MiniMax M2.5

MiniMaxKey minimax-m2.5Also reported as minimaxai/minimax-m2.5, hf:minimaxai/minimax-m2.5, minimax/minimax-m2.5, public/minimax-m2.5, MiniMax-M2.5, rev/minimax-m2.5, pro/minimaxai/minimax-m2.5, kr/minimax-m2.5, srv_mp2huzrg06e426ad12f3:minimaxai/minimax-m2.5, baseten/minimax-m2.5, commandcode/minimaxai/minimax-m2.5, cmc/minimaxai/minimax-m2.5

Rank
#276
by active users
Active users
3
Down 1 from 4 active users in the previous 30 days. vs previous 30 days
Adoption
0.3%
of 958 accounts
Tokens
171K
cache included
Est. cost
<$1
at public list prices
First seen
Feb 12, 2026
in any submission

Oct 14 – Nov 12, 2026 (UTC)958 accounts100% of tokens from an identified modelData through Nov 12, 2026, 00:47 UTCHow we count

Daily active users

Distinct accounts that used this model on each UTC day.

0 active users on Nov 12, 2026

Daily active users for MiniMax M2.5, Oct 14, 2026 to Nov 12, 2026. Peak 1. Use the left and right arrow keys to read each day.110
Show daily values
Daily active users and tokens for MiniMax M2.5
Date (UTC)Active usersTokens
Oct 14, 202615.4K
Oct 15, 202600
Oct 16, 202600
Oct 17, 202600
Oct 18, 202600
Oct 19, 202600
Oct 20, 202600
Oct 21, 202600
Oct 22, 202600
Oct 23, 202600
Oct 24, 202600
Oct 25, 202600
Oct 26, 202600
Oct 27, 202600
Oct 28, 202600
Oct 29, 202600
Oct 30, 202600
Oct 31, 202600
Nov 1, 202600
Nov 2, 202600
Nov 3, 20261154K
Nov 4, 202600
Nov 5, 202600
Nov 6, 202600
Nov 7, 202600
Nov 8, 2026111.5K
Nov 9, 202600
Nov 10, 202600
Nov 11, 202600
Nov 12, 202600

Token mix

How the 171K tokens split. Cache reads are usually most of an agent's tokens and are priced far below input.

  • Input96%
  • Output0.3%
  • Cache read<0.1%
  • Cache write3.1%
  • Reasoning0.2%

Agents that carry MiniMax M2.5

Each agent's share of this model's tokens, and how many accounts used the model through it.

  1. OpenCode90% of this model's tokens1active users
  2. cc-mirror/mozilla4.5% of this model's tokens1active users
  3. Oh My Pi3.2% of this model's tokens1active users
  4. cc-mirror/curl2.2% of this model's tokens1active users

Benchmarks

The best result for MiniMax M2.5 in each benchmark Tokscale tracks. Each benchmark has its own unit, run conditions and source, so compare a score only with other models on the same benchmark. Rank is among the models Tokscale matched in that benchmark.

All benchmarks
  • Epoch Capabilities IndexOverall · Epoch AI
    146.6
    Rank #76 of 160 matched modelsNo conditions reportedModel released Feb 12, 2026Source: epoch.ai (opens in a new tab)
  • WebDev ArenaWeb development · LMArena
    1,386
    Rank #84 of 110 matched modelsNo conditions reportedPublished Oct 19, 2026Source: huggingface.co (opens in a new tab)

Not evaluated: GPQA Diamond, Humanity's Last Exam, FrontierMath Tiers 1–3 (v2), SimpleQA Verified, Terminal-Bench 4.0, CursorBench, DeepSWE, FrontierSWE, Agent Arena. A missing result is not a score of zero.

Pricing

List prices from models.dev in US dollars per 1M tokens, retrieved Oct 21, 2026. MiniMax (minimax.io) is the lab's own API and the reference price for the estimates below.

Price at real agent usageEstimate at list prices

What 1M tokens cost at the reference list price when they split into input, output and cache the way Tokscale users' agents used them. It is not what anyone paid.

At this model's mix
$0.31
Est. per 1M tokens
<0.1% cache reads
At the community mix
$0.04
Est. per 1M tokens
96% cache reads
3:1 input/output blend
$0.52
Per 1M tokens at list prices
No cache

Cache reads were <0.1% of MiniMax M2.5 tokens in the last 30 days and 96% of all tokens. The 3:1 blend, (3 × input + output) ÷ 4, is the usual comparison and ignores cache.

Assumptions

  • MiniMax (minimax.io) list prices per 1M tokens: input $0.30, output $1.20, cache read $0.03, cache write $0.38.
  • This model's mix is its own input, output, cache and reasoning tokens in the last 30 days.
  • The community mix is the tokens of every identified model in the last 30 days.
  • This is an estimate at list prices, not what anyone paid.
  • Reasoning tokens are priced as output.
  • Long-context tiers, batch pricing and discounts are not applied.
  • Token mixes come from public Tokscale submissions. Hidden accounts are excluded.

List prices by provider

  • MiniMax (minimax.io)ReferenceMiniMax-M2.5
    $0.30 input per 1M tokens$1.20 output per 1M tokens$0.03 cache read per 1M tokens$0.38 cache write per 1M tokens205K tokens of context
  • Amazon Bedrockminimax.minimax-m2.5
    $0.30 input per 1M tokens$1.20 output per 1M tokensCache read not listedCache write not listed197K tokens of context
  • OpenRouterminimax/minimax-m2.5
    $0.27 input per 1M tokens$0.95 output per 1M tokens$0.03 cache read per 1M tokensCache write not listed205K tokens of context
  • Vercel AI Gatewayminimax/minimax-m2.5
    $0.30 input per 1M tokens$1.20 output per 1M tokens$0.03 cache read per 1M tokens$0.38 cache write per 1M tokens205K tokens of context

Specs

From models.dev (MIT), retrieved Oct 21, 2026, as the lab or the first listed provider reports them. A dash means models.dev does not list the value.

Context window
205K tokens
Max output
131K tokens
Input
Text
Output
Text
Knowledge cutoff
— not listed
Release date
Feb 12, 2026
Open weights
Yes
Reasoning
Yes
Tool calling
Yes

Top public profiles

Public profiles that used MiniMax M2.5 most in this period, by tokens. Hidden accounts are never listed.

  1. 1ardjo@ardjo-s154Ktokens<$1est. cost1active days<$1 est. cost · 1 active days
  2. 2如是@MiFaZhan11.5Ktokens<$1est. cost1active days<$1 est. cost · 1 active days
  3. 3candyandy@andredubbs5.4Ktokens—est. cost1active daysno price · 1 active days

More from MiniMax

Other MiniMax models in the same period, by active users.

  1. MiniMax M3.1 Flash Free5.8% adoption56active users
  2. MiniMax M3.1 Flash4.0% adoption38active users
  3. MiniMax M32.7% adoption26active users
  4. MiniMax M3.1 Flash Preview1.3% adoption12active users
  5. MiniMax M2.70.6% adoption6active users
  6. MiniMax M2.7 Highspeed0.1% adoption1active users
All models

Sources and attribution

Each score keeps its own source, unit and run conditions. Tokscale does not combine benchmarks into one score, and a missing score means the model was not evaluated, not that it scored zero.

  • Epoch AIEpoch Capabilities Index, Epoch's own runs and the external results it collects.CC BY 4.0 · Retrieved Oct 21, 2026 · Data through Oct 15, 2026Epoch AI, ‘Capabilities & benchmarking’. Published online at epoch.ai. Retrieved from https://epoch.ai/benchmarks.
  • LMArenaWebDev Arena and Agent Arena leaderboards.CC BY 4.0 · Retrieved Oct 21, 2026 · Data through Oct 19, 2026LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), Hugging Face.
  • models.devSpecs and list prices per provider.MIT · Retrieved Oct 21, 2026models.dev, an open catalog of AI models (github.com/anomalyco/models.dev).
  • TokscaleActive users, tokens and token mix from public Tokscale submissions. Hidden accounts are excluded.How we count