DeepSeek V4.1 Flash Accuracy: What the 1M-Token Claim Proves

DeepSeek V4.1 Flash supports up to a one-million-token context window, but this capacity does not guarantee reliable interpretation of every detail in long documents, particularly when PDFs contain OCR errors, tables, footnotes, repeated headers, or conflicting revisions. Its model card reports a 45.2 exact-match score on LongBench-V2 for the V4.1 Flash base model in a one-shot setting, but this benchmark result is not equivalent to an accuracy rate for real-world PDFs or the newer V4.1-Flash-1017 API build, for which no updated long-document benchmark score is cited. The text recommends using the model for fast retrieval, source mapping, first-pass synthesis, and evidence-supported drafting, while requiring page-level citations, checks of surrounding context, explicit handling of uncertainty and absent information, and human review for high-impact decisions. It outlines a repeatable evaluation method using fixed source files, independently prepared answer keys, task categories such as lookup, cross-section reasoning, exceptions, version conflicts, and abstention, and scoring for correct, partial, wrong, unsupported, or appropriately declined answers. It also advises preserving raw inputs and outputs, testing citations against original pages and table headers, recording model versions and token usage, and treating provider pricing examples as estimates that depend on actual billed input and output tokens.

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