per 1M tokens
MiniMax M2.7
novita/minimax/minimax-m2.7
MiniMax M2.7 is an all-around evolved, versatile open-source large language model that seamlessly blends hardcore engineering productivity with high-EQ, human-like interaction capabilities. In real-world software engineering, M2.7 excels by independently driving end-to-end project delivery while efficiently handling advanced tasks such as log analysis, bug troubleshooting, code security, and machine learning. In the professional workspace, it boasts the highest open-source GDPval-AA score (1495 ELO). It delivers high-fidelity, complex editing and multi-turn revisions across the Office suite (Excel, PPT, Word), elevating task execution to industry-leading standards. Built for complex environment interactions, M2.7 maintains an impressive 97% skill-following rate even with complex, long-context tool calls (>2000 tokens). Beyond its robust productivity, M2.7 breaks the "cold tool" stereotype of traditional models. With exceptional identity retention and high emotional intelligence (EQ), it not only empowers ent
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-m2.7. 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-m2.7","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-m2.7",
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-m2.7", "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())