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Model Detail

mistralai logo

Mistral-Small-4-119B-2603

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Provider: MistralCategory: otherParameters: 119B
DB Score
0.1
Downloads
58K
Likes
372
Day
+0.0%
Week
+0.0%
Month
+0.0%
Overview

Mistral-Small-4-119B-2603 is an AI model with 119B parameters released by Mistral. And supports text+image->text inputs, distributed under the permissive apache-2.0 license.

Pricing & Throughput

Mistral-Small-4-119B-2603 is priced at $0.15/M input tokens and $0.6/M output tokens. Operationally the model offers a 262K-token context window, which matters when sizing it for prompt-heavy or latency-sensitive workloads. At this input rate the model sits in the commodity tier and is suitable for high-volume workloads where per-call cost dominates the decision.

Technical

Mistral-Small-4-119B-2603 ships with 119B parameters. Total weight footprint is approximately 119.4 GB, which is the relevant figure when planning local-inference VRAM. The apache-2.0 license is permissive, allowing commercial deployment and derivative work without per-seat fees, though attribution requirements still apply.

Use Cases

Mistral-Small-4-119B-2603 is best fit for general-purpose AI workloads, high-volume batch jobs where per-call cost dominates the budget, and long-context tasks such as full-codebase analysis or book-length summarization (262K tokens). Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.

Download History
Pricing
Input ($/M tokens)
$0.15
Output ($/M tokens)
$0.6
Context Window
262K
Research Paper
arXiv: 2310.06825→
Model Info
Licenseapache-2.0
Modalitytext+image->text
Citations3,836 (442 influential)
Recent newsView all news →
Related News
techcrunchneutral85d ago

Mistral is rumored to be raising €3B at €20B valuation

The funding round would value the company at around €20 billion (about $23.15 billion), nearly double its Series C valuation of €11.7 billion.

arxiv121d ago

Making Knowledge Accessible: Divergent Readability-Accuracy Strategies of Mistral and QWen in Biomedical Text Simplification

arXiv:2511.05080v4 Announce Type: replace Abstract: The growing public demand for accessible biomedical information calls for scalable text simplification. While large language models (LLMs) offer solutions, they too struggle with balancing improved readability against preservation of meaning. This

arxivneutral141d ago

Benchmarking Linguistic Adaptation in Comparable-Sized LLMs: A Study of Llama-3.1-8B, Mistral-7B-v0.1, and Qwen3-8B on Romanized Nepali

arXiv:2604.14171v1 Announce Type: new Abstract: Romanized Nepali, the Nepali language written in the Latin alphabet, is the dominant medium for informal digital communication in Nepal, yet it remains critically underresourced in the landscape of Large Language Models (LLMs). This study presents a sy

techcrunch159d ago

Mistral AI raises $830M in debt to set up a data center near Paris

Mistral aims to start operating the data center by the second quarter of 2026.

techcrunch163d ago

Mistral releases a new open source model for speech generation

The model, which lets enterprises build voice agents for sales and customer engagement, puts Mistral in direct competition with the likes of ElevenLabs, Deepgram, and OpenAI.

huggingface776d ago

WWDC 24: Running Mistral 7B with Core ML

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