---
title: "Is Command R+ (08-2024) still undominated? · Undominated.ai"
canonical: https://undominated.ai/check/cohere__command-r-plus-08-2024/
description: "Command R+ (08-2024): 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 Command R+ (08-2024) still undominated? · Undominated.ai

> Command R+ (08-2024): 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 Command R+ (08-2024) a good deal?

Whether anything in this catalogue beats Command R+ (08-2024) 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, Command R+ (08-2024) is dominated for Balanced on LMArena. Gemini 3.8 Flash scores 265.9 higher and costs 66% less, with a covering envelope. 13 of 136 rated, priced standard models are undominated.

[Inspect model evidence](/models/cohere__command-r-plus-08-2024/) [Compare differences & requirements](/compare/?models=cohere%2Fcommand-r-plus-08-2024%2Cgoogle%2Fgemini-3.8-flash)

 Current model

Command R+ (08-2024)

 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)

Gemini 3.8 Flash is both better and cheaper than Command R+ (08-2024): 265.9 points higher on LMArena and 66% less per million tokens, $2.88 cheaper at this mix.

 [Command R+ (08-2024)](https://undominated.ai/models/cohere__command-r-plus-08-2024/)

LMArena Elo · higher is better

Scale starts at 1040 Elo

 **

1228.8

Effective $/M · Balanced · lower is better

 **

$4.38/M

 [Gemini 3.8 Flash](https://undominated.ai/models/google__gemini-3.8-flash/)

LMArena Elo · higher is better

Scale starts at 1040 Elo

 **

1494.7

Effective $/M · Balanced · lower is better

 **

$1.50/M

Command R+ (08-2024) takes text, returns up to 4,000 tokens from a 128,000-token context, and is listed by 1 seller.

Compared against 136 rated, priced models on this lens: 101 models dominate it and give up nothing, 5 more dominate it but give something up. Command R+ (08-2024) scores 1228.8 at $4.38 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 |
| --- | --- | --- | --- |
| [Gemini 3.8 Flash](/models/google__gemini-3.8-flash/) | 1494.7 +265.9 | $1.50/M | 66% |
| [Gemini 3.7 Flash](/models/google__gemini-3.7-flash/) | 1490.5 +261.7 | $1.50/M | 66% |
| [Muse Spark 1.3](/models/meta__muse-spark-1.3/) | 1489.7 +260.9 | $2.00/M | 54% |
| [Muse Spark 1.1](/models/meta__muse-spark-1.1/) | 1480.2 +251.4 | $2.00/M | 54% |
| [Gemini 3.6 Flash](/models/google__gemini-3.6-flash/) | 1476.1 +247.3 | $1.50/M | 66% |
| [Gemini 3.5 Flash](/models/google__gemini-3.5-flash/) | 1475.7 +246.9 | $3.38/M | 23% |
| [GLM 5.3](/models/z-ai__glm-5.3/) | 1475.1 +246.3 | $1.29/M | 71% |
| [GLM 5.3 Flash](/models/z-ai__glm-5.3-flash/) | 1471.9 +243.1 | $0.237/M | 95% |
| [GLM 5.2](/models/z-ai__glm-5.2/) | 1466.9 +238.1 | $0.998/M | 77% |
| [MiMo-V2.5-Pro](/models/xiaomi__mimo-v2.5-pro/) | 1464.8 +236.0 | $0.544/M | 88% |
| [GLM 5.1](/models/z-ai__glm-5.1/) | 1462.4 +233.6 | $1.48/M | 66% |
| [Gemini 2.5 Pro](/models/google__gemini-2.5-pro/) | 1457.8 +229.0 | $3.44/M | 21% |
| [GPT-5.6 Sol](/models/openai__gpt-5.6-sol/) | 1455.1 +226.3 | $4.00/M | 9% |
| [Kimi K2.6](/models/moonshotai__kimi-k2.6/) | 1454.9 +226.1 | $1.71/M | 61% |
| [Qwen3.7 Plus](/models/qwen__qwen3.7-plus/) | 1454.2 +225.4 | $0.560/M | 87% |
| [Grok 4.5](/models/x-ai__grok-4.5/) | 1450.1 +221.3 | $3.00/M | 31% |
| [GLM 5](/models/z-ai__glm-5/) | 1446.3 +217.5 | $0.930/M | 79% |
| [Qwen3.6 Max Preview](/models/qwen__qwen3.6-max-preview/) | 1446.3 +217.5 | $2.31/M | 47% |
| [Kimi K2.5](/models/moonshotai__kimi-k2.5/) | 1445.6 +216.8 | $0.900/M | 79% |
| [DeepSeek V4 Pro 0423](/models/deepseek__deepseek-v4-pro/) | 1444.0 +215.2 | $1.18/M | 73% |
| [Claude Sonnet 5](/models/anthropic__claude-sonnet-5/) | 1442.2 +213.4 | $4.00/M | 9% |
| [Gemma 4 31B](/models/google__gemma-4-31b-it/) | 1441.7 +212.9 | $0.153/M | 97% |
| [Hy3](/models/tencent__hy3/) | 1440.6 +211.8 | $0.144/M | 97% |
| [GLM 4.6](/models/z-ai__glm-4.6/) | 1440.5 +211.7 | $0.760/M | 83% |
| [Inkling](/models/thinkingmachines__inkling/) | 1439.7 +210.9 | $1.76/M | 60% |
| [Qwen3.8 27B](/models/qwen__qwen3.8-27b/) | 1439.3 +210.5 | $1.06/M | 76% |
| [Qwen3.5 397B A17B](/models/qwen__qwen3.5-397b-a17b/) | 1438.3 +209.5 | $1.29/M | 71% |
| [Qwen3.6 Plus](/models/qwen__qwen3.6-plus/) | 1436.7 +207.9 | $0.731/M | 83% |
| [GLM 5V Turbo](/models/z-ai__glm-5v-turbo/) | 1436.5 +207.7 | $1.90/M | 57% |
| [GLM 4.7](/models/z-ai__glm-4.7/) | 1435.9 +207.1 | $0.738/M | 83% |
| [Gemini 3.5 Flash Lite](/models/google__gemini-3.5-flash-lite/) | 1435.5 +206.7 | $0.850/M | 81% |
| [Gemma 4 26B A4B](/models/google__gemma-4-26b-a4b-it/) | 1434.5 +205.7 | $0.143/M | 97% |
| [MiniMax M3](/models/minimax__minimax-m3/) | 1433.5 +204.7 | $0.525/M | 88% |
| [DeepSeek V4 Flash 0423](/models/deepseek__deepseek-v4-flash/) | 1431.8 +203.0 | $0.103/M | 98% |
| [GLM 4.5](/models/z-ai__glm-4.5/) | 1430.2 +201.4 | $1.00/M | 77% |
| [GPT-5.6 Luna](/models/openai__gpt-5.6-luna/) | 1429.9 +201.1 | $0.450/M | 90% |
| [Grok 4.6](/models/x-ai__grok-4.6/) | 1429.9 +201.1 | $3.00/M | 31% |
| [R1 0528](/models/deepseek__deepseek-r1-0528/) | 1427.5 +198.7 | $0.912/M | 79% |
| [MiMo-V2.5](/models/xiaomi__mimo-v2.5/) | 1427.4 +198.6 | $0.175/M | 96% |
| [DeepSeek V3.2](/models/deepseek__deepseek-v3.2/) | 1424.8 +196.0 | $0.302/M | 93% |
| [DeepSeek V3.2 Exp](/models/deepseek__deepseek-v3.2-exp/) | 1422.6 +193.8 | $0.305/M | 93% |
| [GPT-5.1](/models/openai__gpt-5.1/) | 1422.6 +193.8 | $3.44/M | 21% |
| [Qwen3 VL 235B A22B Instruct](/models/qwen__qwen3-vl-235b-a22b-instruct/) | 1420.6 +191.8 | $0.632/M | 86% |
| [Mistral Medium 3.5](/models/mistralai__mistral-medium-3-5/) | 1420.6 +191.8 | $3.00/M | 31% |
| [Qwen3 235B A22B Instruct 2507](/models/qwen__qwen3-235b-a22b-2507/) | 1419.8 +191.0 | $0.153/M | 97% |
| [DeepSeek V3.1](/models/deepseek__deepseek-chat-v3.1/) | 1419.7 +190.9 | $0.425/M | 90% |
| [Qwen3.5-122B-A10B](/models/qwen__qwen3.5-122b-a10b/) | 1417.9 +189.1 | $0.715/M | 84% |
| [Qwen3 Next 80B A3B Instruct](/models/qwen__qwen3-next-80b-a3b-instruct/) | 1417.6 +188.8 | $0.343/M | 92% |
| [Gemini 2.5 Flash](/models/google__gemini-2.5-flash/) | 1417.3 +188.5 | $0.850/M | 81% |
| [DeepSeek V3.1 Terminus](/models/deepseek__deepseek-v3.1-terminus/) | 1416.9 +188.1 | $0.453/M | 90% |
| [Gemini 3.1 Flash Lite Preview](/models/google__gemini-3.1-flash-lite-preview/) | 1415.3 +186.5 | $0.563/M | 87% |
| [Qwen3 235B A22B Thinking 2507](/models/qwen__qwen3-235b-a22b-thinking-2507/) | 1415.1 +186.3 | $0.747/M | 83% |
| [Qwen3 Max](/models/qwen__qwen3-max/) | 1413.1 +184.3 | $1.56/M | 64% |
| [Inkling Small](/models/thinkingmachines__inkling-small/) | 1412.3 +183.5 | $0.637/M | 85% |
| [GPT-5.4 Mini](/models/openai__gpt-5.4-mini/) | 1412.1 +183.3 | $1.69/M | 61% |
| [o3](/models/openai__o3/) | 1409.9 +181.1 | $3.50/M | 20% |
| [Qwen3.5-27B](/models/qwen__qwen3.5-27b/) | 1408.1 +179.3 | $0.536/M | 88% |
| [GPT-5](/models/openai__gpt-5/) | 1406.1 +177.3 | $3.44/M | 21% |
| [MiniMax M2.7](/models/minimax__minimax-m2.7/) | 1404.6 +175.8 | $0.525/M | 88% |
| [Step 3.5 Flash](/models/stepfun__step-3.5-flash/) | 1403.7 +174.9 | $0.150/M | 97% |
| [Qwen3 VL 235B A22B Thinking](/models/qwen__qwen3-vl-235b-a22b-thinking/) | 1400.8 +172.0 | $1.30/M | 70% |
| [Qwen3.5-Flash](/models/qwen__qwen3.5-flash-02-23/) | 1397.7 +168.9 | $0.114/M | 97% |
| [Grok 4.3](/models/x-ai__grok-4.3/) | 1397.7 +168.9 | $1.56/M | 64% |
| [Claude Haiku 4.5](/models/anthropic__claude-haiku-4.5/) | 1396.6 +167.8 | $2.00/M | 54% |
| [Qwen3.5-35B-A3B](/models/qwen__qwen3.5-35b-a3b/) | 1395.5 +166.7 | $0.547/M | 88% |
| [GLM 4.5 Air](/models/z-ai__glm-4.5-air/) | 1383.7 +154.9 | $0.310/M | 93% |
| [Qwen3 30B A3B Instruct 2507](/models/qwen__qwen3-30b-a3b-instruct-2507/) | 1383.6 +154.8 | $0.084/M | 98% |
| [GPT-4.1](/models/openai__gpt-4.1/) | 1382.8 +154.0 | $3.50/M | 20% |
| [Solar Pro 4](/models/upstage__solar-pro4/) | 1377.3 +148.5 | $0.158/M | 96% |
| [GLM 4.6V](/models/z-ai__glm-4.6v/) | 1376.5 +147.7 | $0.450/M | 90% |
| [DeepSeek V3 0324](/models/deepseek__deepseek-chat-v3-0324/) | 1375.0 +146.2 | $0.438/M | 90% |
| [GPT-5 Mini](/models/openai__gpt-5-mini/) | 1373.0 +144.2 | $0.688/M | 84% |
| [GPT-5.4 Nano](/models/openai__gpt-5.4-nano/) | 1372.9 +144.1 | $0.463/M | 89% |
| [Qwen3 Next 80B A3B Thinking](/models/qwen__qwen3-next-80b-a3b-thinking/) | 1367.8 +139.0 | $0.412/M | 91% |
| [Qwen3 235B A22B](/models/qwen__qwen3-235b-a22b/) | 1366.1 +137.3 | $0.796/M | 82% |
| [gpt-oss-120b](/models/openai__gpt-oss-120b/) | 1365.9 +137.1 | $0.262/M | 94% |
| [Nova 2 Lite](/models/amazon__nova-2-lite-v1/) | 1362.6 +133.8 | $0.850/M | 81% |
| [MiniMax M2.5](/models/minimax__minimax-m2.5/) | 1358.9 +130.1 | $0.473/M | 89% |
| [Gemma 3 27B](/models/google__gemma-3-27b-it/) | 1357.7 +128.9 | $0.172/M | 96% |
| [Mercury 2](/models/inception__mercury-2/) | 1357.6 +128.8 | $0.375/M | 91% |
| [o4 Mini](/models/openai__o4-mini/) | 1353.2 +124.4 | $1.93/M | 56% |
| [GLM 4.7 Flash](/models/z-ai__glm-4.7-flash/) | 1352.2 +123.4 | $0.145/M | 97% |
| [MiniMax M1](/models/minimax__minimax-m1/) | 1342.7 +113.9 | $0.850/M | 81% |
| [MiniMax M2](/models/minimax__minimax-m2/) | 1342.1 +113.3 | $0.446/M | 90% |
| [Trinity Large Thinking](/models/arcee-ai__trinity-large-thinking/) | 1341.8 +113.0 | $0.388/M | 91% |
| [GPT-4.1 Mini](/models/openai__gpt-4.1-mini/) | 1340.2 +111.4 | $0.700/M | 84% |
| [Qwen3 32B](/models/qwen__qwen3-32b/) | 1340.0 +111.2 | $0.130/M | 97% |
| [o3 Mini High](/models/openai__o3-mini-high/) | 1336.5 +107.7 | $1.93/M | 56% |
| [Gemma 3 12B](/models/google__gemma-3-12b-it/) | 1334.2 +105.4 | $0.075/M | 98% |
| [DeepSeek V3](/models/deepseek__deepseek-chat/) | 1332.4 +103.6 | $0.463/M | 89% |
| [GPT-5 Nano](/models/openai__gpt-5-nano/) | 1319.7 +90.9 | $0.138/M | 97% |
| [o3 Mini](/models/openai__o3-mini/) | 1319.1 +90.3 | $1.93/M | 56% |
| [Qwen3 30B A3B](/models/qwen__qwen3-30b-a3b/) | 1317.0 +88.2 | $0.215/M | 95% |
| [Granite 4.2 8B](/models/ibm-granite__granite-4.2-8b/) | 1316.8 +88.0 | $0.107/M | 98% |
| [gpt-oss-20b](/models/openai__gpt-oss-20b/) | 1287.3 +58.5 | $0.036/M | 99% |
| [GPT-4o-mini (2024-07-18)](/models/openai__gpt-4o-mini-2024-07-18/) | 1286.3 +57.5 | $0.262/M | 94% |
| [GPT-4.1 Nano](/models/openai__gpt-4.1-nano/) | 1284.7 +55.9 | $0.175/M | 96% |
| [GPT-4o (2024-08-06)](/models/openai__gpt-4o-2024-08-06/) | 1282.5 +53.7 | $4.38/M | 0% |
| [Llama 3.3 70B Instruct](/models/meta-llama__llama-3.3-70b-instruct/) | 1274.0 +45.2 | $0.155/M | 96% |
| [Mistral Large 2407](/models/mistralai__mistral-large-2407/) | 1266.1 +37.3 | $3.00/M | 31% |
| [Llama 3.1 70B Instruct](/models/meta-llama__llama-3.1-70b-instruct/) | 1260.8 +32.0 | $0.400/M | 91% |

## 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 |
| --- | --- | --- | --- |
| [R1](/models/deepseek__deepseek-r1/) | 1372.6 | $1.15/M | context |
| [GLM 4.5V](/models/z-ai__glm-4.5v/) | 1332.9 | $0.900/M | context |
| [Gemma 3 4B](/models/google__gemma-3-4b-it/) | 1290.7 | $0.063/M | tools |
| [Qwen2.5 72B Instruct](/models/qwen__qwen-2.5-72b-instruct/) | 1268.9 | $0.370/M | context |
| [Mistral Small 3](/models/mistralai__mistral-small-24b-instruct-2501/) | 1233.5 | $0.058/M | context, 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/)