3.2](/models/deepseek__deepseek-v3.2/) | 1424.8 +7.9 | $0.302/M | 33% | | [DeepSeek V3.2 Exp](/models/deepseek__deepseek-v3.2-exp/) | 1422.6 +5.7 | $0.305/M | 33% | | [DeepSeek V3.1](/models/deepseek__deepseek-chat-v3.1/) | 1419.7 +2.8 | $0.425/M | 6% | ## 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/) | 1441.7 | $0.153/M | max output | | [Qwen3 235B A22B Instruct 2507](/models/qwen__qwen3-235b-a22b-2507/) | 1419.8 | $0.153/M | reasoning | | [Qwen3 Next 80B A3B Instruct](/models/qwen__qwen3-next-80b-a3b-instruct/) | 1417.6 | $0.343/M | max output, reasoning | 136 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/)