Built-In Tools vs Custom Tools in LLM Agents
In an AI agent, a tool is anything the model can ask to use, like a search engine, a database lookup or a shell command. The model does…
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LLMs
Language models produce text from the input they receive. Their capabilities, costs and limits affect the products built with them.
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Articles
How Floating-Point Determinism Affects LLM Reproducibility
Running the same prompt through the same LLM does not always give the same output, even with temperature 0 and a fixed seed. One reason is floating-point arithmetic.…
Read articleCan Provider Routing Change LLM Outputs?
Provider routing can change an LLM's output when a request reaches a different model version, fallback model, parameter configuration, precision level, inference engine, region, or runtime environment. Provider…
Read articleHow Model Updates Break LLM Reproducibility
A large language model (LLM) generates text, structured data, code, or tool calls from prompts. Hosted LLMs are not fixed functions of prompt text: providers can change models,…
Read articleWhat Is a System Fingerprint in LLM APIs?
When an LLM API response includes a field such as systemfingerprint, it is identifying the provider’s backend configuration, not your prompt, account, device, or system message. The value…
Read articleIs the Same Prompt Always the Same LLM Input?
No. The text you type into a chat box is only one part of what a large language model (LLM) receives. The full request can also contain system…
Read articleCan Tokenizer Changes Affect LLM Output?
Yes. A tokenizer converts text into a sequence of integer identifiers called token IDs before a large language model (LLM) processes it. A token might represent a whole…
Read articleHow to Test a Nondeterministic LLM Application
When an application calls an LLM, the same input can produce a different response on the next run. A test that compares the response with one expected string…
Read articleWhat Is Batch Invariance in LLM Inference?
Batch invariance means a request produces the same inference result when the server runs it alone, alongside other requests, at a different batch position, or under another supported…
Read articleHow Does Mixture-of-Experts Routing Affect LLM Repeatability?
If you send the same prompt to a mixture-of-experts (MoE) model several times at temperature 0, the answers can still differ. Routing is one possible reason. In each…
Read articleDo Structured Outputs Make LLM Responses Deterministic?
No. For a large language model (LLM), structured outputs make responses more predictable in format, not necessarily in content or execution. A structured output is data generated to…
Read articleDoes Setting a Seed Make LLM Output Reproducible?
No. A seed can improve repeatability, but it does not guarantee identical large language model (LLM) output. It initializes the pseudorandom number generator used in token sampling; it…
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