Can a Cheap Model Beat a Frontier Model? Rebuilding Recursive Language Models with Codex

Large language models have enormous context windows now. That does not mean they use all of that context reliably. As prompts grow, models can miss details, lose track of relationships, or produce plausible summaries instead of doing the exhaustive work a question requires. The Recursive Language Models (RLM) paper proposes a different interface: keep the large context outside the model, expose it as a variable in a persistent programming environment, and let the model inspect, partition, and recursively query smaller pieces. We rebuilt that method with an unusual constraint: no OPENAI_API_KEY ; Codex CLI as the model backend; gpt-5.4-mini for both the RLM root and every subcall; a direct frontier model only as a separate baseline. The result was encouraging, expensive, and more nuanced than “cheap model equals frontier model.” What an RLM changes A normal model call looks roughly like this: large prompt -> model -> answer An RLM instead gives the root model metadata about the input and a Python REPL containing the real context: question | root model | persistent REPL holding the context |-- inspect and search with code |-- split context into useful chunks |-- call smaller LMs over those chunks |-- validate and aggregate results `-- return the final answer The important detail is that the root model does not need to carry every document, record, tool result, and partial answer in its own context window. Large intermediate values can remain in REPL variables. Subcalls receive focused, locally understandable tasks. That makes RLM less like a bigger prompt and more like an out-of-core data-processing system whose semantic operator happens to be a language model. What we actually tested We used an OOLONG trec_coarse validation example from the protocol described in the RLM work. The input was a 308,367-character context containing 3,182 general-knowledge questions. Each question implicitly belonged to one of six answer types: numeric value entity human being location ab