--- title: "Is R1 0528 still undominated? · Undominated.ai" canonical: https://undominated.ai/check/deepseek__deepseek-r1-0528/ description: "R1 0528: 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 R1 0528 still undominated? · Undominated.ai > R1 0528: 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 R1 0528 a good deal? Whether anything in this catalogue beats R1 0528 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, R1 0528 is dominated for Balanced on LMArena. GLM 5.3 Flash scores 44.4 higher and costs 74% less, with a covering envelope. 13 of 136 rated, priced standard models are undominated. [Inspect model evidence](/models/deepseek__deepseek-r1-0528/) [Compare differences & requirements](/compare/?models=deepseek%2Fdeepseek-r1-0528%2Cz-ai%2Fglm-5.3-flash) Current model R1 0528 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 R1 0528: 44.4 points higher on LMArena and 74% less per million tokens, $0.68 cheaper at this mix. [R1 0528](https://undominated.ai/models/deepseek__deepseek-r1-0528/) LMArena Elo · higher is better Scale starts at 1040 Elo ** 1427.5 Effective $/M · Balanced · lower is better ** $0.912/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 R1 0528 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: 12 models dominate it and give up nothing, 2 more dominate it but give something up. R1 0528 scores 1427.5 at $0.91 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 +44.4 | $0.237/M | 74% | | [MiMo-V2.5-Pro](/models/xiaomi__mimo-v2.5-pro/) | 1464.8 +37.3 | $0.544/M | 40% | | [Qwen3.7 Plus](/models/qwen__qwen3.7-plus/) | 1454.2 +26.7 | $0.560/M | 39% | | [Kimi K2.5](/models/moonshotai__kimi-k2.5/) | 1445.6 +18.1 | $0.900/M | 1% | | [Hy3](/models/tencent__hy3/) | 1440.6 +13.1 | $0.144/M | 84% | | [Qwen3.6 Plus](/models/qwen__qwen3.6-plus/) | 1436.7 +9.2 | $0.731/M | 20% | | [GLM 4.7](/models/z-ai__glm-4.7/) | 1435.9 +8.4 | $0.738/M | 19% | | [Gemini 3.5 Flash Lite](/models/google__gemini-3.5-flash-lite/) | 1435.5 +8.0 | $0.850/M | 7% | | [Gemma 4 26B A4B](/models/google__gemma-4-26b-a4b-it/) | 1434.5 +7.0 | $0.143/M | 84% | | [MiniMax M3](/models/minimax__minimax-m3/) | 1433.5 +6.0 | $0.525/M | 42% | | [DeepSeek V4 Flash 0423](/models/deepseek__deepseek-v4-flash/) | 1431.8 +4.3 | $0.103/M | 89% | | [GPT-5.6 Luna](/models/openai__gpt-5.6-luna/) | 1429.9 +2.4 | $0.450/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 | | --- | --- | --- | --- | | [Gemma 4 31B](/models/google__gemma-4-31b-it/) | 1441.7 | $0.153/M | max output | | [GLM 4.6](/models/z-ai__glm-4.6/) | 1440.5 | $0.760/M | max output | 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/)