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Model details

Mistral Large 3

Mistral Large 3 was announced on December 2, 2025 as part of the Mistral 3 generation and is positioned as Mistral's most capable model to date. It is a sparse mixture-of-experts architecture trained with 41 billion active parameters and 675 billion total parameters, marking Mistral's return to MoE design after the Mixtral series. The model is released under the Apache 2.0 license, placing it among frontier instruction-fine-tuned open-weight options. Mistral describes it as achieving parity with the best instruction-tuned open-weight models on general prompts while adding image understanding capability.

For practical deployment, Mistral Large 3 is available across multiple routing options including Cortecs, Mistral AI direct, and OpenRouter, allowing teams to compare latency and throughput on the same underlying weights. Independent inference benchmarks have flagged a recent time-to-first-token increase on the Cortecs-hosted endpoint, suggesting developers with latency-sensitive workloads should verify routing before committing to that path. The combination of a sparse MoE design, open weights, and broad multimodal support makes the model a flexible choice for teams that want frontier-class instruction following with the freedom to self-host or select alternative inference providers.

Cortecsmistral-large-2512mistral-large

Quick Info

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Provider
Cortecs
Model key
mistral-large-2512
Release date
Dec 2, 2025
Last updated
Dec 2, 2025
Knowledge cutoff
2024-11
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.613
Output token cost
$1.838

Limits

Output tokens
256,000 tokens
Context window
256,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about Mistral Large 3

Cortecs

CoverageBenchmark

InferenceBench.dev reports a fresh operational signal for Mistral Large 3 on Cortecs: TTFT (time-to-first-token) increased 36% within the last ~22 hours, suggesting a latency regression developers may want to verify before routing latency-sensitive workloads through the Cortecs-hosted endpoint. The same benchmark surfa The Mistral Large 3 model page on InferenceBench.dev aggregates per-provider latency, throughput, and reliability metrics, framing Cortecs alongside OpenRouter, Mistral AI direct, and others as routing options. While the Cortecs route label is truncated in the excerpt, the +36% TTFT movement is the most actionable data

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