Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed...
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Measured against all 392 chat models CoreAI serves, Mistral: Mistral Small 3 sits at #367 for context capacity — 33K tokens, roughly 24,576 words or 49 pages of text in a single conversation. On price, it is the #16 cheapest of 128 budget-tier models by input cost. It joined the catalog on 2025-01-30.
Every model in this table is available on CoreAI — open the web app and run the same prompt through Mistral: Mistral Small 3 and Mistral: Mistral Nemo side by side to judge with your own eyes.
A typical question (about 1,000 tokens in, 500 out) runs $0.00009 on Mistral: Mistral Small 3's raw per-token rates; a heavy session with a 50K-token document costs about $0.003. On CoreAI you don't juggle these numbers — one subscription covers Mistral: Mistral Small 3 and 300+ other models under a plan usage limit, with no API keys. See plans.
Mistral: Mistral Small 3 handles 33K tokens of context — roughly 24,576 words, or about 49 pages of text in one conversation.
Mistral: Mistral Small 3's underlying rates are $0.05 per 1M input tokens and $0.08 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: Mistral Small 3 is text-only. If you need image understanding, its budget-tier peers with vision are listed in the comparison table above.
No — Mistral: Mistral Small 3 answers directly without an extended reasoning phase, which usually means faster responses.
Open the CoreAI web app or the iOS/Android app, pick Mistral: Mistral Small 3 in the model selector, and chat — no API key, no per-token billing. One subscription covers Mistral: Mistral Small 3 and 300+ other models.
The closest alternatives on CoreAI are Mistral: Mistral Nemo, Google: Gemma 3n 4B, inclusionAI: Ling-2.6-flash — 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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