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AI coding assistants · November 2026 Edition

Windsurf vs Tabnine

Zero of fourteen models named Windsurf first on the direct prompt; zero named Tabnine. Windsurf was named by eleven of the fourteen models and Tabnine by twelve and Windsurf carries 27 labels and Tabnine 39, so the shares are not directly comparable.

Windsurf

accepted challenger

Named in one category this edition.

Tabnine

accepted challenger

Named in one category this edition.

First-choice share4%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate11%3%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 11; printed, not drawn.
Labels2739A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Windsurf reading right to left. Rank and label count are printed, not drawn.GitHub Copilot was named alongside these two in thirteen of the fourteen direct answers. GitHub Copilot vs Windsurf · GitHub Copilot vs Tabnine · Windsurf vs Cursor

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the AI coding assistants page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
WindsurfFirst choices, of fourteen modelsTabnine
Direct00
Paraphrase001 against Windsurf
Comparative10
Budget-constrained21
Scale-constrained00
Negative022 against Windsurf · 1 against Tabnine
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the November 2026 Edition, Windsurf and Tabnine were named in the same answer thirty-seven times, of the 77 answers naming Windsurf and the 106 naming Tabnine. In those answers Tabnine took the first choice three times and Windsurf two.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Windsurf and Tabnine stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
Windsurf Tabnine first choice named as an alternative argued againstblank: not namedEach cell is one answer, Windsurf on the left and Tabnine on the right.

The direct prompt

The plain question, one answer per model, grouped by where Windsurf and Tabnine stood in it.

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashGitHub Copilot alternatives: Cursor, Tabnine, Windsurf
Perplexity SonarGitHub Copilot alternatives: Claude Code, Cursor, Tabnine
Llama 4 MaverickGitHub Copilot alternatives: Claude Code, Cursor, Windsurf
Kimi K2GitHub Copilot alternatives: Amazon Q Developer, Tabnine
GLM 4.7 FlashXGitHub Copilot alternatives: Tabnine, Windsurf
Muse Glimmer 30BGitHub Copilot alternatives: Amazon Q Developer, Cursor, Tabnine

Neither was named

8 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Claude, GitHub Copilot
GPT-5.4 miniGitHub Copilot Business or Enterprise alternatives: Amazon Q Developer, Cursor
Grok 4.20GitHub Copilot alternatives: Amazon Q Developer, Anthropic, Claude Code, Cursor, Gemini Code Assist
Mistral SmallGitHub Copilot alternatives: Claude Code, Cursor, Superblocks
DeepSeek V4 FlashGitHub Copilot alternatives: Amazon Q Developer, Claude Code, Cursor, Sourcegraph Cody
Qwen 3.7 FlashGitHub Copilot alternatives: Anthropic, Augment Code, Claude Code, Cursor
MiniMax M2.5GitHub Copilot alternatives: Amazon Q Developer, Claude Code, Cursor, Sourcegraph Cody
GPT-6 LunaGitHub Copilot alternatives: Claude Code, Cursor

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Windsurf leads by ten points.
Windsurf10%#3 of 9
Tabnine0%#6 of 9
The full small business standing →
Mid-marketThe figures above
Windsurf leads by two points.
Windsurf4%#2 of 11
Tabnine2%#3 of 11
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Windsurf0%#8 of 9
Tabnine0%#4 of 9
The full enterprise standing →

What the models said about Windsurf

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.

“the individual version collects data by default, while enterprise versions offer zero-data-retention” DeepSeek V4 Flash · negative prompt · soft negative
“cloud versions still risk data exfil. Some studies show similar vuln introduction rates.” Grok 4.20 · negative prompt · soft negative
“Free tier available, but less capable on complex tasks per benchmark studies” GLM 4.7 FlashX · paraphrase prompt · soft negative
“Codeium — Best Overall for Small Teams ... If you want zero cost and basic autocomplete: Go with Codeium.” GLM 4.7 FlashX · budget prompt · first choice
“Pick Cursor or Windsurf if: You want the most seamless experience for multi-file refactoring” Gemini 3.5 Flash · comparative prompt · first choice
“Start with Codeium (Free). Ask your engineers to try the free version.” Qwen 3.7 Flash · budget prompt · first choice

What the models said about Tabnine

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.

“cloud versions still risk data exfil. Some studies show similar vuln introduction rates.” Grok 4.20 · negative prompt · soft negative
“Explicitly commits to not storing or training on user code, even in free tiers. Supports fully air-gapped deployments.” DeepSeek V4 Flash · negative prompt · first choice
“Cursor (free tier or Pro) or Tabnine (free tier) are excellent starting points” MiniMax M2.5 · budget prompt · first choice
“Self-hosted/air-gapped options; explicit "code never trains our models" policy” Kimi K2 · negative prompt · first choice
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.