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MiniMax M2.5

GiriลŸ:$0.24/M
ร‡ฤฑktฤฑ:$0.96/M
Yayฤฑnlandฤฑ:Feb 12, 2026

MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1 to extend into general office work, reaching fluency in generating and operating Word, Excel, and Powerpoint files, context switching between diverse software environments, and working across different agent and human teams.

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MiniMax M2.5 iรงin Playground

MiniMax M2.5'ฤฑn Playground'unu keลŸfedin โ€” modelleri test etmek ve sorgularฤฑ gerรงek zamanlฤฑ olarak รงalฤฑลŸtฤฑrmak iรงin etkileลŸimli bir ortam. Prompt'larฤฑ deneyin, parametreleri ayarlayฤฑn ve geliลŸtirmeyi hฤฑzlandฤฑrmak ve kullanฤฑm senaryolarฤฑnฤฑ doฤŸrulamak iรงin anฤฑnda yineleyin.

Technical specifications of MiniMaxโ€‘M2.5

FieldClaim / value
Model nameMiniMax-M2.5 (production release, Feb 12, 2026).
ArchitectureMixture-of-Experts (MoE) Transformer (M2 family).
Total parameters~230 billion (total MoE capacity).
Active (per-inference) parameters~10 billion activated per inference (sparse activation).
Input typesText and code (native support for multi-file code contexts), tool-calling / API tool interfaces (agentic workflows).
Output typesText, structured outputs (JSON/tool calls), code (multi-file), Office artifacts (PPT/Excel/Word via tool chains).
Variants / modesM2.5 (high accuracy/capability) and M2.5-Lightning (same quality, lower latency / higher TPS).

What is MiniMaxโ€‘M2.5?

MiniMaxโ€‘M2.5 is the M2.x familyโ€™s flagship update focused on realโ€‘world productivity and agentic workflows. The release emphasizes improved task decomposition, tool/search integration, code generation fidelity, and token efficiency for extended, multiโ€‘step problems. The model is offered in a standard and a lowerโ€‘latency โ€œlightningโ€ variant intended for different deployment tradeโ€‘offs.


Main features of MiniMaxโ€‘M2.5

  1. Agentic-first design: Improved planning and tool orchestration for multiโ€‘stage tasks (search, tool calls, code execution harnesses).
  2. Token efficiency: Reported reductions in token consumption per task compared to M2.1, enabling lower endโ€‘toโ€‘end costs for long workflows.
  3. Faster endโ€‘toโ€‘end completion: Provider benchmarking reports average task completion times ~37% faster than M2.1 on agentic coding evaluations.
  4. Strong code understanding: Tuned on multiโ€‘language code corpora for robust crossโ€‘language refactors, multiโ€‘file edits, and repositoryโ€‘scale reasoning.
  5. High throughput serving: Targeted for production deployments with high token/sec profiles; suitable for continuous agent workloads.
  6. Variants for latency vs. power tradeoffs: M2.5โ€‘lightning offers lower latency at lower compute and footprint for interactive scenarios.

Benchmark performance (reported)

Providerโ€‘reported highlights โ€” representative metrics (release):

  • SWEโ€‘Bench Verified: 80.2% (reported pass rate on provider benchmark harnesses)
  • BrowseComp (search & tool use): 76.3%
  • Multiโ€‘SWEโ€‘Bench (multiโ€‘language coding): 51.3%
  • Relative speed / efficiency: ~37% faster endโ€‘toโ€‘end completion vs M2.1 on SWEโ€‘Bench Verified in provider tests; ~20% fewer search/tool rounds in some evaluations.

Interpretation: These numbers place M2.5 in parity with or near industryโ€‘leading agentic/code models on the cited benchmarks. Benchmarks are reported by the provider and reproduced by several ecosystem outlets โ€” treat them as measured under the providerโ€™s harness/configuration unless independently reproduced.


MiniMaxโ€‘M2.5 vs peers (concise comparison)

DimensionMiniMaxโ€‘M2.5MiniMax M2.1Peer example (Anthropic Opus 4.6)
SWEโ€‘Bench Verified80.2%~71โ€“76% (varies by harness)Comparable (Opus reported nearโ€‘top results)
Agentic task speed37% faster vs M2.1 (provider tests)BaselineSimilar speed on specific harnesses
Token efficiencyImproved vs M2.1 (~lower tokens per task)Higher token useCompetitive
Best useProduction agentic workflows, coding pipelinesEarlier generation of same familyStrong at multimodal reasoning and safetyโ€‘tuned tasks

Provider note: comparisons derive from release materials and vendor benchmark reports. Small differences can be sensitive to harness, toolchain, and evaluation protocol.

Representative enterprise use cases

  1. Repositoryโ€‘scale refactors & migration pipelines โ€” preserve intent across multiโ€‘file edits and automated PR patches.
  2. Agentic orchestration for DevOps โ€” orchestrate test runs, CI steps, package installs, and environment diagnostics with tool integrations.
  3. Automated code review & remediation โ€” triage vulnerabilities, propose minimal fixes, and prepare reproducible test cases.
  4. Searchโ€‘driven information retrieval โ€” leverage BrowseCompโ€‘level search competence to perform multiโ€‘round exploration and summarization of technical knowledge bases.
  5. Production agents & assistants โ€” continuous agents that require costโ€‘efficient, stable longโ€‘running inference.

How to access and integrate MiniMaxโ€‘M2.5

Step 1: Sign Up for API Key

Log in toย cometapi.com. If you are not our user yet, please register first. Sign into yourย CometAPI console. Get the access credential API key of the interface. Click โ€œAdd Tokenโ€ at the API token in the personal center, get the token key: sk-xxxxx and submit.

Step 2: Send Requests toย minimax-m2.5ย API

Select the โ€œminimax-m2.5โ€ endpoint to send the API request and set the request body. The request method and request body are obtained from our website API doc. Our website also provides Apifox test for your convenience. Replace <YOUR_API_KEY> with your actual CometAPI key from your account.ย Where to call it:ย Chatย format.

Insert your question or request into the content fieldโ€”this is what the model will respond to . Process the API response to get the generated answer.

Step 3: Retrieve and Verify Results

Process the API response to get the generated answer. After processing, the API responds with the task status and output data.

SSS

MiniMax M2.5 iรงin Fiyatlandฤฑrma

MiniMax M2.5 iรงin รงeลŸitli bรผtรงelere ve kullanฤฑm ihtiyaรงlarฤฑna uygun rekabetรงi fiyatlandฤฑrmayฤฑ keลŸfedin. Esnek planlarฤฑmฤฑz sadece kullandฤฑฤŸฤฑnฤฑz kadar รถdeme yapmanฤฑzฤฑ saฤŸlar ve ihtiyaรงlarฤฑnฤฑz bรผyรผdรผkรงe kolayca รถlรงeklendirme imkanฤฑ sunar. MiniMax M2.5'in maliyetleri yรถnetilebilir tutarken projelerinizi nasฤฑl geliลŸtirebileceฤŸini keลŸfedin.

Comet Price (USD / M Tokens)Official Price (USD / M Tokens)Discount
GiriลŸ:$0.24/M
ร‡ฤฑktฤฑ:$0.96/M
GiriลŸ:$0.3/M
ร‡ฤฑktฤฑ:$1.2/M
-20%

MiniMax M2.5 iรงin รถrnek kod ve API

MiniMax M2.5 iรงin kapsamlฤฑ รถrnek kodlara ve API kaynaklarฤฑna eriลŸerek entegrasyon sรผrecinizi kolaylaลŸtฤฑrฤฑn. Ayrฤฑntฤฑlฤฑ dokรผmantasyonumuz adฤฑm adฤฑm rehberlik saฤŸlayarak projelerinizde MiniMax M2.5'in tรผm potansiyelinden yararlanmanฤฑza yardฤฑmcฤฑ olur.

# Get your CometAPI key from https://api.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

curl https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "minimax-m2.5",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Write a one-sentence introduction to MiniMax M2.5."
      }
    ]
  }'

cURL Code Example

# Get your CometAPI key from https://api.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

curl https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "minimax-m2.5",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Write a one-sentence introduction to MiniMax M2.5."
      }
    ]
  }'

Python Code Example

from openai import OpenAI
import os

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/v1"

client = OpenAI(base_url=BASE_URL, api_key=COMETAPI_KEY)

completion = client.chat.completions.create(
    model="minimax-m2.5",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Write a one-sentence introduction to MiniMax M2.5."},
    ],
)

print(completion.choices[0].message.content)

JavaScript Code Example

import OpenAI from "openai";

// Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
const api_key = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const base_url = "https://api.cometapi.com/v1";

const openai = new OpenAI({
  apiKey: api_key,
  baseURL: base_url,
});

const completion = await openai.chat.completions.create({
  model: "minimax-m2.5",
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Write a one-sentence introduction to MiniMax M2.5." }
  ]
});

console.log(completion.choices[0].message.content);