Mixtral 8x7B Instruct — Mistral AI | Modeldex

Mixtral 8x7B Instruct

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Mixtral 8x7B Instruct is a pretrained generative Sparse Mixture of Experts, by Mistral AI, for chat and instruction use. Incorporates 8 experts (feed-forward networks) for a total of 47 billion...

Updated 4 days agoStructured data from Modeldex catalog

Budget

Knowledge cutoff

Dec 31, 2023(2.3 years ago)

API release

Dec 10, 2023(2.4 years ago)

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

Overview

Mixtral 8x7B Instruct is a pretrained generative Sparse Mixture of Experts, by Mistral AI, for chat and instruction use. Incorporates 8 experts (feed-forward networks) for a total of 47 billion...

History

Mixtral 8x7B Instruct became available via the Mistral AI API on 2023-12-10.

Training & availability

Training data has a knowledge cutoff of 2023-12-31 — information about events after that date is unlikely to appear in the model's responses. Mistral AI has not released the underlying model weights — access is via their hosted API only.

Capabilities

Context window: 32K tokens.
Input modalities: text.

Recommended for: cheap.

Limitations

The knowledge cutoff is 27 months old — this model will not know about recent events, releases, or API changes.
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.

Pricing

Input: $0.5400 per 1M tokens
Output: $0.5400 per 1M tokens

Use the cost calculator above to estimate monthly spend for your workload.

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/mixtral-8x7b-instruct",
    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

@ $0.54/1M

Output tokens / month2.0M

@ $0.54/1M

Input cost

$2.7

5.0M × $0.54/1M

Output cost

$1.08

2.0M × $0.54/1M

Total / month

$3.78

$45.36 / year

Providers & performance

1 provider

Multi-provider inference routes for this model — sorted by throughput. Latency is time-to-first-token; throughput is output tokens per second. Data from OpenRouter, measured over the last 30 minutes.

Provider	Throughput	Latency (TTFT)	Input $ / 1M	Output $ / 1M	Context	Quant	Supports
DeepInfra	138tok/s	288ms	$0.54	$0.54	33K	fp8	tools · json

Popularity

Signals from open-source communities — not a quality measure, but useful for gauging adoption among developers.

🤗

HuggingFace downloads

597.8K/ month

HuggingFace likes

4.7K

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.