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Best Model for Continue

Continue is built for model freedom, including local models via Ollama, so picks span cloud quality and private, low-cost open weights. Claude Sonnet 4.6 is the best hosted driver; for a true $0 or privacy-first setup, open models like Qwen3 235B, DeepSeek V3.2, Codestral, and Llama 4 Maverick run well locally or cheaply hosted.

Read the full Continue review → · updated 2026-06-22
#1Claude Sonnet 4.6Anthropic · $6.60/1M · 1M ctx

The best hosted quality for Continue's chat, autocomplete, and edits.

Overall 91/100 · Value 46 · 78% community winFull breakdown →
#2Qwen3 235B A22BAlibaba (Qwen) · $0.09/1M · 262K ctx

A capable open-weight MoE you can self-host — efficient enough for local Continue setups.

Overall 82/100 · Value 99 · 74% community winFull breakdown →
#3DeepSeek V3.2DeepSeek · $0.26/1M · 131K ctx

Dependable open-weight quality at very low cost — a staple Continue default.

Overall 77/100 · Value 84 · 71% community winFull breakdown →
#4CodestralMistral · $0.48/1M · 256K ctx

Fast, cheap code completions — a natural fit for Continue's inline autocomplete.

Overall 72/100 · Value 70 · 69% community winFull breakdown →
#5Llama 4 MaverickMeta · $0.28/1M · 1.0M ctx

Broad local-runtime support and a 1M context for private, low-cost setups.

Overall 76/100 · Value 80 · 71% community winFull breakdown →
#6GPT-5.4 MiniOpenAI · $1.88/1M · 400K ctx

A cheap, fast hosted option when you don't want to run anything locally.

Overall 82/100 · Value 58 · 74% community winFull breakdown →

FAQ

What is the best model for Continue?
Claude Sonnet 4.6 for hosted quality; for local or privacy-first setups, Qwen3 235B, DeepSeek V3.2, Codestral, and Llama 4 Maverick are strong. Continue's model freedom lets you mix a local autocomplete model with a hosted chat model.
Can Continue run fully local models?
Yes — Continue supports local models via Ollama and similar runtimes, so you can run open-weight models like Llama 4, Qwen3, or DeepSeek entirely on your own machine for $0 and full privacy.

The model is half the story — the agent is the other half

The model picks the moves; the agent runs the loop, the tools, and the guardrails. Once you've chosen a model, see which agent gets the most out of it.

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