llmfit vs Continue
Detailed side-by-side comparison to help you choose the right tool
llmfit
🔴DeveloperDeveloper Tools
llmfit review covering its local LLM VRAM, quantization, context, and RAM calculators, practical uses, limitations, pricing uncertainty, and alternatives.
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🔴DeveloperDeveloper Tools
Open-source AI coding assistant for VS Code and JetBrains — bring any model, any MCP server, and share reusable rules and agents across your team via Continue Hub.
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llmfit - Pros & Cons
Pros
- ✓Answers a narrow hardware-sizing question quickly
- ✓Shows context and quantization tradeoffs before a large download
- ✓No account is required for the public calculators
Cons
- ✗An estimate cannot replace a benchmark on the exact runtime and hardware
- ✗The site did not expose clear commercial or licensing terms during research
- ✗Recommendations do not measure answer quality for a specific workload
Continue - Pros & Cons
Pros
- ✓Open-source assistant for VS Code and JetBrains. This directly supports the primary workflow.
- ✓Bring-your-own-model: Anthropic, OpenAI, Ollama, local, any provider.
- ✓First-class MCP client — any MCP server becomes callable tools.
- ✓Continue Hub for sharing assistants, rules, prompts across a team.
Cons
- ✗At least one tier requires a sales quote, preventing a complete public budget calculation.
- ✗Features and limits can change by plan, billing interval, region, and release; verify current documentation.
- ✗MCP connectivity expands the permission surface and requires narrow scopes, approvals, logs, and credential rotation.
- ✗A representative pilot is necessary because a feature list does not establish reliability or operational fit.
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