--- title: "Is Qwen2.5 72B Instruct still undominated? · Undominated.ai" canonical: https://undominated.ai/check/qwen__qwen-2.5-72b-instruct/ description: "Qwen2.5 72B Instruct: 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 Qwen2.5 72B Instruct still undominated? · Undominated.ai > Qwen2.5 72B Instruct: 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 Qwen2.5 72B Instruct a good deal? Whether anything in this catalogue beats Qwen2.5 72B Instruct 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, Qwen2.5 72B Instruct is dominated for Balanced on LMArena. GLM 5.3 Flash scores 203.0 higher and costs 36% less, with a covering envelope. 13 of 136 rated, priced standard models are undominated. [Inspect model evidence](/models/qwen__qwen-2.5-72b-instruct/) [Compare differences & requirements](/compare/?models=qwen%2Fqwen-2.5-72b-instruct%2Cz-ai%2Fglm-5.3-flash) Current model Qwen2.5 72B Instruct 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 Qwen2.5 72B Instruct: 203.0 points higher on LMArena and 36% less per million tokens, $0.13 cheaper at this mix. [Qwen2.5 72B Instruct](https://undominated.ai/models/qwen__qwen-2.5-72b-instruct/) LMArena Elo · higher is better Scale starts at 1040 Elo ** 1268.9 Effective $/M · Balanced · lower is better ** $0.370/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 Qwen2.5 72B Instruct takes text, returns up to 16,384 tokens from a 32,768-token context, and is listed by 2 sellers. Compared against 136 rated, priced models on this lens: 27 models dominate it and give up nothing, 1 more dominates it but gives something up. Qwen2.5 72B Instruct scores 1268.9 at $0.37 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 +203.0 | $0.237/M | 36% | | [Gemma 4 31B](/models/google__gemma-4-31b-it/) | 1441.7 +172.8 | $0.153/M | 59% | | [Hy3](/models/tencent__hy3/) | 1440.6 +171.7 | $0.144/M | 61% | | [Gemma 4 26B A4B](/models/google__gemma-4-26b-a4b-it/) | 1434.5 +165.6 | $0.143/M | 61% | | [DeepSeek V4 Flash 0423](/models/deepseek__deepseek-v4-flash/) | 1431.8 +162.9 | $0.103/M | 72% | | [MiMo-V2.5](/models/xiaomi__mimo-v2.5/) | 1427.4 +158.5 | $0.175/M | 53% | | [DeepSeek V3.2](/models/deepseek__deepseek-v3.2/) | 1424.8 +155.9 | $0.302/M | 18% | | [DeepSeek V3.2 Exp](/models/deepseek__deepseek-v3.2-exp/) | 1422.6 +153.7 | $0.305/M | 18% | | [Qwen3 235B A22B Instruct 2507](/models/qwen__qwen3-235b-a22b-2507/) | 1419.8 +150.9 | $0.153/M | 59% | | [Qwen3 Next 80B A3B Instruct](/models/qwen__qwen3-next-80b-a3b-instruct/) | 1417.6 +148.7 | $0.343/M | 7% | | [Step 3.5 Flash](/models/stepfun__step-3.5-flash/) | 1403.7 +134.8 | $0.150/M | 59% | | [Qwen3.5-Flash](/models/qwen__qwen3.5-flash-02-23/) | 1397.7 +128.8 | $0.114/M | 69% | | [GLM 4.5 Air](/models/z-ai__glm-4.5-air/) | 1383.7 +114.8 | $0.310/M | 16% | | [Qwen3 30B A3B Instruct 2507](/models/qwen__qwen3-30b-a3b-instruct-2507/) | 1383.6 +114.7 | $0.084/M | 77% | | [Solar Pro 4](/models/upstage__solar-pro4/) | 1377.3 +108.4 | $0.158/M | 57% | | [gpt-oss-120b](/models/openai__gpt-oss-120b/) | 1365.9 +97.0 | $0.262/M | 29% | | [Gemma 3 27B](/models/google__gemma-3-27b-it/) | 1357.7 +88.8 | $0.172/M | 53% | | [GLM 4.7 Flash](/models/z-ai__glm-4.7-flash/) | 1352.2 +83.3 | $0.145/M | 61% | | [Qwen3 32B](/models/qwen__qwen3-32b/) | 1340.0 +71.1 | $0.130/M | 65% | | [Gemma 3 12B](/models/google__gemma-3-12b-it/) | 1334.2 +65.3 | $0.075/M | 80% | | [GPT-5 Nano](/models/openai__gpt-5-nano/) | 1319.7 +50.8 | $0.138/M | 63% | | [Qwen3 30B A3B](/models/qwen__qwen3-30b-a3b/) | 1317.0 +48.1 | $0.215/M | 42% | | [Granite 4.2 8B](/models/ibm-granite__granite-4.2-8b/) | 1316.8 +47.9 | $0.107/M | 71% | | [gpt-oss-20b](/models/openai__gpt-oss-20b/) | 1287.3 +18.4 | $0.036/M | 90% | | [GPT-4o-mini (2024-07-18)](/models/openai__gpt-4o-mini-2024-07-18/) | 1286.3 +17.4 | $0.262/M | 29% | | [GPT-4.1 Nano](/models/openai__gpt-4.1-nano/) | 1284.7 +15.8 | $0.175/M | 53% | | [Llama 3.3 70B Instruct](/models/meta-llama__llama-3.3-70b-instruct/) | 1274.0 +5.1 | $0.155/M | 58% | ## 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 3 4B](/models/google__gemma-3-4b-it/) | 1290.7 | $0.063/M | tools | 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/)