Model

Mistral: Mistral Medium 3.5

Catalog snapshot from OpenRouter. This model is discoverable on-site even when it is not currently included in the global ranking list.

Data updated:

Data version: v20260601T114858Z Data size: 100

This model is currently available from the catalog snapshot and may not be included in the latest ranked board yet.

About this model

Mistral: Mistral Medium 3.5 is listed in our model catalog as a Multimodal model with 262,144 ctx and a snapshot average price around $4.50 per 1M tokens. The data below is generated from the latest catalog snapshot and integration examples are provided when an OpenRouter id is available.

You can also explore more models from Mistral AI , and browse more options from Unknown .

Key metrics

Rank
Not ranked
Kind
Multimodal
Core metric
262,144 ctx
1M tokens (avg)
$4.50
Vendor / team
Mistral AI
Origin
Unknown
License
Unknown
VRAM requirement

Hippo's Quick Action

OpenRouter chat completions URL; set Authorization and body per docs.

Price calculator

Est. monthly cost (USD):

Price comparison (snapshot)

Source / aggregator Price / 1M tokens
Snapshot average (board) $4.50

Figures come from the imported leaderboard snapshot; live aggregator pricing can change.

How to integrate

OpenRouter exposes an OpenAI-compatible Chat Completions endpoint. Use the tabs below to switch example languages. Replace the model id with the one from your provider page if you route elsewhere.

// Node.js 18+ — set OPENROUTER_API_KEY in your environment
const res = 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: "mistralai/mistral-medium-3-5",
    messages: [{ role: 'user', content: 'Hello' }],
  }),
});
const data = await res.json();
console.log(data);

Store API keys in environment variables or a secret manager—never commit them to source control.

Alternative picks

Pick one or two more models on global rankings and use Compare to view them side by side.

Run with Ollama

Paste into your terminal (install Ollama first):