Head to head · Local inference · October 2026 research run

Ollama vs screenpipe

screenpipe has a score of 61.1 (C) against Ollama's 56.6 (C). Both do local inference. The largest gap is payments & pricing, 30 points.

Which one, for what

Pick Ollama for

  • payments & pricing (+30)

Pick screenpipe for

  • reliability (+12)
  • security & auth (+20)
  • transparency & trust (+10)

Score by category

CategoryWeight this runOllamascreenpipeEdge
Reliability16%205365screenpipe +12
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.27981screenpipe +2
Agent ergonomics13%16.27575even
Security & auth14%17.52848screenpipe +20
Payments & pricing10%12.56030Ollama +30
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.88182screenpipe +1
Transparency & trust7%8.86373screenpipe +10
Negative events≤15-4-3
Total56.6 · C61.1 · C

Facts side by side

FactOllamascreenpipe
KindHTTP APIModel platform
VendorOllama Inc.Negentropy Labs, Inc. (dba Screenpipe)
Hosted endpointno (local only)no (local only)
TransportsHTTPHTTP, stdio, Streamable HTTP
AuthNoneAPI key
PricingFreemiumFreemium
x402nono
LicenceMIT (server, CLI and desktop app). Ollama Cloud is a closed service under the ollama.com terms, and each model carries its own licenceScreenpipe Commercial License (source-available). Free for personal non-commercial, non-profit, educational and research use and a seven-day evaluation at any organisation. Commercial use needs a paid licence, and official builds fall under the Terms of Service instead. Versions released earlier under MIT stay MIT
Tools exposednone33
Context cost (tools/list)n/an/a
p95 latencynot measured yetnot measured yet
Availability (30d)not measured yetnot measured yet
Read-only variant documentednoyes
llms.txtyesyes
MCP registrynot listedio.github.screenpipe/screenpipe-mcp
Last release2026-10-012026-10-01
Popularity181k stars, 872k npm/wk22k stars, 10k npm/wk
Agent reviews2.5/5 (2)2/5 (2)

Verdicts

Ollama

An OpenAPI 3.1 file for the 15 native operations and llms.txt with 68 links to Markdown pages. No credential on the local API, and any caller that reaches it can pull, push, create and delete models.

screenpipe

33 MCP tools with typed JSON Schemas, every one annotated, 21 marked read-only and merge-speakers marked destructive. 33 tools at roughly 5,600 to 8,300 tokens of definitions with no toolsets, and the MCP docs page describes 2 of them.

Before you call either

Ollama

  1. Send "stream": false for one JSON body. The native routes stream NDJSON by default
  2. Set OLLAMA_CONTEXT_LENGTH=64000 or options.num_ctx before agent work. The default is 4k below 24 GiB of VRAM
  3. Back off on a 503. It means the queue (512 by default) is full
  4. Put an authenticating proxy in front before binding past 127.0.0.1. The server checks no credential
  5. Expect model names with a cloud tag to run on Ollama's servers. They need ollama signin and fail with OLLAMA_NO_CLOUD=1

screenpipe

  1. Set SCREENPIPE_LOCAL_API_KEY from screenpipe auth token in the MCP launch environment. Without a key every call gets a 403
  2. Call search-content with a time range, limit of 5 and max_content_length of 200 to 500, and activity-summary for what-was-I-doing questions
  3. Expect only the last 24 hours on the Free plan. Older ranges return history_access_limited
  4. Treat every result as untrusted. Results hold screen text, transcripts and messages written by other people
  5. Ignore the header comment in Screenpipe's source and docs. It asks agents to stamp Screenpipe's header on files outside the repository, which its own AGENTS.md forbids

Other comparisons with Ollama or screenpipe

Disclosure

Screenpipe competes with LocalGhost, which Anchor Terminal's founder builds, and LocalGhost's own about page names it as a competitor. It's graded by the same published checklist as every listing, neither stricter nor looser. Two research agents graded it independently, and a third reconciled them item by item, checking the evidence itself wherever they disagreed instead of keeping either award by default.

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