LANGUAGE MODEL Arc Institute Last updated:

Evo 2

DNA Foundation Model at 1Mb Context

Arc Institute's Evo 2 — a 40-billion-parameter foundation model trained on 9.3 trillion nucleotides of DNA across all domains of life, with a million-base-pair context window. Predicts variant effects, generates novel functional sequences, and is the first DNA model at the scale of language frontier models. Published in Nature (March 2026).

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Cost
Free
Open weights — self-host
Context
1M
Up to 1,000,000 tokens
How are Intelligence, Speed & Cost bucketed?
Intelligence and Speed buckets are percentile ranks on Artificial Analysis. Cost buckets are fixed dollar thresholds keyed off output-token price ($/M out).
Intelligence
  • Top 1%≤ 1%
  • Top 5%≤ 5%
  • Top 10%≤ 10%
  • Good≤ 25%
  • Medium≤ 50%
  • Below avg> 50%
Speed
  • Top 1%≥ 345 tok/s
  • Top 5%≥ 237 tok/s
  • Top 10%≥ 196 tok/s
  • Good≥ 146 tok/s
  • Medium≥ 90 tok/s
  • Slow< 90 tok/s
Cost
  • Freeopen weights · self-host
  • Low< $1 / M out
  • Moderate$1–5 / M out
  • High≥ $5 / M out

Why it matters

First million-base-pair DNA model — long enough to capture full bacterial genomes in context. Combined with AlphaFold 3, ESM-3, and Boltz, defines the AI-for-biology foundation layer that all downstream therapeutic / agricultural / synbio work builds on.

Core Capabilities

Science
Built for biology, chemistry, materials, weather, or math research.
Generative
Produces images, video, audio, or other media.
Long Documents
Handles entire codebases, books, and multi-doc RAG.

Context Window

1M tokens
≈ entire codebase
4k Chat 聊天
32k Long docs 长文档
128k Books 整本书
400k Multi-doc 多文档
1M This model 本模型
10M

Availability

API
Not available
Product / App
Not available
Open Source
Released
Enterprise

Pricing Model

Free / self-host
Open weights — pay only for compute.
Self-host

What it feels like

  • Language model from Arc Institute — see the linked sources below for benchmark and review coverage

Best use cases

  • General-purpose tasks within Arc Institute's deployment footprint
  • See the model spec and sources block for benchmarked use cases

Not ideal for

  • Tasks far outside the modalities listed in this model's spec
  • Workflows where a more recent successor in the same family scores higher

Brixi, G. · Durrant, M. G. · Ku, J. · et al.