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Open weightsHugging Face/10 trustVerified

SmolLM3

Fully open 3B multilingual reasoner with a published training recipe

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About

SmolLM3 is Hugging Face's 3-billion-parameter open language model, released in July 2025 under Apache 2.0 with the full training recipe published alongside the weights. It was trained on 11.2 trillion tokens, reasons in a dual mode that can be toggled with /think and /no_think flags, and supports six languages plus tool calling. At 3B it runs on consumer hardware without a dedicated GPU, though its reasoning depth and factual reliability trail much larger models.

Specs

Context window

128K

Pricing

Free quota

API access

Weights

Open weights

Released

July 8, 2025

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

on-device assistantsmultilingual chatreasoning prototypestool-calling agents

Trust score — 8/10

/10 trustVerified

Scored 8/10 (verified tier, metrics-v1). Evidence: Released 2025-07-08 by Hugging Face under Apache 2.0 with the full training recipe (data mixture, configs) published; 3.08B params, trained on 11.2T tokens; 64K trained context, 128K via YaRN; Dual-mode reasoning (/think, /no_think) and native tool calling verified from multiple writeups; Benchmark figures not collected this session; entry makes no benchmark claims. License: Apache-2.0 confirmed across sources..

How the trust score is built

Full methodology →
Adoption · stars/downloads, log-scaled vs peers
8.0/10
Maintenance · recency, releases, issue load
9.0/10
Openness · license + docs
10.0/10
Manual review · sanity read + red-flag check
7.0/10
  • · Released 2025-07-08 by Hugging Face under Apache 2.0 with the full training recipe (data mixture, configs) published
  • · 3.08B params, trained on 11.2T tokens; 64K trained context, 128K via YaRN
  • · Dual-mode reasoning (/think, /no_think) and native tool calling verified from multiple writeups
  • · Benchmark figures not collected this session; entry makes no benchmark claims

Sources