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Model Season every model has a season

MiniMax M2.7

minimax/minimax-m2.7-20260318
MiniMaxChinaOpen weights

The 32nd most-used model on the router over the last 7 days, with 0.40% of tokens. Weekly share peaked at 5.7% in the week of Mar 23, 2026, with 12T tokens processed since Mar 16, 2026.

Launch
Mar 18, 2026
Context
200k tokens
Modality
text → text
Reasoning
yes
License
Open weights
Input
$0.30 / 1M
Output
$1.20 / 1M
Share, last 7 days
0.40%
32nd of 61 · Sep 4, 2026 to Sep 10, 2026
Peak weekly share
5.7%
week of Mar 23, 2026
Cumulative tokens
12T
since the week of Mar 16, 2026
Weeks in the top 10
8
of 25 weeks with volume

Weekly token share

Share of the router's weekly volume, since the first week with volume

0%2%4%6%8%Apr '26MayJunJulAugpeak 5.7% on Mar 23, 2026
See the numbers
WeekShare
Aug 31, 20260.593%
Aug 24, 20260.179%
Aug 17, 20260.236%
Aug 10, 20260.257%
Aug 3, 20260.263%
Jul 27, 20260.213%
Jul 20, 20260.064%
Jul 13, 20260.105%
Jul 6, 20260.238%
Jun 29, 20260.272%
Jun 22, 20260.349%
Jun 15, 20260.517%
Jun 8, 20260.516%
Jun 1, 20260.933%
May 25, 20261.654%
May 18, 20261.930%
May 11, 20262.788%
May 4, 20262.893%
Apr 27, 20263.059%
Apr 20, 20263.605%
Apr 13, 20264.689%
Apr 6, 20265.659%
Mar 30, 20264.417%
Mar 23, 20265.673%
Mar 16, 20261.796%

Debuted in the week of Mar 16, 2026 and peaked at 5.7% 1 week later. The latest full week came in at 0.59%, 10% of peak.

What this model is used for new

Tasks where the model ranks among the leaders, and its share of each

This model is not among the leaders in any of the 29 tasks classified in the Sep 10, 2026 snapshot. That does not mean it goes unused: the source lists only the largest models in each task.

Snapshot of the rolling 7-day window through Sep 10, 2026. Share: the model's tokens in the task over the task's total tokens. Weight: the task's share of classified volume.

Where to run it

Endpoints in the source's catalog, from cheapest to most expensive on input

ProviderInputOutputContextQuantizationZero retention
GMICloud$0.21$0.84192kfp8no
Mara$0.24$0.96192knot reportedyes
Novita$0.27$1.08200kfp8yes
AtlasCloud$0.30$1.20192kfp8no
Minimax$0.30$1.20200kfp8yes
DeepInfra$0.38$1.70192kfp8yes
Groq$0.60$1.80192knot reportedyes
SambaNova$0.60$2.40192knot reportedyes
Minimax$0.60$2.40200kfp8yes

9 endpoints across 8 providers, with input from $0.21 to $0.60 per 1M tokens. 7 offer zero data retention.

Prices in US dollars per million tokens, from the latest archived endpoint catalog.

Benchmarks

Artificial Analysis indexes and benchmarks run by the source, with cost per task

Intelligence
23.2
44th of 82
Coding
52.6
48th of 111
Agents
16.8
50th of 86

GPQA Diamond 84.1%

$0.025 per task, 4143 tasks. 43rd of 131 evaluated. Median of evaluated models: 80.2%, $0.024 per task.

τ-bench verified, airline 71.1%

$0.018 per task, 1396 tasks. 56th of 122 evaluated. Median of evaluated models: 70.7%, $0.056 per task.

Artificial Analysis indexes, exposed by the catalog; benchmarks run by the source and archived on Sep 11, 2026. The gray mark is the median of evaluated models.

Against the week's largest models

The five largest proprietary and five largest open-weights models over the last 7 days

ModelLab7-day shareBlended priceContextIntelligenceWeeks in top 10
Proprietary
GPT-5.6 LunaOpenAIOpenAI11.5%$0.451M37.56
Gemini 3.8 FlashGoogleGoogle2.1%$1.501M41.20
Muse Spark 1.3 ContributorMetaMeta1.5%$0.1251M0
Claude Opus 5AnthropicAnthropic1.4%$10.001M50.71
GPT-5.6 SolOpenAIOpenAI1.4%$4.001M47.10
Open weights
Hy4 previewTencentTencent15.5%$1.251M1
DeepSeek V4 Flash 0731DeepSeekDeepSeek10.0%$0.0941.31M34.55
GLM 5.3 FlashZ.ai (GLM)Z.ai (GLM)10.0%$0.2371.31M41.92
MiMo-V2.5XiaomiXiaomi4.2%$0.1751M22.315
DeepSeek V4 Flash 0423DeepSeekDeepSeek3.9%$0.1111M24.819
MiniMax M2.7this pageMiniMaxMiniMax0.40%$0.525200k23.28

Share over the last 7 days (Sep 4, 2026 to Sep 10, 2026). Blended price in US dollars per million tokens, weighted 75% input and 25% output. A dash means the number is not published, not zero.

What this page doesn't say. Share here is a slice of one router's traffic, where the deciding factor is usually price per token. It is not market, revenue or user share, and it does not tell you which model fits your workload.