Model Selection Guide

Here's the honest truth about AI model recommendations: by the time I write them down, they're probably already outdated. New models drop every few weeks, existing ones get updated, prices shift, and yesterday's champion becomes today's budget option.

Instead of maintaining a static list that's perpetually behind, we built something better — a real-time leaderboard showing which models BIGGI users are actually having success with right now.

Check the Live Models List

👉 See what's working today at biggi.dev/models

This isn't benchmarks from some lab. It's real usage data from developers like you, updated continuously. You'll see which models people are choosing for different tasks, what's delivering results, and how the landscape is shifting in real-time.

General Guidance

While the specifics change constantly, some principles stay consistent:

How to Select and Switch Models

  • Use the model selector in the chat prompt area to pick a model for the current session. You can also type /models to open the model picker.
  • When the selected model supports variants, type /variant to open the reasoning effort selector.
  • Set per-agent defaults and a global default in the Settings panel (Models tab), or directly in the biggi.jsonc config file.
  • Model precedence: Session override → Last picked per agent → Per-agent config → Global config → First available model from a connected provider.
  • The model selector remembers the last model you picked for each agent — switching agents restores your previous choice. A manual pick always beats config settings; use the reset button (visible when your active model differs from config) to go back to the config default.

For complex coding tasks: Premium models (Claude Sonnet/Opus, GPT-5 class, Gemini Pro) typically handle nuanced requirements, large refactors, and architectural decisions better.

For everyday coding: Mid-tier models often provide the best balance of speed, cost, and quality. They're fast enough to keep your flow state intact and capable enough for most tasks.

For budget-conscious work: Newer efficient models keep surprising us with price-to-performance ratios. DeepSeek, Qwen, and similar models can handle more than you'd expect. Review pricing and promotional tiers in your provider's dashboard before selecting one.

For local/private work: Ollama and LM Studio let you run models locally. The tradeoff is usually speed and capability for privacy and zero API costs.

Using an unlisted model? You can register any model — including fine-tunes, newly released models, or custom local models — by adding it to your config file. See Custom Models for details.

Free and Budget Model Picks

BIGGI does not bundle managed free inference. Connect a provider directly and choose any free or budget model that provider makes available, or use a local model for zero provider charges.

See Bring Your Own Provider for credentials and local models, and Usage and Costs for provider-owned billing and cost controls.

Context Windows Matter

One thing that doesn't change: context window size matters for your workflow.

  • Small projects (scripts, components): 32-64K tokens works fine
  • Standard applications: 128K tokens handles most multi-file context
  • Large codebases: 256K+ tokens helps with cross-system understanding
  • Massive systems: 1M+ token models exist but effectiveness degrades at the extremes

Check our provider docs for specific context limits on each model.

💡Tip

Be thoughtful about Max Tokens settings for thinking models. Every token you allocate to output takes away from space available to store conversation history. Consider only using high Max Tokens / Max Thinking Tokens settings with modes like Architect and Debug, and keeping Code mode at 16k max tokens or less.

💡Tip

Recover from context limit errors: If you hit the input length and max tokens exceed context limit error, you can recover by deleting a message, rolling back to a previous checkpoint, or switching over to a model with a long context window like Gemini for a message.

Models During Delegation

When an agent delegates work to a subagent (via the task tool), the subagent inherits the parent agent's model by default. You can override this per subagent in your config:

Subagents inherit the model currently active in the primary agent session — the model shown in the selector at the bottom of the chat. To bypass inheritance and pin a specific model for a subagent:

  • Via Settings — open Settings → Models → Model per Mode, find the subagent, and pick its model.
  • Via config file — edit biggi.jsonc:
{
  "agent": {
    "explore": {
      "model": "anthropic/claude-haiku-4-5"
    }
  }
}

The Settings UI writes the same agent.<name>.model entry, so either method produces the same override. Subagents without an explicit model continue to inherit whatever the invoking agent is running.

For details on configuring subagent models, see Custom Subagents.

The VS Code extension supports a vscode:// protocol handler that lets you open VS Code and automatically select a model, an agent, or both — no manual picker interaction required. This is useful for sharing model recommendations, launching a specific model tier from a web page, or switching quickly to a preferred agent.

URL Format

Include at least one of the model or agent parameters:

vscode://biggi.biggi-code/biggicode/switch?model=<modelID>
vscode://biggi.biggi-code/biggicode/switch?agent=<agentName>
vscode://biggi.biggi-code/biggicode/switch?model=<modelID>&agent=<agentName>

Replace <modelID> with a connected provider/model ID such as anthropic/claude-sonnet-4. Replace <agentName> with a visible primary agent ID such as code or plan, rather than its display name.

Example: Direct Provider Model

To open BIGGI and switch to a model from a directly connected provider, use:

vscode://biggi.biggi-code/biggicode/switch?model=anthropic%2Fclaude-sonnet-4

To switch only to Plan and use its normal model selection, specify the agent without a model:

vscode://biggi.biggi-code/biggicode/switch?agent=plan

To select both at the same time, include both parameters:

vscode://biggi.biggi-code/biggicode/switch?model=anthropic%2Fclaude-sonnet-4&agent=plan
💡Tip

URL-encode the / in model IDs as %2F when embedding this URL in HTML links or other contexts where bare slashes may be misinterpreted.

How It Works

  • VS Code open: the BIGGI sidebar is focused and the linked selection is applied to the active session immediately.
  • VS Code closed: VS Code launches, then applies the selection once the extension is ready.
  • When model is provided, it must identify a model in the current connected-provider catalog. Invalid or unavailable models cause the deep link to be ignored.
  • When agent is provided, it must identify a visible primary agent. Invalid or unavailable agents cause the deep link to be ignored.
  • An agent-only link uses the model that would normally be selected for that agent. When both parameters are present, the agent is selected first so the linked model applies to it.
  • The selection follows the same precedence as using the pickers: it updates the active session, or the next session when no session is active. It does not change your configured defaults in settings.

Sharing and Embedding

You can embed these links in a web page:

<a href="vscode://biggi.biggi-code/biggicode/switch?model=anthropic%2Fclaude-sonnet-4&amp;agent=plan">
  Open BIGGI with Claude Sonnet in Plan
</a>

Or share as a plain URL that users can paste into their browser's address bar.

Stay Current

The AI model space moves fast. Bookmark biggi.dev/models and check back when you're evaluating options. What's best today might not be best next month — and that's actually exciting.