Mixtral 8x7B

Mistral Mixtral Generally Available Dec 2023

Mistral AI's original sparse MoE model — 46.7B total / 12.9B active params, Apache 2.0 licence, 32K context. Fast, cost-efficient, and one of the most widely deployed open-weight models.

Context
33K
tokens
Input
$0.54
per MTok
Output
$0.60
per MTok

Modalities

Input
Text Code
Output
Text Code

Code Examples

curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistralai/Mixtral-8x7B-v0.1",
    "messages": [
      { "role": "user", "content": "Explain quantum entanglement in one sentence." }
    ]
  }'

API Parameters

Name Type Description
frequency_penalty number Penalize tokens by their frequency so far. Positive values reduce repetition.
max_completion_tokens integer Maximum number of tokens the model may generate in the response.
presence_penalty number Penalize tokens that have appeared at all so far. Positive values encourage new topics.
response_format one of Constrain output to a JSON schema or an enum (structured outputs).
seed integer Deterministic seed for sampling. Same seed + same prompt produces identical output.
stop array Up to 4 sequences where the API will stop generating tokens.
stream boolean Stream partial responses as Server-Sent Events.
temperature number Sampling temperature; higher values produce more random output. 0 is deterministic.
tool_choice one of Controls which (if any) tool is called: "none", "auto", "required", or a specific tool.
tools array List of tools (functions) the model may call.
top_p number Nucleus sampling: consider only tokens whose cumulative probability ≥ top_p.

Standard OpenAI-compatible parameters. Consult the provider docs for model-specific behaviour.

Benchmark Scores

Benchmark Score
MMLU 70.6%
HumanEval 40.2%
MATH 28.4%

Performance

140
tok / sec
output speed

Source: Mixtral paper + Artificial Analysis, April 2026

Strengths & Limitations

Best For
Apache 2.0 — fully open weights
MoE efficiency at low inference cost
Strong multilingual (5 languages)
109K+ HuggingFace downloads
Limitations
32K context window
Outperformed by newer Mistral and Llama 4 models
Older training data

Tags

Open WeightsMoEFastCodingMultilingual