La Plateforme
la-plateforme-1d3130c5·14 events·first seen 1mo agoAliases: La Plateforme
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Mistral AI Launches La Plateforme: First API Endpoints in Early Access
Mistral AI opened beta access to its first developer platform, La Plateforme, offering three generative text endpoints (mistral-tiny, mistral-small, mistral-medium) and an embedding endpoint. Mistral-tiny serves Mistral 7B Instruct v0.2, mistral-small serves Mixtral 8x7B, and mistral-medium serves an unreleased prototype model scoring 8.6 on MT-Bench. The platform also introduces Mistral-embed with a 1024-dimension embedding model achieving 55.26 on MTEB. The API follows OpenAI-compatible chat interface specifications and is ramping toward general availability.
Mistral AI Announces Fine-Tuning for Flagship Models, Agents Alpha, and SDK 1.0
Mistral AI has announced three platform updates: fine-tuning support for all flagship and specialist models on La Plateforme (including Mistral Large 2 and Codestral), an alpha release of an Agents feature enabling custom workflows via Le Chat or API, and a stable 1.0 release of the mistralai Python and TypeScript SDK. Fine-tuning supports base prompts, few-shot prompting, and full fine-tuning with custom datasets. The Agents feature is described as early-stage, with tool and data-source integrations planned.
Mistral AI Launches Model Customization Suite: Open-Source SDK, Managed Fine-Tuning, and Custom Training
Mistral AI has introduced three tiers of model customization on la Plateforme: an open-source LoRA-based fine-tuning SDK (mistral-finetune) for self-hosted use, serverless managed fine-tuning services via API initially supporting Mistral 7B and Mistral Small, and bespoke custom training services including continuous pretraining for enterprise customers. The managed fine-tuning uses LoRA adapters and claims cost and efficiency advantages over full fine-tuning while maintaining comparable performance. This positions Mistral as a full-stack customization provider competing with OpenAI's fine-tuning API and similar offerings.
Mistral Launches Batch API at 50% Cost Reduction
Mistral AI has released a batch API on La Plateforme that processes high-volume asynchronous requests at 50% lower cost than synchronous API calls. Users upload a batch file, wait for processing, then download results. The API supports all models on La Plateforme with a limit of 1 million ongoing requests per workspace, and is positioned as a response to recent API price hikes from competitors.
Mistral AI Releases Mistral Small v24.09, Free API Tier, and Pixtral 12B Vision on le Chat with Broad Price Cuts
Mistral AI announced a multi-part release on September 17, 2024: a free tier for la Plateforme API, significant price reductions across its model family (up to 80% for Mistral Small and Codestral), an updated Mistral Small v24.09 (22B parameters, improved alignment and reasoning), and the availability of Pixtral 12B vision capabilities on le Chat. Pixtral 12B, released under Apache 2.0, supports images of any size without text performance degradation and is now accessible for free on le Chat. The pricing updates also apply to cloud partner deployments on Azure AI Studio, Amazon Bedrock, and Google Vertex AI.
Mistral AI Releases Mistral Large, Claims Second-Best API Model After GPT-4
Mistral AI has released Mistral Large, its most capable model to date, claiming second place among API-accessible models behind GPT-4 on standard benchmarks including MMLU, HellaSwag, and coding/math evals. The model features a 32K context window, native fluency in five European languages, function calling, and constrained output mode. Simultaneously, Mistral is launching a new Mistral Small optimized for latency, restructuring its endpoint lineup, and announcing Microsoft Azure as its first major distribution partner. This marks Mistral's first significant commercial partnership and expansion beyond its own infrastructure.
Mistral AI Releases Magistral: First Reasoning Model in Open and Enterprise Variants
Mistral AI announces Magistral, its first reasoning model, released in two variants: Magistral Small (24B parameters, open-weight, Apache 2.0) and Magistral Medium (enterprise, closed). Magistral Medium scores 73.6% on AIME2024 (90% with majority voting @64), while Magistral Small scores 70.7% (83.3% respectively). Key differentiators include native multilingual chain-of-thought reasoning across eight major languages, transparent traceable reasoning steps, and up to 10x faster token throughput in Le Chat via Flash Answers. The release is accompanied by a research paper covering training infrastructure, reinforcement learning algorithm, and novel observations for training reasoning models.
Mistral Large 2 (123B): New Frontier Model with 128k Context, Multilingual and Code Capabilities
Mistral AI releases Mistral Large 2, a 123-billion-parameter model with a 128k context window, supporting 80+ coding languages and over a dozen natural languages. The model claims competitive performance with GPT-4o, Claude 3 Opus, and Llama 3 405B on code generation, reasoning, and multilingual benchmarks, while targeting cost-efficient single-node inference. Weights are available under a Mistral Research License for non-commercial use, with a commercial license required for self-deployment. The model is accessible via Mistral's la Plateforme API (mistral-large-2407), HuggingFace, and Google Cloud Vertex AI.
Mistral AI Releases Mathstral 7B: Math-Specialized Model with SOTA Reasoning in Size Category
Mistral AI has released Mathstral 7B, a math and STEM-specialized model built on Mistral 7B, developed in collaboration with Project Numina. The model achieves 56.6% on MATH and 63.47% on MMLU in standard evaluation, improving to 74.59% on MATH with a reward model over 64 candidates using inference-time compute scaling. Weights are open on HuggingFace and compatible with mistral-inference and mistral-finetune tooling.
Mistral AI Releases Ministral 3B and 8B Edge Models
Mistral AI has introduced two new small language models, Ministral 3B and Ministral 8B, targeting on-device and edge computing use cases. Both models support up to 128k context length and claim state-of-the-art performance in the sub-10B parameter category, outperforming comparable models from Google and Meta on internal benchmarks. Ministral 8B features an interleaved sliding-window attention mechanism for memory-efficient inference and is priced at $0.1/M tokens via API, while Ministral 3B is priced at $0.04/M tokens. Weights for Ministral 8B Instruct are available for research use, with commercial licensing available on request.
Mistral Small 3: 24B Latency-Optimized Open-Weight Model Released Under Apache 2.0
Mistral AI has released Mistral Small 3, a 24B-parameter instruction-tuned model optimized for low latency, achieving over 81% on MMLU at 150 tokens/s on a single GPU. The model is competitive with Llama 3.3 70B and Qwen 32B while being more than 3x faster on equivalent hardware, and is released under Apache 2.0 for both pretrained and instruction-tuned checkpoints. It is explicitly not trained with RL or synthetic data, positioning it as a base model for community fine-tuning and reasoning capability development. Deployment targets include local inference on consumer hardware (RTX 4090, MacBook 32GB RAM), agentic function calling, and domain-specific fine-tuning.
Mistral OCR: New Document Understanding API with State-of-the-Art Benchmark Performance
Mistral AI has released Mistral OCR, an Optical Character Recognition API designed for deep document understanding, handling text, tables, equations, images, and complex layouts from PDFs and images. The model claims top benchmark scores across math, multilingual, scanned, and table categories, outperforming Google Document AI, Azure OCR, Gemini 1.5/2.0, and GPT-4o on an internal test set. It is priced at 1000 pages per dollar (with batch inference doubling that), available via la Plateforme API today, and is already deployed as the default document understanding model in Le Chat. A selective self-hosting option is offered for organizations with sensitive data requirements.
Mistral AI Releases Mixtral 8x22B Under Apache 2.0
Mistral AI has released Mixtral 8x22B, a sparse Mixture-of-Experts model with 141B total parameters but only 39B active parameters, under the permissive Apache 2.0 license. The model features a 64K token context window, native function calling, multilingual support across five European languages, and strong math and coding performance. Mistral claims it outperforms all other open-weight models on standard benchmarks while being faster than dense 70B models due to sparse activation. An instructed version achieves 90.8% on GSM8K maj@8.
Mistral AI Releases Codestral: 22B Open-Weight Code Generation Model
Mistral AI has released Codestral, a 22B open-weight model explicitly designed for code generation, supporting 80+ programming languages with a 32k context window. The model is available under a non-production license on HuggingFace, with commercial licenses available on request, and is accessible via a dedicated API endpoint (codestral.mistral.ai) free during an 8-week beta. Codestral claims state-of-the-art performance on RepoBench, HumanEval, and fill-in-the-middle benchmarks, outperforming DeepSeek Coder 33B and matching or exceeding GPT-4-Turbo on some language-specific evals. Integrations are available with LlamaIndex, LangChain, Continue.dev, and Tabnine for IDE-based developer workflows.