Ministral 8B is an 8B parameter model featuring a unique interleaved sliding-window attention pattern for faster, memory-efficient inference. Designed for edge use cases, it supports up to 128k context length...
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Mistral: Ministral 8B holds the #326 spot for context size out of 400 chat models in the CoreAI catalog — 128K tokens, roughly 96,000 words or 192 pages of text in a single conversation. On price, it is the #69 cheapest of 125 budget-tier models by input cost. It joined the catalog on 2024-10-17.
Every model in this table is available on CoreAI — open the web app and run the same prompt through Mistral: Ministral 8B and Mistral: Ministral 3 3B 2512 side by side to judge with your own eyes.
A typical question (about 1,000 tokens in, 500 out) runs $0.00016 on Mistral: Ministral 8B's raw per-token rates; a heavy session with a 50K-token document costs about $0.006. On CoreAI you don't juggle these numbers — one subscription covers Mistral: Ministral 8B and 300+ other models under a plan usage limit, with no API keys. See plans.
Mistral: Ministral 8B handles 128K tokens of context — roughly 96,000 words, or about 192 pages of text in one conversation.
Mistral: Ministral 8B's underlying rates are $0.11 per 1M input tokens and $0.11 per 1M output tokens. On CoreAI it is included in one subscription alongside 300+ models, so there is no per-token billing to manage.
No — Mistral: Ministral 8B is text-only. If you need image understanding, its budget-tier peers with vision are listed in the comparison table above.
No — Mistral: Ministral 8B answers directly without an extended reasoning phase, which usually means faster responses.
Open the CoreAI web app or the iOS/Android app, pick Mistral: Ministral 8B in the model selector, and chat — no API key, no per-token billing. One subscription covers Mistral: Ministral 8B and 300+ other models.
The closest alternatives on CoreAI are Mistral: Ministral 3 3B 2512, Qwen: Qwen3 30B A3B Instruct 2507, IBM: Granite 4.0 Micro — similar tier and capability. The fastest way to choose is running one prompt through them side by side in CoreAI's Compare view.
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