You can translate a foreign-language stock report on your own computer with a local model runner such as Ollama: install it, download a model, and translate the report in short passages. Treat the result as a reading aid, not a verified financial translation. Keep the source beside each translated passage and check figures, names, dates, units, and wording that could reverse a claim.
What “local” means for this workflow
A local model runs inference on your computer rather than sending the prompt to a model provider’s hosted service. Ollama documents its local API at http://localhost:11434/api; local API calls do not require an API key. Ollama documents its cloud endpoint separately, where requests require authentication. If privacy is the reason for choosing local inference, check that your app or script points to the local endpoint and selects a local model—not a cloud service. See Ollama’s API introduction and authentication documentation.
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Ollama’s Privacy Policy, last updated March 2026, says: “We do not collect, store, transmit, or have access to your prompts, responses, model interactions, or other content you process locally.” That statement is about content processed locally through Ollama. It does not establish how every other application, operating-system service, or connected tool on your computer handles data. Cloud-hosted use is a separate case. Read Ollama’s Privacy Policy for its scope.
Install Ollama and download a local model
Ollama’s quickstart currently gives Gemma 4 E2B as a local example. Its download is about 7.2 GB, and Ollama recommends 8 GB of available VRAM or unified memory for this model. Those are figures for this particular model, not universal requirements for local AI or translation. With less VRAM, the system may use RAM and respond more slowly. Model names and recommendations can change, so check the Ollama quickstart when setting up.
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Install Ollama using the official Ollama download page, then open the app.
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Open a terminal and download the quickstart example with
ollama pull gemma4:e2b. -
Start an interactive local session with
ollama run gemma4:e2b. To see which models are available locally, useollama list, as described in the Ollama CLI reference.Do these 3 things before closing this tab:
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Try a short passage in the report’s original language before processing more. Confirm that the output follows your instructions and that the model is usable on your hardware.
Translate the report in manageable sections
Do not send an entire long report as one prompt. LocalAI’s documentation recommends translating one sentence or paragraph at a time. Working passage by passage also makes it easier to preserve context and check the result against the source. See LocalAI’s text-generation documentation.
Use a prompt that protects the details
Give the model a clear translation task and explicit handling rules. For example:
Translate the passage below from [source language] into [target language]. Preserve paragraph and table structure. Keep company and executive names and ticker symbols unchanged. Retain the original currencies, units, dates, and number formats. Do not convert figures. If a phrase is ambiguous or you are uncertain, mark it for review rather than guessing. Return only the translation, preserving headings and footnotes.
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This prompt is a practical way to request a careful format; it is not evidence that the model will follow every instruction or translate accurately. For a table, include its heading and labels with the relevant rows so the model has enough context, then compare the translated output with the original.
Keep the source and translation together
Work through the report by section, retaining page or section identifiers, headings, and table context. Put each original passage next to its translation rather than replacing the source. That lets you trace an unfamiliar sentence back to the report and catch formatting changes that can hide meaning.
Check the details that can change an investment conclusion
Local inference does not make a translation financially reliable by itself. The available documentation does not establish that a particular local model reliably translates financial statements or stock research across language pairs, and it provides no credible comparative benchmark or model-quality ranking for this use. Review the translation against the source, especially for:
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Numbers and formats: figures, decimal separators, percentages, currencies, units, and dates.
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Identity: company and executive names, ticker symbols, and references to subsidiaries or business segments.
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Financial language: ratios, footnotes, table labels, and distinctions between reported, estimated, and forecast figures.
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Meaning-changing wording: negation, comparisons, and direction—for example, whether a metric increased or did not increase.
These are safeguards for your review, not a guarantee of correctness. If a mistranslated detail could affect a financial decision, consult a fluent reader or another qualified source before relying on it.
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Using local inference can reduce transmission of report content to a model provider, but it does not automatically make every part of a workflow private. A separate app may use its own service or data path; confirm its endpoint and model selection. Also check whether your employer, client, or the publisher’s license permits you to process the material this way. Ollama’s product documentation is not legal advice and does not determine the terms that apply to a report you received.
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