Authenry

Work

Research & strategy2026

Open models

Open-weight language models compared on capability, licensing and deployment.

Benchmark scores of four open-weight modelsDrawn from p. 9
MMLUGPQA DiamondHumanEvalMATH
Llama 3.3 70BDense 70B, 128K8650.588.477
Qwen 2.5 72BDense 72B, 128K86.149.888.276.8
DeepSeek V3MoE 671B, 128K87.552.189.380.2
Falcon 3 10BDense 10B, 32K68.531.265.424.7

Recommended in the report

Findings

  1. 01

    The distinction between true open-source software, as defined by the Open Source Initiative, and open-weights releases carries significant implications for vendor lock-in, legal indemnification, and algorithmic auditability.p. 2

Language models
  1. From the report

    A model possesses no practical utility if it cannot be served with acceptable latency, high concurrency, and economic efficiency.p. 14

    Memory needed to serve a large modelDrawn from p. 14
    Seventy-billion parameter model at half-precisionapproximately 140 gigabytes
    671-billion parameter modelexceed 360 gigabytes

Start a conversation

It is about

Write to us