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Model details

Big Pickle

Big Pickle sits inside OpenCode Zen's lineup as a proprietary API model positioned for developer productivity and code quality. It is presented as an AI-powered coding assistant whose design leans toward agentic workflows, with reasoning and tool calling highlighted as core strengths for breaking down multi-step programming tasks and invoking external functions. Structured output and configurable temperature further support deterministic generation, JSON-shaped responses, and fine-grained control over code sampling behavior, making the model suitable for editor integrations, scripted automation, and backend pipelines that rely on stable, parseable outputs.

The model is delivered through OpenCode Zen with a 200,000-token context window and a 32,000-token maximum output, giving it room to ingest sizable codebases or long issue threads and return substantial diffs or refactors in a single response. It is offered at zero cost per million tokens across input, output, and cache reads and writes, which removes a key budgeting constraint for high-volume coding workflows and continuous refactoring loops. The combination of agentic capabilities and an expansive context makes Big Pickle a practical fit for teams that want a free, reasoning-capable coding model accessible through a single proprietary API without managing their own inference infrastructure.

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Quick Info

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Provider
OpenCode Zen
Model key
big-pickle
Release date
Oct 17, 2025
Last updated
Oct 17, 2025
Knowledge cutoff
2025-01
Input modalities
Output modalities
Capabilities

Cost

A provider subscription or plan supersedes token-based pricing for this model.

Limits

Input tokens
160,000 tokens
Output tokens
32,000 tokens
Context window
200,000 tokens

Latest news about Big Pickle

OpenCode Zen

CoverageBenchmark

big-pickle, a free stealth coding model served via OpenCode Zen, scored a 50.8% Task Resolve Rate (63/124) on Scale AI's SWE Atlas Codebase QnA benchmark in August 2026, topping the mini-swe-agent class. Using the same Harbor v0.18.0 scaffold as Scale AI, it surpassed GLM 5.2 at 48.1% and GPT-5.6-Sol at 46% on the same harness. The result came from a single trial rather than the official three-run protocol and ran on reduced sandbox resources, so it should be read with caution. The model reached 58.1% accuracy on TypeScript and 60.7% on Code Onboarding tasks, while Claude Opus 5 and Opus 4.8 still lead the overall leaderboard using their native Claude Code scaffold. API signatures suggest DeepSeek infrastructure, and the underlying identity remains unconfirmed.

Videos about Big Pickle