Mistral Large 3 API
Mistral AI
Mistral Large 3
About Mistral Large 3
Mistral Large 3 is a language model developed by Mistral AI. It's particularly well-suited for analyzing images, screenshots, and visual content, orchestrating tool-using agents that call APIs and external services, producing structured outputs for reliable data extraction, and handling large contexts of up to 256K tokens. Its 256K-token context window means you can pass in entire documents, codebases, or conversation histories without losing context.
As of Oct 1, 2026, Mistral Large 3 costs $0.022 per 1M input tokens and $0.066 per 1M output tokens on Qubax, versus $0.500 / $1.50 on OpenRouter (96% less on input). A typical 1,000 chat requests (2K tokens in, 500 out) come to about $0.08. Measured availability over the last 7 days: 100.0%. 29 independent compute providers currently serve it, so requests fail over automatically. It handled 306 requests on Qubax in the last 24 hours. Pay with USDC, USDT, BTC, ETH or 200+ other coins — no credit card required.
Pricing
| Token Type | Qubax | OpenRouter | You Save |
|---|---|---|---|
| Input (per 1M tokens) | $0.022 | $0.500 | 96% |
| Output (per 1M tokens) | $0.066 | $1.50 | 96% |
| Cache read (per 1M tokens) | $0.0022 | — | — |
Prices per 1 million tokens. Pay with 200+ cryptocurrencies. Cache read is the discounted rate providers offer for repeated prompt prefixes.
Price History (60 Days)
This model's price over the last 60 days. Compare against all top AI models →
Estimated Monthly Cost
Specifications
Use Cases
Capabilities
Quick Start
from openai import OpenAI
client = OpenAI(
base_url="https://api.qubax.ai/v1",
api_key="qbx_live_YOUR_API_KEY",
)
response = client.chat.completions.create(
model="mistral-large-3",
messages=[
{"role": "user", "content": "Hello!"}
],
)
print(response.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.qubax.ai/v1",
apiKey: "qbx_live_YOUR_API_KEY",
});
const response = await client.chat.completions.create({
model: "mistral-large-3",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);curl https://api.qubax.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer qbx_live_YOUR_API_KEY" \
-d '{
"model": "mistral-large-3",
"messages": [{"role": "user", "content": "Hello!"}]
}'Get your API key from the dashboard.
Why use Mistral Large 3 on Qubax?
96% Cheaper
Up to 96% off OpenRouter prices
Pay with Crypto
200+ coins (BTC, ETH, SOL, USDT, USDC & more). No credit card needed.
OpenAI Compatible
Drop-in replacement. Works with Cline, Cursor, any tool.
More from Mistral AI
Compare Mistral Large 3 with alternatives
| Model | Provider | Input / 1M | Output / 1M | vs Mistral Large 3 |
|---|---|---|---|---|
| Mistral Large 3 | Mistral AI | $0.022 | $0.066 | — |
| Meta: Muse Spark 1.2 Contributor | Meta | $0.037 | $0.075 | More expensive |
| DeepSeek V4.1 Flash | DeepSeek | $0.035 | $0.126 | More expensive |
| Llama 3.3 70B | Meta | $0.022 | $0.070 | Cheaper |
| Qwen 3.8 Max | Alibaba | $0.037 | $0.113 | More expensive |
Frequently Asked Questions
How much does the Mistral Large 3 API cost?
On Qubax, Mistral Large 3 costs $0.022 per 1M input tokens and $0.066 per 1M output tokens. This is 96% cheaper than OpenRouter's price of $0.500 per 1M input tokens.
Is the Mistral Large 3 API compatible with OpenAI?
Yes. Qubax provides an OpenAI-compatible API. You can use Mistral Large 3 as a drop-in replacement by changing your base URL to https://api.qubax.ai/v1 and using your Qubax API key. It works with Cline, Cursor, OpenCode, Hermes Agent, and any tool that supports OpenAI APIs.
Why is Mistral Large 3 cheaper on Qubax than OpenRouter?
Qubax sources AI inference from an open compute marketplace on the Base blockchain where GPU providers compete on price. We pass the savings to you — 96% cheaper than OpenRouter's price for Mistral Large 3.
How do I pay for Mistral Large 3 API usage?
Qubax uses prepaid crypto credits. Deposit USDC on the Base chain and your balance is automatically deducted as you use the API. No credit card required. Top up from $3.
What is the context window of Mistral Large 3?
Mistral Large 3 supports a context window of 256K tokens, allowing you to process large documents, codebases, or long conversations in a single request.
What can I build with Mistral Large 3?
Mistral Large 3 is versatile enough for a wide range of applications. You can use it to analyze images and visual content, build autonomous agents that call external tools and APIs, generate structured JSON output for data pipelines, process long documents and entire codebases, and more. Because it's served through Qubax's OpenAI-compatible API, integration into existing apps, agents, or workflows takes just a few lines of code.
How fast is Mistral Large 3 on Qubax?
Mistral Large 3 on Qubax supports streaming responses, so tokens begin arriving in real time as they're generated. Latency depends on the provider and prompt complexity. Qubax routes requests through an intelligent routing layer, which selects the fastest available compute provider for each request — so you get competitive latency at a lower price.
Mistral Large 3 vs Meta: Muse Spark 1.2 Contributor: which should I choose?
Mistral Large 3 by Mistral AI and Meta: Muse Spark 1.2 Contributor by Meta are both strong models in a similar price tier. Mistral Large 3 and supports vision/image inputs. Meta: Muse Spark 1.2 Contributor comes from a different lab and may have different strengths depending on your workload. On Qubax, Mistral Large 3 starts at $0.022/1M input tokens versus Meta: Muse Spark 1.2 Contributor's $0.037/1M — making Mistral Large 3 the more cost-effective option for high-volume workloads. Both are available on Qubax with crypto payments and OpenAI-compatible APIs, so you can try each and switch freely.
Can I use Mistral Large 3 for commercial projects?
Yes. Mistral Large 3 on Qubax can be used for commercial purposes. You own the outputs you generate. Qubax provides the API infrastructure — you bring your use case.
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