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Ollama Silently Truncated My Context Window: A Scanner to Find Out Why

Why your local model may have lost the start of a long prompt, and a shell scanner that compares server settings, request overrides and what Ollama actually allocated.
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If a local model seems to have forgotten the start of a long prompt, the cause is often a mismatch between three numbers: what the model can support, what Ollama allocated, and what your frontend asked for on each request. This article explains how those layers interact and gives you a small shell scanner that reports what it can observe at each layer. It also says plainly which layers it cannot see.

Three different “context” numbers

Ollama’s documentation defines context length as “the maximum number of tokens that the model has access to in memory.” That is a runtime allocation, not a model trait. People mix up three separate values:

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  • Model capability: the largest context the model was built to handle. Having this capability does not mean Ollama loaded it that way.
  • Ollama’s allocation: what the server actually loaded. It comes from the app setting, the OLLAMA_CONTEXT_LENGTH server variable, a CLI /set parameter num_ctx, or an API request’s options.num_ctx.
  • The per-request value from your frontend: a chat UI or agent tool may send its own num_ctx with every call, overriding the server default.

Open WebUI documents this last case directly. If num_ctx is set in a model preset or in a chat’s advanced parameters, it is sent on every request and overrides OLLAMA_CONTEXT_LENGTH. Its guide also warns that the control prefills 2048 when toggled on, which can leave you with a far smaller context than you meant. It states that an undersized context silently truncates the prompt. That is a documented behavior of Open WebUI with Ollama. It does not prove every client behaves the same way or hides errors.

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What defaults apply?

Ollama’s current context-length documentation (checked 2026) lists defaults based on VRAM:

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The Ollama FAQ separately states a default of 4096 tokens. The two pages frame defaults differently, so don’t assume both hold on your install. These defaults depend on version, so confirm your running version and settings instead. Ollama also suggests at least 64000 tokens for web search, agents and coding tools. That is a product recommendation, and not every model or machine can support it.

The diagnostic flow

  1. Identify the setup. Note the Ollama version, the model, and how requests reach it: app, CLI, raw API, or a frontend such as Open WebUI.
  2. Read the server setting. Check OLLAMA_CONTEXT_LENGTH in the environment the server really runs in. The FAQ explains that this differs between the macOS app, a Linux systemd service and Windows. Your terminal’s environment is not necessarily the server’s.
  3. Look for request-level overrides. Inspect frontend model presets, chat advanced parameters, agent configs and any code that sets options.num_ctx. An explicit request value can override the server setting.
  4. Ask Ollama what it allocated. Load the model, then run ollama ps. Compare the CONTEXT column to your intended value, and check PROCESSOR for CPU/GPU split.
  5. Report the discrepancy as server default, request override, and observed runtime value, noting any layer you could not inspect.

A scanner you can run

This Bash script collects the evidence the steps above call for. It reads only what Ollama and your shell expose. Pass the model name as the first argument.

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#!/usr/bin/env bash
# ollama-ctx-scan.sh MODEL
MODEL="${1:?usage: $0 MODEL}"

echo "== Version =="
ollama --version

echo; echo "== Model details (capability and any baked-in parameters) =="
ollama show "$MODEL"

echo; echo "== This shell's OLLAMA_CONTEXT_LENGTH =="
echo "${OLLAMA_CONTEXT_LENGTH:-not set in this shell}"

echo; echo "== Server service environment (Linux systemd) =="
if command -v systemctl >/dev/null 2>&1 && systemctl cat ollama >/dev/null 2>&1; then
  systemctl show ollama --property=Environment
else
  echo "not visible: no systemd ollama unit found (app, Windows, macOS or container?)"
fi

echo; echo "== Loaded models (runtime allocation) =="
ollama ps

Run a request first so the model is loaded, then run the script. For a clean baseline, send a request with no overrides, then one with an explicit value:

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curl http://localhost:11434/api/generate -d '{
  "model": "MODEL", "prompt": "hi", "stream": false,
  "options": {"num_ctx": 8192}
}'
ollama ps

If CONTEXT changes to match, requests can set the allocation. If your frontend’s requests show a different number than your server variable, the frontend is the override.

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Reading the results

Server variable says one thing, ollama ps says another

Either the variable isn’t set where the server runs (a shell export doesn’t reach a systemd service or the desktop app), or a request overrode it. Check the frontend presets next. Open WebUI’s 2048 prefill is a known way to end up here.

CONTEXT is small and nothing overrides it

You are probably on a default sized to your VRAM, such as 4k on machines under 24 GiB. Raise it with the app setting, OLLAMA_CONTEXT_LENGTH, or a request option.

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PROCESSOR shows CPU offloading

The model, plus its context memory, doesn’t fully fit on the GPU. A larger context makes this worse, so raising it may slow generation.

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Raising the limit safely

A larger context uses more memory. Ollama documents that memory needs for concurrent requests scale with OLLAMA_NUM_PARALLEL * OLLAMA_CONTEXT_LENGTH. Raise the value stepwise, rerun ollama ps, and watch the PROCESSOR column. Don’t just set the maximum the model advertises; the machine, not the model card, is usually the limit.

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What this scanner can’t tell you

  • It does not identify which exact tokens were dropped. That behavior has not been verified across clients and versions.
  • It can’t see inside frontends it can’t query. Check their settings by hand.
  • A clean result doesn’t clear other causes: application-side trimming, prompt formatting, tokenization differences, or model-specific limits. Treat a mismatch as a likely context configuration issue, and verify before declaring it the cause.

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