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Model details

Ministral 3 8B 2512

Ministral 3 8B 2512 sits in the middle of Mistral's Ministral 3 family, positioned as a small but capable model that brings image understanding into a compact footprint. Third-party directories describe it as a balanced member of the line, built for efficient inference while still handling multimodal inputs, making it well suited to scenarios where lightweight deployment and visual reasoning both matter. The combination of text and image inputs in a small model opens up use cases such as document interpretation, UI analysis, and visual question answering without requiring a large flagship deployment.

Benchmark snapshots surfaced by directory listings suggest the model delivers solid general intelligence and coding ability for its size, with particularly competitive coding performance relative to other small models, while agentic tasks remain a more modest area. Design Arena results across website, code, game development, and 3D design indicate consistent creative and structural generation quality, reinforcing its fit for prototyping, content generation, and developer assistance workloads. A large context window further supports applications that need to reason over long documents, codebases, or extended multimodal sessions.

OpenRoutermistralai/ministral-8b-2512ministral

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Provider
OpenRouter
Model key
mistralai/ministral-8b-2512
Release date
Dec 2, 2025
Last updated
Dec 2, 2025
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.15
Output token cost
$0.15

Limits

Output tokens
209,715 tokens
Context window
262,144 tokens

Transparent token rates

Compare Ministral 3 8B 2512 pricing

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

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Latest news about Ministral 3 8B 2512

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CoverageBenchmark

Mistral: Ministral 3 8B 2512 was evaluated on the OpenOCR benchmark corpus (ocr-shared-11-normalized/v2, scorer ocr-shared-11-scorer/v2), achieving a 97.4% average score across 11 documents with all 11/11 scores reproducible. The benchmark was measured on 2026-08-07 and published on 2026-08-22, using the OpenRouter pro Per-document breakdowns show strong performance on structured text: 100% on a grocery receipt (1.8s latency, 446 chars returned vs 428 ground truth), 86.7% on a café receipt (1.3s), and 100% on both a handwritten letter (619ms, 177/177 chars) and handwritten notes (869ms). Average latency across the corpus is reported

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