Head to head

ArgosBrain vs Letta

Letta pays LLM on every read. ArgosBrain pays $0.

What Letta does
Tiered memory (core/archival/recall) where every read is an LLM tool call.
What ArgosBrain does differently
Deterministic, zero-token structural reads with no LLM on the hot path.
What Letta is

The baseline, stated fairly.

Letta (formerly MemGPT; Apache-2.0, Letta AI / Charles Packer) ships a tiered memory architecture — core (always in context), archival (vector-searchable), recall (message history) — with agent self-edits via tool calls.

Sleep-time compute performs background LLM summarization during idle time. Letta Code (March 2026) is their memory-first coding harness — #1 model-agnostic open-source agent on Terminal-Bench.

How it actually works

Technical facts.

Sources: Letta docs · Letta repo · Letta Code

Verdict

Where each one wins.

↑ Where ArgosBrain wins
  • $0/query vs LLM-per-read. This is the sharpest cost difference in the whole competitive set.
  • Deterministic reads. Letta's agent has to decide to search; ArgosBrain answers structurally.
  • No sleep-time compute cost. Our consolidation is a tokio task, not an LLM call.
  • Symbol precision.
↑ Where Letta wins
  • Agent Development Environment (ADE) — visual debugger, stateful agent graph.
  • Terminal-Bench #1 OSS (Letta Code) — a real number we don't match on full-agent benchmarks.
  • Richer agent loop (self-editing memory) is conceptually ambitious.
When to choose which

Honest recommendation.

Choose Letta if
  • You want a full agent framework
  • Built-in stateful memory
  • Token cost is not a concern
Choose ArgosBrain if
  • Memory layer any agent can use
  • Zero token cost at retrieval