Big Pickle: OpenCode Zen Stealth Model
Updated: 2026-09-07Everything you need to decide: what Big Pickle does, who it fits, and whether it is free.
Big Pickle is a stealth model from OpenCode Zen—you get the capability without knowing which underlying model powers it. What matters is output quality.
- Model ID
- big-pickle
- Provider
- OpenCode Zen
- API
- openai-completions
- Base URL
- https://opencode.ai/zen/v1
- Context
- 200,000 tokens
- Max output
- 32,000 tokens
- Input
- text
- Reasoning
- ✓
- Pricing
- USD 0 input · USD 0 output · USD 0 cache read · USD 0 cache write
200,000-token context window. Feed it an entire module or small project—it reads and modifies across files.
32,000-token max output. Enough for complete implementation plans, multi-layer patches, or detailed architecture docs.
Reasoning enabled. Built for complex refactors, hard-to-reproduce bugs, and architecture trade-offs—anything that needs multi-step thinking.
Text input. Paste code, describe requirements, provide context—pure text, no image input.
How to use it
- 1.Select or configure Big Pickle in OpenCode with the model ID big-pickle and your OpenCode Zen API key.
- 2.Pi records the API as openai-completions and the Base URL as https://opencode.ai/zen/v1; prefer the official OpenCode installer and model-selection flow.
- 3.Put the task, constraints, and relevant code into your text prompt, use reasoning and the long context for implementation, review, or debugging, then validate the result.
Use cases
- Cross-file reading and modification in large codebases—200k context fits.
- Debug hard-to-reproduce bugs and document reproduction steps—reasoning breaks down causality.
- Compare architecture options, weigh risks, and get an actionable rollout plan.
- Draft refactor patches, tests, and migration docs in one pass.
FAQ
What is Big Pickle?
A stealth model from OpenCode Zen. You get the capability without knowing which underlying model powers it.
Is Big Pickle free now?
Yes. Currently USD 0 across the board—limited-time offer, confirm before committing.
When should I use Big Pickle?
When the task needs long context, reasoning, or cross-file understanding—large-codebase refactors, hard-to-reproduce bugs, architecture comparisons.
Configuration
{
"providers": {
"opencode": {
"apiKey": "YOUR_API_KEY",
"models": [
{
"id": "big-pickle",
"name": "Big Pickle",
"reasoning": true,
"input": [
"text"
],
"contextWindow": 200000,
"maxTokens": 32000,
"cost": {
"input": 0,
"output": 0,
"cacheRead": 0,
"cacheWrite": 0
},
"compat": {
"supportsStore": false,
"supportsDeveloperRole": false,
"maxTokensField": "max_tokens"
}
}
],
"api": "openai-completions",
"baseUrl": "https://opencode.ai/zen/v1"
}
}
}Compatibility
| Feature | Value |
|---|---|
| supportsStore | No |
| supportsDeveloperRole | No |
| supportsReasoningEffort | Yes |
| supportsUsageInStreaming | Yes |
| maxTokensField | max_tokens |
| requiresToolResultName | No |
| requiresAssistantAfterToolResult | No |
| requiresThinkingAsText | No |
| requiresReasoningContentOnAssistantMessages | No |
| thinkingFormat | openai |
| openRouterRouting | — |
| vercelGatewayRouting | — |
| chatTemplateKwargs | — |
| zaiToolStream | No |
| supportsStrictMode | Yes |
| cacheControlFormat | None |
| sendSessionAffinityHeaders | No |
| supportsLongCacheRetention | Yes |