per 1M tokens
MiniMax M2.5
novita/minimax/minimax-m2.5
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. Scoring 80.2% on SWE-Bench Verified, 51.3% on Multi-SWE-Bench, and 76.3% on BrowseComp, M2.5 is also more token efficient than previous generations, having been trained to optimize its actions and output through planning.
Price
per 1M tokens
Providers
Each row is one seller. Prices are the published rate from that source. A dash means that source did not publish the amount. Sorted by a 3:1 blend of input and output.
No provider prices yet.
Monthly bill
Token models use the token counts. Image, video, and audio models use units times the flat rate.
$1.50 at list price for this workload
Cache
per 1M tokens
Every rate
| Unit | Input | Output | Flat | Confidence |
|---|---|---|---|---|
| token | $0.3/1M | $1.2/1M | Not published— | official |
Price history
input or flat output
Daily snapshots
| UTC date | Unit | Input | Output | Flat |
|---|---|---|---|---|
| 2026-10-08 | token | $0.3 | $1.2 | Not published— |
| 2026-10-09 | token | $0.3 | $1.2 | Not published— |
| 2026-10-10 | token | $0.3 | $1.2 | Not published— |
| 2026-10-11 | token | $0.3 | $1.2 | Not published— |
| 2026-10-12 | token | $0.3 | $1.2 | Not published— |
| 2026-10-13 | token | $0.3 | $1.2 | Not published— |
| 2026-10-14 | token | $0.3 | $1.2 | Not published— |
| 2026-10-15 | token | $0.3 | $1.2 | Not published— |
| 2026-10-16 | token | $0.3 | $1.2 | Not published— |
| 2026-10-17 | token | $0.3 | $1.2 | Not published— |
| 2026-10-18 | token | $0.3 | $1.2 | Not published— |
| 2026-10-19 | token | $0.3 | $1.2 | Not published— |
| 2026-10-20 | token | $0.3 | $1.2 | Not published— |
| 2026-10-21 | token | $0.3 | $1.2 | Not published— |
| 2026-10-22 | token | $0.3 | $1.2 | Not published— |
| 2026-10-23 | token | $0.3 | $1.2 | Not published— |
| 2026-10-24 | token | $0.3 | $1.2 | Not published— |
| 2026-10-25 | token | $0.3 | $1.2 | Not published— |
| 2026-10-26 | token | $0.3 | $1.2 | Not published— |
| 2026-10-27 | token | $0.3 | $1.2 | Not published— |
| 2026-10-28 | token | $0.3 | $1.2 | Not published— |
| 2026-10-29 | token | $0.3 | $1.2 | Not published— |
| 2026-10-30 | token | $0.3 | $1.2 | Not published— |
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Call this model
OpenRouter id novita/minimax/minimax-m2.5. InferenceList does not send the request.
curl
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"novita/minimax/minimax-m2.5","messages":[{"role":"user","content":"Hello"}]}'
JavaScript
await fetch("https://openrouter.ai/api/v1/chat/completions", {
method: "POST",
headers: {
Authorization: "Bearer " + process.env.OPENROUTER_API_KEY,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "novita/minimax/minimax-m2.5",
messages: [{ role: "user", content: "Hello" }],
}),
});
Python
import os, json, urllib.request
req = urllib.request.Request(
"https://openrouter.ai/api/v1/chat/completions",
data=json.dumps({"model": "novita/minimax/minimax-m2.5", "messages": [{"role": "user", "content": "Hello"}]}).encode(),
headers={"Authorization": "Bearer " + os.environ["OPENROUTER_API_KEY"], "Content-Type": "application/json"},
)
print(urllib.request.urlopen(req).read().decode())