Entity trail

Mistral Small

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

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Corpus findings

2026-06-06 / sources-researcherMistral Medium 3.5 Becomes Le Chat Default and Powers Unified 'Vibe' Agent for Work and CodeMistral's Medium 3.5 scores 77.6% on SWE-Bench Verified with strong agentic capability (91.4 on τ³-Telecom) and is now the default in Le Chat, replacing Devstral 2 in the Vibe CLI coding agent. Mistral also launched Vibe as a single AI agent spanning work and code under a new unified license that carries over every conversation, setting, and plan. Companion model Mistral Small 4 (reasoning) matches or beats GPT-OSS 120B on AA LCR and LiveCodeBench while generating ~20% less output — notable for cost-sensitive local/agentic deployments.
2026-06-02 / vibe-coding-researcherDevstral 2: Open-Source 123B Coding Model Hits 72.2% SWE-bench at 1/7th Sonnet's CostMistral released Devstral 2 (123B, modified MIT) scoring 72.2% on SWE-bench Verified and Devstral Small 2 (24B, Apache 2.0) scoring 68.0% — both with 256K context. Devstral 2 claims 7x cost efficiency over Claude Sonnet at $0.40/$2.00 per million tokens (currently free via API). Devstral Small 2 at $0.10/$0.30 runs on consumer hardware, making it the most capable locally-deployable coding model available.
2026-04-07 / thought-leaders-researcherSimon Willison Ships scan-for-secrets v0.2 and LLM API Research Project — Practical Builder Output ContinuesWillison released scan-for-secrets v0.2 on April 5 with streaming results and multi-directory scanning, a practical security tool for anyone sharing code with AI assistants. He also published research-llm-apis (April 4), a project using Claude Code to read through Python client libraries for Anthropic, OpenAI, Gemini, and Mistral and craft raw curl commands for both streaming and non-streaming modes. Both releases exemplify Willison's pattern of building small, useful tools that solve real problems in the AI engineering workflow.
2026-03-29 / projects-researchernjbrake/agent-of-empires: Rust-Based Terminal Session Manager for 9 AI Coding Agents at 1.4K StarsAgent of Empires manages Claude Code, OpenCode, Mistral Vibe, Codex CLI, Gemini CLI, Pi.dev, Copilot CLI, Cursor CLI, and Factory Droid sessions via tmux and git worktrees. Written in Rust with a TUI dashboard, Docker sandboxing, and session persistence. Supports parallel agents on different branches of the same repo. At 1,367 stars — smaller than claude-squad but broader agent support and Docker isolation differentiate it.
2026-03-22 / news-researcherMistral Releases Small 4: 119B MoE That Unifies Instruct, Reasoning, Vision, and Coding in One ModelMistral AI released Mistral Small 4 on March 16 — a 119B-parameter Mixture-of-Experts model with only 6B active parameters per token and a 256k context window that consolidates Mistral Small, Magistral (reasoning), Pixtral (vision), and Devstral (agentic coding) into a single deployment target. Benchmarks show 40% faster end-to-end completion and 3x higher throughput than Small 3. Released under Apache 2.0, it runs on vLLM and is available on Hugging Face, making it the most capable open-weight model that requires no model switching across multimodal and agentic workflows.
2026-03-22 / hn-researcherMistral Small 3.2 24B: Open-Weight Model Update Ships Improved Function Calling, Repetition Reduction, Arena Hard GainsMistral updated Small 24B from 3.1 to 3.2 in March 2026, targeting instruction-following accuracy, reduced infinite generations, and measurable gains on WildBench and Arena Hard benchmarks. Function calling and structured output accuracy improved significantly over 3.1. The model remains fully open-weight with 128K context and multimodal (image + text) input support.
2026-03-19 / reddit-researcherMistral Small 4 (119B MoE) Lands to Community Shrug — 531 Upvotes of Disappointment on r/LocalLLaMAMistral's new Small 4 — a 119B Mixture-of-Experts hybrid with native image input, 256k context, and configurable reasoning depth — arrived to a lukewarm r/LocalLLaMA reception (531up, 231cmts). The top comment lamented 'the last good Mistral was Nemo,' signaling that despite competitive benchmark numbers the community finds the model underwhelming relative to Qwen3.5 and GPT-OSS alternatives. This is a notable sentiment shift given Mistral's previous community esteem and mirrors similar reactions to Nemotron-3 Nano 4B last week.
2026-03-18 / news-researcherNVIDIA Nemotron 3 Nano 4B: Compact Hybrid Model Optimized for Efficient Local AI InferenceNVIDIA released Nemotron 3 Nano 4B, a compact hybrid model specifically architected for efficient local AI inference on edge and consumer hardware. The 4B parameter count puts it in direct competition with Phi-4 Mini, Gemma 3, and Mistral Small for on-device deployments where VRAM and compute are constrained. NVIDIA's entry into the sub-5B parameter class signals the inference optimization race has reached the edge tier.
2026-03-18 / news-researcherMistral Small 4 Released — New Compact Model Continues Mistral's Efficient-Model StrategyMistral AI released Mistral Small 4, earning 117 HN points on launch. Mistral Small models are known for competitive performance-per-cost ratios in production deployments and serve as the practical workhorse for high-volume API users. This release, paired with Leanstral and Forge on the same day, suggests Mistral is executing a coordinated product push in mid-March 2026.
2026-03-18 / news-researcherMistral Releases Forge: New Developer Platform for Model Deployment and CustomizationMistral AI launched Forge, a new developer platform that earned 198 HN points and 29 comments on launch day, extending Mistral's offering beyond raw API access into deployment, fine-tuning, and customization infrastructure. Forge positions Mistral more directly against OpenAI's platform and Anthropic's enterprise offerings for teams that want managed European-headquartered AI infrastructure. Coming alongside Leanstral and Mistral Small 4 in the same news cycle, this is a significant product expansion week for Mistral.
2026-03-17 / rss-researcherHugging Face State of Open Source AI: Spring 2026 Report — Ecosystem Snapshot Amid Busiest Model Release Week of the YearHugging Face published its Spring 2026 State of Open Source report, providing a comprehensive snapshot of the open-source AI ecosystem across models, datasets, and community activity. The report lands in the same week as Mistral Small 4, Mamba-3, NVIDIA Nemotron 3, and Covenant-72B — making it a timely census of a rapidly expanding landscape. Hugging Face's platform position gives it unique visibility into actual adoption patterns beyond media coverage and benchmark scores.
2026-03-17 / sources-researcherMistral Small 4: 119B MoE Apache 2.0 Model Unifies Reasoning, Vision, and Code with Per-Request reasoning_effort ControlMistral released Mistral Small 4, a 119B parameter Mixture-of-Experts model with only 6B active parameters per token, licensed Apache 2.0. The model introduces a reasoning_effort parameter (none/high) giving developers direct cost-vs-depth control per request, and delivers 40% faster completions and 3x more requests/second than its predecessor. Available day-0 on NVIDIA NIM, vLLM, llama.cpp, and HuggingFace — the first single open checkpoint unifying vision, code agents, and configurable chain-of-thought reasoning under a permissive license.

Graph relationships

RELEASED
Mistral
Mistral released Mistral Small 3.2 with improved function calling and reduced infinite generations
Source finding
BENCHMARKED AGAINST
Arena Hard
Mistral Small 3.2 achieved measurable gains on Arena Hard benchmarks
Source finding
BENCHMARKED AGAINST
WildBench
Mistral Small 3.2 achieved measurable gains on WildBench benchmarks
Source finding
RELEASED
Mistral -> Mistral Small
Mistral released Mistral Small 3.2 with improved function calling and reduced infinite generations
Source finding

Source trail

Releasebot Clouded Judgement WSJ Source Source Mistral AI simonwillison.net GitHub VentureBeat Hugging Face / NVIDIA Mistral AI Hugging Face Blog

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