Mistral 7B — Mistral AI | Modeldex

Mistral 7B

Active

Compact open-weights model that outperforms Llama 2 13B on many benchmarks.

Updated 3 days agoStructured data from Modeldex catalog

Open source

Not enough benchmark coverage yet for an Intelligence Index — needs at least 3 results across 2 categories.

Overview

Mistral 7B uses grouped-query attention and sliding-window attention to punch well above its weight at 7 billion parameters. Apache-2.0 licensed.

History

Mistral 7B was released on 2023-09-27.

Training & availability

Weights are publicly available under the Apache-2.0 license, making this an open-weight model suitable for on-prem deployment and fine-tuning.

Capabilities

Context window: 32K tokens.
Max output: 8K tokens.
Input modalities: text.

Recommended for: open-source.

Limitations

The context window (32K tokens) is modest by 2026 standards — unsuitable for processing long documents in a single request.
Text-only — cannot process images, audio, or video inputs.

Quick start

Minimal example using the OpenRouter API. Copy, paste, replace the key.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="sk-or-...",
)
resp = client.chat.completions.create(
    model="mistral/mistral-7b",
    messages=[{"role": "user", "content": "Explain quantum computing in one sentence."}],
)
print(resp.choices[0].message.content)

Cost calculator

Estimate your monthly bill. Presets are typical workload sizes.

Input tokens / month5.0M

@ $0.11/1M

Output tokens / month2.0M

@ $0.19/1M

Input cost

$0.55

5.0M × $0.11/1M

Output cost

$0.38

2.0M × $0.19/1M

Total / month

$0.93

$11.16 / year

Integrations & tooling support

Tool calling: Not supported
Structured outputs: Not supported

Price vs quality

Budget pricing

Priced low — good for high-volume tasks. Quality tier pending more benchmark coverage.