Coding · Head-to-head

Windsurf vs LFM2.5-2.6B

Windsurf (freemium, AI Score 7.2/10) vs LFM2.5-2.6B (free, AI Score 8/10). Side-by-side pricing, features, pros and cons, and which to pick.

The verdict

Pick Windsurf if…
  • your primary use case is developers already productive in windsurf's cascade workflow who have no urgent reason to migrate, and teams evaluating cognition's stack who want an editor-side agent sitting alongside devin's cloud agents.
Try Windsurf →
Pick LFM2.5-2.6B if…
  • budget is the constraint
  • overall capability matters more than price (AI Score 8 vs 7.2)
  • your primary use case is mobile and edge developers building offline agents for ios or android who need dependable tool calling from a model small enough to ship inside the app, with no hosted api in the loop.
Try LFM2.5-2.6B →

Side-by-side specs

Spec Windsurf LFM2.5-2.6B
Category Coding Coding
Pricing model freemium free
Headline pricing Free tier; paid plans from $20/mo (the Devin lineup now served at windsurf.com) — verify before buying Free open weights — self-host only, no hosted API
Free tier Yes, but it is credit-metered and is Devin's free tier, not the unlimited-basic-completions-forever tier this entry once described. That tier no longer exists. Confirm current allowances on the live pricing page before relying on it. The entire model is free to download and run — the only cost is the hardware you run it on and the licence terms you agree to.
AI Score 7.2/10 8/10
Best for Developers already productive in Windsurf's Cascade workflow who have no urgent reason to migrate, and teams evaluating Cognition's stack who want an editor-side agent sitting alongside Devin's cloud agents. Mobile and edge developers building offline agents for iOS or Android who need dependable tool calling from a model small enough to ship inside the app, with no hosted API in the loop.
Editor's pick
Use cases development agents development agents
Date added 2025-06-01 2026-08-06

Pros and cons

Windsurf logo

Windsurf

Coding · freemium

Pros

  • Cascade remains one of the better-designed agent loops: it plans, edits across files, runs commands, reads output and iterates without needing constant re-prompting
  • Repo-wide indexing means the agent locates the relevant files itself instead of making you paste context
  • Mixes cheap in-house SWE-series models for routine edits with frontier models for hard problems, so agent runs are not uniformly expensive
  • Enterprise self-hosted and air-gapped deployment with zero data retention, which Cursor does not offer at any tier
  • Full VS Code fork with terminal execution and file-write access, not a chat sidebar bolted onto an editor

Cons

  • ×The founding team including CEO Varun Mohan left for Google DeepMind in July 2025 and Cognition bought what remained, so an independent product roadmap is not a safe assumption
  • ×windsurf.com resolved to Cognition's Devin site when checked on 2026-08-10, meaning the plans a buyer actually encounters are Devin's and no Windsurf-branded price could be confirmed on any live page
  • ×Cursor and Claude Code have caught up on multi-file agentic work, erasing the 2025 lead this entry's original 9.1 score was built on
  • ×Pricing is credit-metered and hard to forecast for a team; the unlimited free tier that once made the product an easy recommendation is gone
LFM2.5-2.6B logo

LFM2.5-2.6B

Coding · free

Pros

  • Runs entirely offline on phone- and laptop-class hardware, so there is no per-token cost and no user data leaves the device
  • Tuned specifically for tool calling and multi-step execution rather than conversation — the weak spot for most models this size
  • Open weights you can fine-tune, quantize and ship inside your own application, with no endpoint a vendor can deprecate
  • First-party mobile deployment path (LEAP SDK for iOS/Android, Apollo app) instead of leaving you to port it yourself
  • Architecture picked for CPU and NPU throughput, which is the constraint that actually bites on edge hardware

Cons

  • ×Licence is Liquid's own LFM Open License with a company-revenue threshold, not Apache 2.0 or MIT — a real disadvantage against Qwen, Gemma and SmolLM checkpoints in the same weight class
  • ×No hosted API at all — you own inference, quantization, updates and the ops burden that comes with them
  • ×At 2.6B parameters it will not hold a long-horizon coding session or deep multi-file reasoning; this is a weight class for bounded, tool-mediated tasks
  • ×Vendor-published benchmarks remain largely un-replicated by independent evaluators, so treat the launch numbers as a starting hypothesis rather than a result
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Updated 2026-08-10. Spec data sourced from official product pages and tracked in our public directory at /tools.